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World J Crit Care Med. Jan 9, 2022; 11(1): 1-21
Published online Jan 9, 2022. doi: 10.5492/wjccm.v11.i1.1
Precision medicine in sepsis and septic shock: From omics to clinical tools
Juan Carlos Ruiz-Rodriguez, Luis Chiscano-Camón, Adolfo Ruiz-Sanmartin, Marcos Pérez-Carrasco, Clara Palmada, Ricard Ferrer, Intensive Care Department, Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Barcelona 08035, Spain
Juan Carlos Ruiz-Rodriguez, Erika P Plata-Menchaca, Luis Chiscano-Camón, Adolfo Ruiz-Sanmartin, Marcos Pérez-Carrasco, Ricard Ferrer, Shock, Organ Dysfunction and Resuscitation Research Group, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Barcelona Hospital Campus, Barcelona 08035, Spain
Juan Carlos Ruiz-Rodriguez, Luis Chiscano-Camón, Adolfo Ruiz-Sanmartin, Ricard Ferrer, Departament de Medicina, Universitat Autònoma de Barcelona, Bellaterra 08193, Spain
Erika P Plata-Menchaca, Department of Intensive Care, Hospital Clínic de Barcelona, Barcelona 08036, Spain
Vicent Ribas, Data Analytics in Medicine, Digital Health Unit, Eurecat, Centre Tecnològic de Catalunya, Barcelona 08005, Spain
Mónica Martínez-Gallo, Manuel Hernández-González, Immunology Division, Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Barcelona 08035, Spain
Mónica Martínez-Gallo, Manuel Hernández-González, Diagnostic Immunology Research Group, Vall d’Hebron Institut de Recerca (VHIR), Vall d’Hebron Barcelona Hospital Campus, Barcelona 08035, Spain
Mónica Martínez-Gallo, Manuel Hernández-González, Department of Cell Biology, Physiology and Immunology, Universitat Autònoma de Barcelona, Bellaterra 08193, Spain
Juan J Gonzalez-Lopez, Nieves Larrosa, Department of Clinical Microbiology, Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, Barcelona 08035, Spain
Juan J Gonzalez-Lopez, Nieves Larrosa, Department of Microbiology and Genetics, Universitat Autònoma de Barcelona, Bellaterra 08193, Spain
ORCID number: Juan Carlos Ruiz-Rodriguez (0000-0001-7392-8617); Erika P Plata-Menchaca (0000-0002-9050-2658); Luis Chiscano-Camón (0000-0003-0037-0610); Adolfo Ruiz-Sanmartin (0000-0001-5587-5419); Marcos Pérez-Carrasco (0000-0001-7086-083X); Clara Palmada (0000-0003-0463-4070); Vicent Ribas (0000-0002-7266-6106); Mónica Martínez‐Gallo (0000-0002-7340-2161); Manuel Hernández-González (0000-0002-6932-5853); Juan J Gonzalez-Lopez (0000-0003-2419-5909); Nieves Larrosa (0000-0001-8808-0233); Ricard Ferrer (0000-0002-4859-4747).
Author contributions: Ruiz-Rodríguez JC contributed to manuscript design, conception, and coordination; Plata-Menchaca EP organized the manuscript generation process and revised the style and format of the manuscript; Ruiz-Rodríguez JC, Plata-Menchaca EP, Chiscano-Camón LS, Ruiz-Sanmartin A, Pérez-Carrasco M, Palmada C, Ribas V, Gallo MM, Hernández M, González-López JJ, Larrosa MN and Ferrer R provided important intellectual contributions to each section of the manuscript, including performance of writing and revision; all authors have read and approve the final manuscript.
Conflict-of-interest statement: The authors declare having no conflicts of interest.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Juan Carlos Ruiz-Rodriguez, MD, PhD, Consultant Physician-Scientist, Intensive Care Department, Vall d’Hebron Hospital Universitari, Vall d’Hebron Barcelona Hospital Campus, 119, Passeig de la Vall d'Hebron, Barcelona 08035, Spain. jcruiz@vhebron.net
Received: April 26, 2021
Peer-review started: April 26, 2021
First decision: June 17, 2021
Revised: June 23, 2021
Accepted: December 22, 2021
Article in press: December 22, 2021
Published online: January 9, 2022
Processing time: 253 Days and 18.4 Hours

Abstract

Sepsis is a heterogeneous disease with variable clinical course and several clinical phenotypes. As it is associated with an increased risk of death, patients with this condition are candidates for receipt of a very well-structured and protocolized treatment. All patients should receive the fundamental pillars of sepsis management, which are infection control, initial resuscitation, and multiorgan support. However, specific subgroups of patients may benefit from a personalized approach with interventions targeted towards specific pathophysiological mechanisms. Herein, we will review the framework for identifying subpopulations of patients with sepsis, septic shock, and multiorgan dysfunction who may benefit from specific therapies. Some of these approaches are still in the early stages of research, while others are already in routine use in clinical practice, but together will help in the effective generation and safe implementation of precision medicine in sepsis.

Key Words: Sepsis; Septic shock; Organ dysfunction; Precision medicine; Biomarkers; Phenotype; Endotype

Core Tip: Sepsis is a heterogeneous disease with different clinical courses and several clinical phenotypes. Precision medicine in sepsis allows the identification of specific subgroups of patients who may benefit from a personalized approach with interventions targeted towards specific pathophysiological mechanisms.



INTRODUCTION

Sepsis requires a structured and protocolized treatment, which have been thoroughly reviewed in the literature[1-3]. The last version of the Surviving Sepsis Campaign (SSC) guidelines was released in 2021[4], and the hour-1 bundle was updated in 2018[5]. The implementation of the SSC recommendations and bundles[6] is associated with a sustained reduction in the risk of death. Still, mortality from sepsis remains unacceptably high[7].

All patients with sepsis are candidates for receipt of the main pillars of sepsis treatment: Infection control, initial resuscitation, and multiorgan support. However, specific subgroups of patients not responding to conventional therapies may benefit from other therapies, which can be considered therapeutic rescue strategies.

Currently, sepsis is defined as organic dysfunction associated with a dysregulated response of the host to infection[8]. The host response is initiated when bacterial endotoxin or other bacterial structures interacting with the host´s immune system stimulate the production of a cascade of immune mediators that activate and target leukocytes, leading to organ dysfunction.

SEPSIS: A HETEROGENEOUS DISEASE

We have to ask ourselves whether all septic patients' clinical courses are predictable. Does dysregulated host response to infection progress and manifest similarly in all patients? The answer is clear and resounding: No. In sepsis, there is significant heterogeneity between individuals. In a certain way, such heterogeneity is foreseen based on the existing differences in age, causative microorganisms, types of sepsis foci, and comorbidities. Pathophysiologically, there are also significant differences. The inflammatory response occurs in two distinct stages: The pro-inflammatory and the anti-inflammatory phases. These phases vary among individuals and within the same individual, depending on a particular moment within the clinical course. This could explain the observed heterogeneity in responses to available immunomodulating treatments (e.g., corticosteroids, elimination of cytokines, and anti-cytokine antibodies).

Therefore, patients with a low risk for adverse outcomes are candidates to receive conventional treatments. In contrast, patients with a high risk of clinical deterioration could benefit from specific therapies addressing their particular pathophysiological characteristics. This gives rise to so-called ‘precision medicine’. This term comes from oncology and described the adaptation of a treatment to each patient’s traits based on the genomic study and the molecular characteristics of tumors.

In this narrative review, we explain the different strategies to create and implement precision medicine for sepsis, with the intent of supporting individualization of patients’ management (Figure 1). In the first part of this manuscript, we will review the technologies developed to identify endotypes and phenotypes (omics-based biomarkers, bioinformatics, and biomarkers commonly used in the clinic). In the second part of the manuscript, we will describe the different endotypes with their specific potential treatments (e.g., immunoglobulins, endotoxin- and cytokine-hemadsorption, restoration of immunoparalysis) (Table 1). Omics-based biomarkers research is still in the early stages, while other biomarkers are now available and in use in the clinic.

Figure 1
Figure 1 Strategies to create precision medicine in sepsis.
Table 1 Clinical applicability of precision medicine strategies.
Precision medicine strategy
Target (s)
Clinical application
Genomics and epigenomicsGenetic variantsPrognosis, severity
GenotypesSusceptibility to sepsis
Transcriptomics Gene expression profiles, activity and regulationSusceptibility to sepsis
Sepsis response signaturesSeverity, prognosis
MetabolomicsSmall molecules produced by cellsPrognosis
Metabolomic profileResponse to treatment
ProteomicsProteins expressed by the genome under certain conditionsDiagnosis, Prognosis
BiomarkersDiagnosis, prognosis
BioinformaticsMachine learning techniquesDiagnosis
Prediction of clinical trajectories
Assessment and treatment of organ dysfunction
Clinical phenotypes
BiomarkersLevels of molecules (mostly inflammatory)Phenotypes
Antimicrobial stewardship
Prediction of organ dysfuntion
Allocation of hospital resources
Diagnosis
Severity
ImmunoglobulinsImmunoglobulin levelsDetection and treatment of sepsis-associated hypogammaglobulinemia
Endotoxin and hemoadsoptionEndotoxin levels and elimination by hemoadsoptionRescue therapy
Cytokines and hemoadsoptionCytokine levels and elimination by hemoadsoptionRescue therapy
ImmunoparalysismHLA-DR expressionImmunoparalysis detection
Immunoadjuvant treatment
Stratification of patients
GM-CSF therapy
TECHNOLOGIES DEVELOPED TO IDENTIFY ENDOTYPES AND PHENOTYPES
Omics technologies

Novel technologies have been developed in recent years to detect different evolutionary patterns or other patterns in response to different therapies in sepsis. Omics-based biomarkers and bioinformatics can select various endotypes and phenotypes of sepsis patients indistinguishable from the clinical point of view at the bedside. Therefore, they help in the adaptation of specific therapies to patients according to their individual characteristics[9].

Genomics and epigenomics: Genomics is defined as the study of genes and their functions. The different clinical presentations and prognoses of sepsis patients have already been associated with particular genetic variants. A genetic polymorphism is an allelic variant that exists in an unalterable state in a population, with a frequency (generally > 1%) that cannot be accounted for by new mutations. Various polymorphisms have been described in the genes that encode pro-inflammatory and anti-inflammatory cytokines. This is also true for cytokine receptors, cellular recognition pathways, intracellular signaling pathways, and hemostasis molecules. All these pathways are involved in the severity and risk of mortality in sepsis[10].

Epigenomics studies the additional changes that alter gene expression without changing the DNA sequence. These include DNA methylation, non-coding (nc)RNAs, histone variants, and histone post-translational modifications. Epigenetic modifications can respond to environmental stimuli by activating or inhibiting gene transcription. Lorente-Sorolla et al[11] showed that sepsis patients undergoing widespread changes in the methylome of their circulating monocytes had associated aberrant levels of interleukin (IL)-10 (IL-10) and IL-6, and a high occurrence of organ dysfunction. Changes in histone modifications, especially histone acetylation, can lead to abnormal expression of IL-10 mRNA[12]. An ncRNA is a functional RNA molecule transcribed from DNA, though not translated into a protein. ncRNAs regulate gene expression at the transcriptional and post-transcriptional levels. The three major classes of short ncRNAs are known as micro (mi)RNAs, short interfering (si)RNAs, and piwi-interacting (pi)RNAs. Plasma levels of miR-133a are higher in critically ill patients with sepsis than in patients with non-infectious inflammation, and predict intensive care unit (ICU) and long-term mortality[13]. Consequently, epigenetic biomarkers could help detect patients with clinical deterioration and unfavorable evolution[11-14].

Individualized treatment based on the genetic characteristics of the host has not yet been implemented in clinical practice, even though it is undoubtedly one of the most promising research fields for the future management of patients with sepsis and septic shock.

Transcriptomics: The transcriptome is the set of messenger RNAs and ncRNA molecules in a specific cell or tissue. Transcriptomics is the study of the transcriptome of one particular cell or tissue in a specific circumstance, based on the analysis of gene expression profiles. It aims at monitoring gene activity and regulation. Transcriptomic studies have made possible the characterization of different gene expression profiles in sepsis.

Interindividual transcriptome variation in sepsis has been evaluated in several large cohorts. Maslove et al[15] identified two subtypes in septic patients. The subtype 1 gene expression profile is characterized by a significantly increased expression of genes involved in inflammatory and Toll-like receptor (TLR)-mediated signaling pathways. This profile is associated with a higher prevalence of sepsis. Davenport et al[16] analyzed peripheral blood leucocyte global gene expression of 265 critically ill patients with community-acquired pneumonia and organ dysfunction. That transcriptomic study showed two distinct sepsis response signatures: SRS1 and SRS2. SRS1, present in 41% of patients, identified patients with an immunosuppression phenotype that included features of endotoxin tolerance, T cell exhaustion, and down-regulation of human leucocyte antigen class II. SRS1 was associated with higher 14-, 28- and 60-d mortality than SRS2. Sweeney et al[17] performed an unsupervised clustering analysis on pooled transcriptomic profiles from 14 datasets of sepsis patients (n = 700). The authors described three transcriptomic subtypes based on their functional analysis: the inflammopathic, adaptive, and coagulopathic subtypes. The adaptive subtype was associated with a lower clinical severity and lower mortality rate than the other subtypes. The coagulopathic subtype was associated with higher mortality and occurrence of clinical coagulopathy than either the adaptative or inflammopathic subtypes. Septic shock was more frequent in the inflammopathic subtype. Wong et al[18,19] conducted a genome-wide expression profiling using whole blood-derived RNA from 98 children with septic shock, and identified three subclasses of patients, which they designated as A, B, and C. Patients in subclass A were characterized by repression of genes corresponding to adaptive immunity and glucocorticoid receptor signaling. The subclass A patients had higher illness severity and mortality rate than the patients in subclasses B and C.

In the future, transcriptomic studies should help us in the early identification of patients with evolutionary patterns associated with greater severity and mortality, allowing for more personalized treatment.

Metabolomics: Metabolomics is the study of the metabolome, a collection of small molecules produced by cells[20]. This technology has been increasingly used in various investigations, such as the identification of biomarkers, drug activities, or drug-induced toxicity and metabolism. Critical illnesses, such as sepsis, alter the metabolomic profile. Thus, metabolomic studies in sepsis have been aimed at discovering metabolites that discriminate between patients with sepsis and non-infectious systemic inflammatory response syndrome (SIRS), identifying prognostic factors, and recognizing changes in response to treatment[21].

Su et al[22] studied a total of 65 patients (35 with sepsis, 15 with SIRS, and 15 healthy subjects). Levels of dimethylisine, 2-phenylacetamide, glyceryl-phosphoryl-ethanolamine, and D-cysteine were associated with the severity of sepsis. In addition, four other metabolites (S-(3-methylbutanoyl)-dihydrolipoamide-E, glycerophosphocholine, and S-succinyl-glutathione) were elevated within 48 h prior to death, indicating their potential use in predicting mortality. Neugenbauer et al[23] demonstrated that high levels of putrescine, lysoPCaC18:0, and SM C16: 1 are associated with higher mortality in community-acquired pneumonia and intra-abdominal infections. In a previous study, Mickiewicz et al[24] found 20 metabolites significant for discrimination between survivors and non-survivors. The pathways highlighted in this study were related to energy metabolism and branched-chain amino acid processes.

Metabolomic studies have characterized the fundamental role of lysophospholipids, especially lysophosphatidylcholine (LPC), in sepsis prognosis[25-27]. Ferrario et al[28] studied the changes in lipid homeostasis that occur during sepsis progression. Plasma samples from 20 patients with septic shock were studied on days 1 and 7 of septic evolution. The authors identified 137 metabolites, many of which were significantly different between survivors and non-survivors. LPC and phosphatidylcholine were found at lower levels in non-survivors than in survivors on day 1 and day 7. Using regression models, the lowest levels of LPC on day 7 were identified as the strongest predictors of mortality. Drobnik et al[26] observed that the LPC concentration was markedly reduced in patients with sepsis compared to controls, and a negative correlation between these levels and mortality was found. Instead, Cho et al[25] found no association between low LPC levels and severity of the disease in septic patients. They also observed no differences in LPC levels between survivors and non-survivors.

In sum, metabolomics is a tool that allows for predicting the severity and prognosis of sepsis patients. This technology also provides a higher level of biochemical detail and knowledge than other systems biology approaches.

Proteomics: Proteomics is the part of omics that is responsible for the study of the proteome. The proteome comprises the set of all proteins expressed by the genome of a cell, tissue, or organism at a given time and under certain conditions of time and environment[29]. This technology provides an analysis of the expression, location, function, and interaction of proteomes. Compared to other immunological tests, proteomics is a novel method that has the advantage of having high throughput, sensitivity, and specificity. The development of proteomics has provided a means to study cellular processes, such as cell signaling, identifying protein modifications, and the characterization of specific biological markers[30].

For more than a decade, the study of proteomics has been sought to find new biomarkers determining sepsis diagnosis and prognosis. Su et al[31] selected 192 proteins in patients with sepsis and septic shock for investigation. Of these, vimentin (a molecule that modulates lymphocyte apoptosis and inflammatory response) increased significantly in patients with sepsis and septic shock compared to controls. The non-survivors had higher vimentin levels in serum, and its expression was increased in lymphocytes in particular. As such, this molecule could be a marker for prognosis prediction in patients with sepsis. In a previous study of 16 critically ill patients, Punyadeera et al[32] found that a combination of various proteins [e.g., IL-1α, interferon gamma-induced protein 10 (IP-10), soluble tumor necrosis factor receptor (sTNF-R)2 and soluble cell death receptor (sFAS)] could induce the progression of sepsis to septic shock. Furthermore, a combined measurement of matrix metalloproteinase (MMP)-3, IL-1α, IP-10, soluble IL-2 receptor (sIL-2R), sFas, sTNF-R1, soluble receptor for advanced glycation end products (i.e., sRAGE), granulocyte-macrophage colony-stimulating factor (GM-CSF), IL-1β, and eotaxin could differentiate survivors from non-survivors. Latour-Pérez et al[33] observed that increased levels of activator receptor 1 expressed in myeloid cells (i.e., sTREM-1) throughout the first 3 d of evolution were associated with high mortality in critically ill patients with sepsis. The high initial severity of illness explained this finding. Gibot et al[34] found that the progressive decrease in plasma concentrations of sTREM-1 indicated a favorable clinical course during the recovery phase of sepsis and discriminated between survivors and non-survivors. Decoux et al[35] analyzed the serum proteome in a group of patients with early sepsis. To cope with the large dynamic range of serum protein samples, the authors performed N-glycosylation, a chemical enrichment of glycopeptides and subsequent differences were found in the serum proteome between survivors and non-survivors. For instance, some modified proteins and glycopeptides belong to common pathways, such as the coagulation cascade and the complement system. The authors also found decreased total neutrophil gelatinase-associated lipocalin (NGAL) and vascular cell adhesion molecule 1 (VCAM-1) levels in non-survivors, two molecules believed to be part of the inflammatory response. Thus, even though VCAM and NGAL increase in sepsis, their study suggested that these increases may be part of a beneficial response necessary for survival, and pointed to the complexity of the regulatory network that is already activated in these patients at an early stage.

Proteomics has also helped to understand the role of proteolysis in sepsis by studying circulating peptides. Bauzá-Martinez et al[36] described a higher number of circulating peptides in patients with septic shock than in sepsis patients or non-hospitalized healthy subjects. The peptide count and abundance in septic shock patients were higher in non-survivors than in survivors, suggesting an association between the magnitude of proteolysis and the outcome. The predominant role of serine proteases, such as chymotrypsin and MMPs, in causing the observed proteolytic degradation was demonstrated.

Ultimately, proteomics helps increase our understanding of the pathophysiology of sepsis and identify new molecules that can predict patients’ evolution. This technology also aids in the identification of significant prognostic factors in sepsis patients. Therefore, proteomic approaches are promising for clinical applications and biomarker studies of sepsis.

Bioinformatics

A major trend today in research is improving the accuracy of the diagnosis of sepsis. The definition of sepsis was updated in 2016 and advocated using the quick Sequential Organ Failure Assessment (qSOFA), which assesses blood pressure, respiratory rate, and mental status for sepsis diagnosis[8]. A major criticism by the medical community of this score lies in its low specificity[37]. For this reason, different research teams are trying to enhance this scale through the addition of bedside parameters (e.g., biomarker data), which could improve these diagnostic criteria. Another critical aspect in clinical research is obtaining a set of baseline phenotypes and patient trajectories in the ICU through multivariate analysis techniques, such as principal component analysis, factor analysis, and probabilistic clustering. For instance, a previous study[38] defined the following four different phenotypes for sepsis through consensus k-means clustering: (1) Patients with low vasopressor titration; (2) Patients with chronic conditions and renal dysfunction; (3) Patients with high inflammation and pulmonary dysfunction; and (4) Patients with liver dysfunction and septic shock. Another study[39] defined the following phenotypes predicting ICU outcomes: (1) Patients requiring mechanical ventilation support; (2) Patients with severe organ dysfunction; (3) Patients with high severity scores; and (4) Patients with hepatic dysfunction.

Therefore, improved versions of the qSOFA scale are evaluated in the context of all available data at hospital admission through standard machine learning techniques, such as multivariate logistic regression, relevance vector machines, support vector machines, shallow neural networks or random forests, taking the diagnosis of sepsis confirmed through hemocultures as the main outcome. To predict organ dysfunction before its onset, phenotypes are now being improved by adding different clinical traits and biomarkers that become altered before organ dysfunction is detected at a systemic level. Current initiatives are intended to enhance these phenotypes by applying a generalization of the factor analysis method with Deep Autoencoders to assess the strength of associations between variables and their importance within each patient phenotype.

Deep Reinforcement Learning has also become an important research line for assessing the continuum of organ dysfunction in sepsis. For instance, Raghu et al[40] proposed a continuous state-space model for sepsis management in a twist beyond the more traditional development and use of discriminative classifiers.

Other studies have used Bayesian Networks and Random Forests[41] for assessing patient trajectories of septic and septic shock patients in the acute phase. A common trend between these initiatives is that they all pave the way to study patient trajectories in the ICU. Patient trajectory assessment includes studying the prevalence of each phenotype and their impact on other clinical outcomes, such as long-term survival (e.g., 100-d survival rate), vasopressor resistance, and days on organ support[38,39,42].

An accurate assessment of the organ dysfunction continuum is possible with the inclusion of biomarker data (e.g., complement cascade, platelet degranulation, acute inflammation response, negative regulation of endopeptidase activity, and blood coagulation), through the development of comprehensive, interpretable and mathematically rigorous models of knowledge representation through Deep Learning techniques such as Deep Reinforcement Learning and standard machine learning techniques based on graphical models[42]. These techniques will improve diagnosis, trajectory, and long-term survival prediction in sepsis and septic shock. Also, they could set the basis for the personalized treatment of organ dysfunction.

Available biomarkers at clinics

The reliability of clinical assessments in patients with sepsis is often limited, and there is a need to individualize decision-making processes based on objective data. The heterogeneity of patients with sepsis has led to the use of biomarkers for patient stratification according to prognosis and severity of illness, improving phenotyping, intensifying medical therapy in high-risk patients, guiding antimicrobial stewardship, and allocating hospital resources.

Procalcitonin (PCT) is the most widely studied biomarker and is helpful as an adjunctive clinical tool for predicting prognosis and supporting clinical decisions in sepsis[43]. In a previous study of patients with septic shock and high vasopressor requirements, patients who had PCT levels of > 2 ng/mL benefited from receiving adjuvant therapy with hydrocortisone, vitamin C, and thiamine to reduce the progression of organ dysfunction[44]. High initial levels of PCT (> 6 ng/mL) are helpful to predict progressive organ dysfunction and an increased risk of mortality[45]. Thus, this subgroup of patients may be considered for receiving personalized rescue therapies, as conventional treatment may be insufficient to improve prognosis. Interestingly, PCT non-clearance is a predictor of adverse outcomes and treatment failure[46-48]. In a large observational study, the inability to decrease PCT by more than 80% was a significant independent predictor of mortality[49]. This finding may aid in sepsis care, potential suitability of adjuvant treatments, and allocation of resources. Well-designed randomized controlled trials (RCTs) and meta-analyses have shown a mortality benefit when using PCT-guided algorithms for antimicrobial stewardship in sepsis[50-52].

Mid-region fragment of pro-adrenomedullin (MR-proADM) is a biomarker mainly produced by vascular endothelial cells. MR-pro-ADM directly reflects plasma levels of adrenomedullin, a potent vasodilator agent with metabolic and immune-modulating properties. MR-proADM levels increase in sepsis, and high plasma clearance at day 5 has been associated with better outcomes[53]. Furthermore, the role of this biomarker for the early identification of patients at higher risk of organ dysfunction has been recognized. In a recent study, the use of MR-proADM performed better in the prediction of mortality compared to lactate, PCT, C-reactive protein, and SOFA score[54]. Former studies have evaluated MR-proADM to predict ICU admission and the need for urgent treatment[55]. Thus, MR-pro-ADM is found beneficial to guide clinical decisions regarding the use of ICU and hospital resources.

The use of sepsis biomarkers is evolving as one of the most promising developments in precision medicine. Identifying additional reliable biomarkers in sepsis will significantly improve our understanding of this heterogeneous disease and help the medical community refine clinical assessments. Likewise, comprehensive clinical assessments should be the starting point for developing and studying clinically accurate biomarkers in sepsis[56,57].

Recent progress in several biomarker research areas, including the development of point-of-care testing technologies[58], will extend their application for diagnosis, risk stratification, molecular phenotyping, and monitoring therapeutic responses, leading to more personalized medicine at the bedside. Further clinical validation of current biomarkers should be sought in certain patients [e.g., renal dysfunction, receiving continuous renal replacement therapy (i.e. CRRT), trauma]. Point-of-care sepsis biomarkers have the potential to be a game-changer as their implementation becomes widely available.

ENDOTYPES AND SPECIFIC POTENTIAL TREATMENTS
Immunoglobulins

The pathogenesis of sepsis is associated with dysregulation of the innate and adaptive immune systems. The adaptive immune system’s underlying altered mechanism is the function of antibodies and immunoglobulins (Igs)[59]. Still, the SSC guidelines[4] make a weak recommendation for using Igs as a potential treatment in sepsis patients, given the low certainty of evidence derived from the main studies and a meta-analysis[60,61]. Although the previous studies have not assessed Igs’ baseline status as an inclusion criterion, it is reasonable to think that patients with hypogammaglobulinemia could benefit from Ig treatment.

The underlying mechanisms causing decreased levels of Igs in sepsis are not entirely clear. Still, impaired Ig production, vascular leakage secondary to endothelial dysfunction, an imbalance between IgG production and its utilization by the complement system, excessive catabolism, or reduced plasma cell Ig secretion may be involved. Also, patients with sepsis frequently have lymphopenia and quantitative or functional abnormalities within T cell and B cell populations[62].

Several studies have shown higher mortality in sepsis patients with hypogammaglobulinemia. Although the definition of hypogammaglobulinemia is variable, low levels of gammaglobulins can be defined as IgG below 500 mg/dL in individuals older than 5 years or 2 standard deviations below reference values for age[63-67]. Low plasma levels of IgG (hypo-IgG) is the most common deficiency, with a prevalence as high as 70%[68]. Hypo-IgG is associated with an increased risk of severe illness [higher acute physiology and chronic health evaluation II (i.e. APACHE II) score], a greater incidence of acute respiratory distress syndrome, and a longer duration of shock[69], especially on the day of diagnosis and the following 48 h[70]. Also, a synergistic role of IgG, IgM, and IgA in sepsis and septic shock has been described[66,71]. The combined presence of low levels of endogenous IgG, IgM, and IgA in plasma is associated with reduced survival in patients with sepsis or septic shock[72].

Some studies have reported that immunoglobulin formulations containing IgG did not improve mortality rates in patients with sepsis[60]. Conversely, Welte et al[73] demonstrated a clinically significant reduction of mortality risk in patients with pneumonia treated with intravenous Ig (IVIg). That study identified a population with a very high risk of mortality, namely patients with high levels of C-reactive protein and PCT, and hypo-IgM.

Polyvalent intravenous Igs represent a promising approach to modulate both the pro-and anti-inflammatory responses[74]. In adults, the use of IgM-enriched IVIg has shown favorable results[60,61,73-79]. IgM-IgA-enriched IVIg preparations are associated with a reduction in mortality[61,73,75,76]. A recent meta-analysis of 19 trials and > 1500 patients showed a significant reduction in mortality when using IgM- and IgA-enriched IVIg compared to human albumin solution or no treatment[80,81]. However, the eligibility criteria for receiving polyvalent IVIg and the best treatment strategy should be well defined[77]. The administration of a single dose of polyclonal gammaglobulin of 1 or 2 g/kg is widely accepted (level of evidence 2C)[82]. Other strategies propose IgM and IgA-enriched polyclonal IVIg dose of 250 mg/kg/d by a 10-h infusion, for 3 consecutive days[83], or an infusion of 42 mg/kg body weight of IgM-enriched polyclonal IVIg once daily for 5 consecutive days[73]. In a retrospective study, 129 adult patients benefited from receiving IgM-IgA enriched IVIg, when the administration was performed within the first 23 h from admission[78].

The routine administration of IVIg in sepsis patients is not recommended, as stated in the 2016 SSC. However, patients with hypogammaglobulinemia could benefit from this treatment. Further studies are needed to clinically validate the most appropriate dose and administration regimen of IVIg in sepsis patients with hypogammaglobulinemia.

Endotoxin hemoadsorption

Endotoxin is a lipopolysaccharide (LPS) present in the outer membrane of Gram-negative bacteria and is one of the best examples of pathogen-associated molecular patterns (i.e. PAMPs). Its presence, together with that damage-associated molecular patterns (i.e. DAMPs) released by host injured cells, results in the elevation of pro-inflammatory and anti-inflammatory cytokines[84], activating the anti-infectious innate immune response and mediating the clinical syndrome of sepsis. LPS elicits its actions through a transmembrane protein, the TLR4, a type of pattern recognizing receptor expressed on innate immune system cells, in a process in which many important molecules are involved. In this process, the LPS-binding protein (i.e. LBP) transports circulating endotoxin and facilitates its recognition by the cell through receptor CD14. CD14 directs the LPS-LBP complex to TLR4, and the accessory protein myeloid differentiation 2 (MD2) associated with TLR4 on the cell surface is involved in the LPS-TLR4 union. Recognition of the LPS-LBP complex by these receptors transduces the endotoxin signal to the cell nucleus, leading to the expression of a complex network of inflammatory mediators. The presence of endotoxin activates changes in the expression of more than 300 genes, leading to the activation of macrophages, endothelial cells, neutrophils, and the coagulation cascade. It also triggers the release of a complex cascade of host-derived inflammatory mediators[85,86].

Endotoxin activity has emerged as a valuable marker of disease severity. The lipid-A domain of endotoxin induces most of the toxicity associated with LPS, characterized by fever, diarrhea, hemodynamic instability, multiple organ failure, and, ultimately, death[87]. A previous study highlighted the clinical relevance of circulating levels of LPS, showing a significant correlation between endotoxin levels and severity of septic shock, organ dysfunction, and mortality[86]. The prevalence of endotoxemia in patients with septic shock was high, and up to 82% of patients showing intermediate or high endotoxin activity[88]. Patients with endotoxemia also presented significantly higher lactate concentration and inotropic score.

In human illness, the measurement of endotoxin is notoriously difficult. The chromogenic limulus amebocyte lysate assay was the first diagnostic test developed. It was based on endotoxin’s ability to induce coagulation of proteins in the hemolymph of the horseshoe crab, Limulus polyphemus[89]. Since other microbial products, especially from fungi, can activate the limulus reaction, the assay is not specific for endotoxin. Since 2004, the endotoxemia measurement in humans has been made through the Endotoxin Activity Assay (EAA), a chemiluminescent rapid (30-min) assay described by Romaschin in 1998[90]. That test is based on the ability of an antibody to form an antibody-antigen complex in whole blood. This antibody targets the highly conserved lipid A epitope of endotoxin. It has a very high binding affinity, leading to very high sensitivity. In addition, the antibody does not cross-react with Gram-positive or fungal components, allowing for very high specificity. The results are expressed in EAA units, where < 0.39 is considered low, 0.40-0.59 intermediate, and ≥ 0.60 high. As this assay uses patient’s neutrophils as a readout system, it is impossible to store specimens for later assaying, and measurements must be performed within 3 h of obtaining the sample. The EAA is the only assay that is approved by the United States’ Food and Drug Administration for measuring endotoxin activity in whole blood.

Endotoxin has been considered as one of the therapeutic targets for the treatment of sepsis and septic shock. The possibility of eliminating endotoxin through blood purification techniques and, specifically, by hemoadsorption has been raised. Adsorption with a fiber column immobilized with polymyxin B (PMX) (Toraymyxin®; Toray, Tokyo, Japan), is one of the best-known endotoxin elimination therapies. Another possibility is the oXiris® hemofilter (Baxter, Meyzieu, France).

Four clinical trials have evaluated the efficacy of endotoxin hemoadsorption in septic shock. In a multicenter, open-label, pilot, randomized, controlled study conducted in Europe, 36 postsurgical patients with severe sepsis or septic shock secondary to intraabdominal infection were randomized to receive PMX treatment over 2 h (n = 17) or standard therapy (n = 19)[91]. There were no statistically significant differences in endotoxin levels from baseline to 6, 8 or 24 h after treatment between the two groups. Five of the eighteen (28%) patients in the control group and five of the seventeen (29%) patients in the PMX group died during the study period. The survival analysis showed no statistical significance between the two groups. There was also no statistically significant difference in the mean duration of ICU stay nor the number of ICU-free days between the two groups. However, patients treated with PMX demonstrated substantial increases in cardiac index and oxygen delivery index, and the need for CRRT after study entry was reduced. PMX was well tolerated and showed no significant side effects. Thus, that study showed the PMX cartridge to be safe and to have the potential to improve cardiac and renal dysfunction due to sepsis or septic shock. The early use of polymyxin B hemoperfusion in abdominal septic shock (i.e. EUPHAS) trial[92] evaluated hemoperfusion with PMX in a small sample of 64 patients with intraabdominal infection-related severe sepsis and septic shock. The design was oriented to assess hemodynamic improvement. The recovery of mean arterial pressure allowed for the reduction of vasoactive drugs in the PMX group. SOFA scores improved in the PMX group. Furthermore, a significant reduction in 28-d mortality was observed in the intervention group (32%) compared to the conventional treatment group (53%). The ABDOMIX trial[93] studied 243 patients with septic shock within 12 h after emergency surgery for secondary peritonitis due to organ perforation. The PMX hemoperfusion (i.e. PMX-HP) group (n = 119) received conventional therapy plus two sessions of PMX-HP. There were no significant differences in the SOFA score nor the 28-d mortality rate between PMX-HP and control groups (27.7% vs 19.5%). The severity of the disease and mortality were moderate. Among the 220 sessions performed, a premature interruption was observed in 25 cases (11%), mainly during the first session and primarily due to circuit clotting. A total of two PMX-HP sessions were completed in only 81 of 119 patients (69.8%). Of note, plasma EAA levels were not measured in any RCTs previously discussed.

The Euphrates trial[94] is one of the RCTs with the largest sample of patients and features the highest scientific rigor. Among its main characteristics is the use of EAA as a predictive biomarker. This trial studied 450 critically ill patients with septic shock and an EAA level of 0.6 or higher. The intervention consisted of two PMX-HP treatments (90-120 min) plus standard therapy, completed within 24 h of enrollment (n = 224) or sham hemoperfusion plus standard therapy (n = 226). PMX-HP was not associated with a significant difference in 28-d mortality. However, Klein et al[95] performed a post-hoc analysis of 194 patients with EAA between 0.6-0.89. A survival benefit was observed in patients who received therapy with PMX hemofilters. Monti et al[96] published the first study describing the use of PMX-HP as rescue therapy, involving 52 patients with refractory septic shock unresponsive to conventional therapy. The SOFA score was 10 (8-14) points and serum lactate level was 5.89 ± 4.04 mmol/L. All patients were on mechanical ventilation, and 90% were treated with corticosteroids. Rapid and early reversal of circulatory dysfunction and other organ failures were obtained. The overall 30-d mortality was lower (29%) than expected by the SAPS II score (47%).

Consequently, it seems reasonable that patients with refractory septic shock and severe multiorgan dysfunction, with adequate control of the focus and EAA 0.6-0.9 could be candidates for endotoxin hemoadsorption. The TIGRIS study[97] is ongoing, recruiting patients with SOFA score > 9 and EAA levels between 0.60 and 0.89. The results of that study will provide more information on the possible benefits of endotoxin hemoadsorption in patients with septic shock, high requirement for vasopressor support, and severe multiorgan dysfunction.

Cytokine hemoadsorption

Sepsis appears when the initially appropriate host response to infection becomes amplified and subsequently dysregulated, leading to an imbalance between pro-inflammatory and anti-inflammatory responses[98]. An excess of pro-inflammatory cytokines can lead to endothelial injury and SIRS. Severe cases can progress to disseminated intravascular coagulation and multiple organ failure that eventually leads to death[99].

A tightly regulated balance in the cytokine network is crucial for eliminating invading pathogens on the one hand and restricting excessive, tissue-damaging inflammation on the other. This network comprises pro-inflammatory cytokines [tumor necrosis factor-alpha (TNF-α), IL-1, IL-6, IL-12, interferon-gamma (IFN-γ) and macrophage migration inhibitory factor (MIF)], anti-inflammatory cytokines [IL-10, transforming growth factor-beta (TGF-β), and IL-4], and soluble inhibitors of pro-inflammatory cytokines[100], such as soluble TNF receptor (TNFR), IL-1 receptor antagonist (IL-1Ra), and IL-2 receptor antagonist (IL-1R2)[101,102]. In endothelial cells, TNF-α enhances the expression of adhesion molecules and increases integrin adhesiveness in neutrophils, promoting their extravasation into tissues[103,104]. TNF-α and IL-1 are the main mediators of inflammation-induced activation of coagulation[105]. In addition, TNF-α and IL-1 amplify inflammatory cascades in an autocrine and paracrine manner by activating macrophages to secrete other pro-inflammatory cytokines, lipid mediators, and reactive oxygen and nitrogen species, leading to sepsis-induced organ dysfunction[98,106]. A key function of IL-6 is the induction of fever[107] and the mediation of the acute phase response[108,109]. The high concentration of IL-6 binds to the soluble form of the IL-6 receptor. This complex combines with the signal-transducing component glycoprotein 130 on the cells, including endothelial cells, to elicit IL-6 signal activation. Despite its pro-inflammatory properties, IL-6 also has been shown to promote anti-inflammatory responses. IL-6 inhibits the release of TNF-α and IL-1[110] and enhances the circulation levels of anti-inflammatory mediators[111-113]. IL-10 and TGF-β suppress the production of pro-inflammatory mediators in immune cells and stimulate the production of IL-1Ra and sTNFRs[114,115].

Several studies have suggested an association of IL-6 hypercytokinemia with organ dysfunction, response to treatment, and prognosis in sepsis. Kellum et al[116] found that 82% of patients with community-acquired pneumonia had a systemic elevation of cytokine levels. Furthermore, patients with higher levels of IL-6 and IL-10 had associated severe organ dysfunction[117,118] and higher mortality[116,118]. The association between high levels of IL-6 and IL-10 with organ dysfunction and mortality has been confirmed in other studies[117-120]. Patients who survive sepsis show a rapid decrease in IL-6 Levels, in contrast to the non-decreasing values or a slowly progressive decrease in non-survivors[119, 120]. Thus, the reduction of IL-6 Levels is associated with a better prognosis[121], and IL-10 overproduction is the main predictor of severity and mortality[122,123].

Given the central role of increased systemic inflammation in the pathophysiology of sepsis-induced organ dysfunction, the development of therapies aimed at dampening the cytokine storm could help improve immune homeostasis. Extracorporeal blood purification therapies have been proposed as a strategy to improve the outcome of septic patients, attenuating the systemic expression of pro-inflammatory and anti-inflammatory mediators and restoring immune homeostasis[116]. These include different cytokine hemoadsorption techniques. Currently, we have several devices for assessing cytokine adsorption; these include Cytosorb® (CytoSorbents Corporation, Monmouth Junction, NJ, United States), oXyris (Baxter, Meyzieu, France), Alteco LPS Adsorber (Alteco Medical AB, Lund, Sweden), HA 330 and 380 (Jafron Biomedical Co., Zhuhai, GuangDong, China).

CytoSorb® is the most widely used cartridge, and our experience is greatest with it. It has been evaluated for various clinical conditions, such as SIRS after cardiopulmonary bypass, liver failure, and rhabdomyolysis-associated myoglobinemia[118-120]. In it, cytokines are adsorbed by polymer beads within a perfused cartridge, through extracorporeal circulation[117]. Cytosorb® can attenuate both the pro-inflammatory and anti-inflammatory responses, achieving a recovery of balance much earlier.

Several observational studies have suggested the clinical benefits of using Cytosorb® in septic shock to reduce vasopressor support and even achieve a mortality reduction. Friesecke et al[124] studied 20 consecutive patients with refractory septic shock after 6 h of standard treatment and hypercytokinemia. Refractory septic shock was defined as a progressive shock despite full-standard therapy and lactate ≥ 2.9 mmol/L (or increased compared to baseline), and high noradrenaline requirements (> 0.3 mcg/ kg/min). The mean IL-6 Levels were 25.523 ng/mL (range: 1052-491260 ng/mL). In that study, Cytosorb® application was found to be associated with a significant decrease in noradrenaline requirements and an increase in lactate clearance, which resulted in shock resolution in 13 patients. In another case series of 45 patients with septic shock treated with hemoadsorption, Paul et al[125] described a significant vasopressor dose reduction (i.e., norepinephrine by 51.4%, epinephrine by 69.4%, and vasopressin by 13.9%). Besides, a reduction in IL-6 Levels (by 52.3%) and lactate levels (by 39.4%) was observed in the survivors. A survival rate of 75% was reported in patients who received treatment within 24 h of admission to the ICU. Patients who received treatment within 24-48 h after admission to the ICU had a survival rate of 68%. In a retrospective study conducted by Brouwer et al[126], Cytosorb® was associated with decreased 28-d all-cause mortality in patients with septic shock.

The scientific evidence on the clinical benefits of cytokine elimination derived from RCTs is scarce. Hawchar et al[127] performed a proof of concept, prospective, randomized pilot trial on the application of Cytosorb® in 20 patients with early-onset septic shock. A significant reduction in the need for vasopressor support was observed. In the control group, this change was not achieved with therapy. Rugg et al[128] compared patients with septic shock who received CytoSorb® in addition to CRRT (n = 42) vs matched controls (n = 42). Median catecholamine requirements approximately halved within 24 h after the initiation of Cytosorb®. In-hospital mortality was significantly lower in the CytoSorb® group (35.7% vs 61.9%; P = 0.015). Derived from our current knowledge, we can attribute the benefits of cytokine hemoadsorption only to the elimination of cytokines in the subgroup of patients with very high hypercytokinemia and associated refractory septic shock. Further studies are needed to define the influence of hemadsorption in the elimination of other substances.

Cytokine hemoadsorption may have a role as rescue therapy in a particular subgroup of patients with refractory septic shock, hyperlactatemia, multiorgan failure, and very high hypercytokinemia. As such, appropriate and well-designed RCTs should be performed in patients with this clinical profile, to validate its benefits.

Immunoparalysis

More than 20 years ago, it was hypothesized that the early hyperinflammatory phase in sepsis was followed by a compensatory anti-inflammatory response to limit tissue damage[129]. In recent years, the therapeutic advances incorporated in sepsis treatment have facilitated a reduction in sepsis mortality, especially in early mortality derived from septic shock and severe multiorgan dysfunction. Some of the patients surviving the first few days evolve to a situation of chronic multiorgan dysfunction, dependent on mechanical ventilation and vasopressor therapy. This stage, known as sepsis-associated immunoparalysis, resembles the normal aging process of the immune system (immunosenescence), characterized by a general dysregulation of innate and adaptive immune responses. Monocytes and macrophages play a critical role in critically ill patients with severe infections. These cells are the front-line of the innate cellular response that initiates and promotes the adaptive immune response.

The human leukocyte antigen (HLA)-DR isotype is a major histocompatibility complex class II cell surface receptor encoded by the HLA complex and constitutively expressed on antigen-presenting cells (e.g., monocytes/macrophages, dendritic cells, and B lymphocytes). It is also inducible on T lymphocytes[130]. Decreased HLA-DR expression has been demonstrated in septic patients, at both the protein- and RNA- levels. There is also a relationship between circulating HLA-DR mRNA and HLA-DR expression in vivo[131]. Various studies in vitro have shown that constitutive and IFN-γ inducible HLA-DR expression is predominantly regulated at the transcriptional level. The observed loss of HLA-DR expression in monocytes of septic patients implies a transcriptional regulation via a decrease of its transactivator, specifically the class II transactivator (i.e., CIITA)[130].

Although no association has been found between the kinetics of monocytic (m)HLA-DR expression and primary infection sites or causative pathogens, it has been associated with severity. Patients with high SOFA scores have an associated low expression of mHLA-DR. The prognosis of patients with low mHLA-DR expression is poor compared to patients with a rapid increase in mHLA-DR expression, primarily because of the higher incidence of secondary infections and mortality rate[132]. The most reliable marker for monitoring the immune alterations in critically ill patients is the decreased mHLA-DR expression, measured by flow cytometry[133].

Immunoparalysis can be identified by studying the expression of HLA-DR in monocytes. Multiple studies have linked the low expression of mHLA-DR with the presence of more significant adverse effects and higher short and long-term mortality rates (at 7 d and 28 d) in sepsis and septic shock[134,135]. Measures of mHLA-DR levels can not only be used as a marker of monocyte functionality and severity of the disease but also to guide innovative clinical therapies based on restoring the immune system[135,136].

In patients with immunoparalysis, several immuno-adjuvant agents are under investigation. GM-CSF, IFN-g, anti-programmed death-ligand 1 (i.e., anti PDL-1), or IL-7 could have a role in treating sepsis-associated immunoparalysis. For instance, decreased mHLA-DR has been used to stratify patients for GM-CSF administration in a clinical trial, including a small sample of sepsis patients. This biomarker-guided GM-CSF therapy was found to be safe and effective in restoring monocyte immunocompetence, shortening mechanical ventilation duration, and reducing ICU/hospital stay[135]. Another clinical trial tested the hypothesis that GM-CSF improves neutrophil phagocytosis in critically ill patients. They previously measured the neutrophil phagocytic capacity and included the subgroup of patients in whom phagocytosis was known to be impaired (to < 50%). The study showed that GM-CSF did not improve mean neutrophil phagocytosis but was safe and appeared to increase the proportion of patients with adequate phagocytosis[137]. Novel therapies targeting the restoration of monocyte immunocompetence are promising for improving outcomes in later stages of sepsis.

CONCLUSION

The heterogeneity of sepsis is a complex and engaging feature of the disease that elicits novel strategies for improved patient classification. Thus, precision medicine creates an individualized approach on a case-by-case basis by identifying subgroups of sepsis patients with a high risk of adverse outcomes who may benefit from specific treatments or rescue therapies according to their particular characteristics (e.g., genotypes or phenotypes). Of note, we urge the implementation of predictive-enrichment strategies for the design and development of future clinical trials to improve the certainty of scientific assessments.

Although some clinical tools are still being evaluated in the early stages of research, such as the omics technologies, precision medicine is becoming a reality that improves our clinical approaches when currently available tools are implemented in patients with sepsis, septic shock, and organic dysfunction. Further scientific contributions in this field will be essential to identify specific endotypes responding to targeted therapies and translate individualized treatments to the bedside.

Footnotes

Provenance and peer review: Invited article; Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Critical care medicine

Country/Territory of origin: Spain

Peer-review report’s scientific quality classification

Grade A (Excellent): A

Grade B (Very good): 0

Grade C (Good): 0

Grade D (Fair): 0

Grade E (Poor): 0

P-Reviewer: Deshwal H S-Editor: Wu YXJ L-Editor: A P-Editor: Wu YXJ

References
1.  Dellinger RP, Carlet JM, Masur H, Gerlach H, Calandra T, Cohen J, Gea-Banacloche J, Keh D, Marshall JC, Parker MM, Ramsay G, Zimmerman JL, Vincent JL, Levy MM; Surviving Sepsis Campaign Management Guidelines Committee. Surviving Sepsis Campaign guidelines for management of severe sepsis and septic shock. Crit Care Med. 2004;32:858-873.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2171]  [Cited by in F6Publishing: 2024]  [Article Influence: 101.2]  [Reference Citation Analysis (0)]
2.  Dellinger RP, Levy MM, Carlet JM, Bion J, Parker MM, Jaeschke R, Reinhart K, Angus DC, Brun-Buisson C, Beale R, Calandra T, Dhainaut JF, Gerlach H, Harvey M, Marini JJ, Marshall J, Ranieri M, Ramsay G, Sevransky J, Thompson BT, Townsend S, Vender JS, Zimmerman JL, Vincent JL; International Surviving Sepsis Campaign Guidelines Committee;  American Association of Critical-Care Nurses;  American College of Chest Physicians;  American College of Emergency Physicians;  Canadian Critical Care Society;  European Society of Clinical Microbiology and Infectious Diseases;  European Society of Intensive Care Medicine;  European Respiratory Society;  International Sepsis Forum;  Japanese Association for Acute Medicine;  Japanese Society of Intensive Care Medicine;  Society of Critical Care Medicine;  Society of Hospital Medicine;  Surgical Infection Society;  World Federation of Societies of Intensive and Critical Care Medicine. Surviving Sepsis Campaign: international guidelines for management of severe sepsis and septic shock: 2008. Crit Care Med. 2008;36:296-327.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3281]  [Cited by in F6Publishing: 3056]  [Article Influence: 191.0]  [Reference Citation Analysis (0)]
3.  Dellinger RP, Levy MM, Rhodes A, Annane D, Gerlach H, Opal SM, Sevransky JE, Sprung CL, Douglas IS, Jaeschke R, Osborn TM, Nunnally ME, Townsend SR, Reinhart K, Kleinpell RM, Angus DC, Deutschman CS, Machado FR, Rubenfeld GD, Webb S, Beale RJ, Vincent JL, Moreno R; Surviving Sepsis Campaign Guidelines Committee including The Pediatric Subgroup. Surviving Sepsis Campaign: international guidelines for management of severe sepsis and septic shock, 2012. Intensive Care Med. 2013;39:165-228.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3146]  [Cited by in F6Publishing: 3102]  [Article Influence: 282.0]  [Reference Citation Analysis (0)]
4.  Evans L, Rhodes A, Alhazzani W, Antonelli M, Coopersmith CM, French C, Machado FR, Mcintyre L, Ostermann M, Prescott HC, Schorr C, Simpson S, Wiersinga WJ, Alshamsi F, Angus DC, Arabi Y, Azevedo L, Beale R, Beilman G, Belley-Cote E, Burry L, Cecconi M, Centofanti J, Coz Yataco A, De Waele J, Dellinger RP, Doi K, Du B, Estenssoro E, Ferrer R, Gomersall C, Hodgson C, Møller MH, Iwashyna T, Jacob S, Kleinpell R, Klompas M, Koh Y, Kumar A, Kwizera A, Lobo S, Masur H, McGloughlin S, Mehta S, Mehta Y, Mer M, Nunnally M, Oczkowski S, Osborn T, Papathanassoglou E, Perner A, Puskarich M, Roberts J, Schweickert W, Seckel M, Sevransky J, Sprung CL, Welte T, Zimmerman J, Levy M. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Intensive Care Med. 2021;47:1181-1247.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 295]  [Cited by in F6Publishing: 1653]  [Article Influence: 551.0]  [Reference Citation Analysis (0)]
5.  Levy MM, Evans LE, Rhodes A. The Surviving Sepsis Campaign Bundle: 2018 update. Intensive Care Med. 2018;44:925-928.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 512]  [Cited by in F6Publishing: 625]  [Article Influence: 104.2]  [Reference Citation Analysis (0)]
6.  Levy MM, Rhodes A, Phillips GS, Townsend SR, Schorr CA, Beale R, Osborn T, Lemeshow S, Chiche JD, Artigas A, Dellinger RP. Surviving Sepsis Campaign: association between performance metrics and outcomes in a 7.5-year study. Crit Care Med. 2015;43:3-12.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 337]  [Cited by in F6Publishing: 365]  [Article Influence: 40.6]  [Reference Citation Analysis (0)]
7.  Yébenes JC, Ruiz-Rodriguez JC, Ferrer R, Clèries M, Bosch A, Lorencio C, Rodriguez A, Nuvials X, Martin-Loeches I, Artigas A; SOCMIC (Catalonian Critical Care Society) Sepsis Working Group. Epidemiology of sepsis in Catalonia: analysis of incidence and outcomes in a European setting. Ann Intensive Care. 2017;7:19.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 43]  [Cited by in F6Publishing: 50]  [Article Influence: 7.1]  [Reference Citation Analysis (0)]
8.  Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, Bellomo R, Bernard GR, Chiche JD, Coopersmith CM, Hotchkiss RS, Levy MM, Marshall JC, Martin GS, Opal SM, Rubenfeld GD, van der Poll T, Vincent JL, Angus DC. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315:801-810.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 15803]  [Cited by in F6Publishing: 15276]  [Article Influence: 1909.5]  [Reference Citation Analysis (2)]
9.  Leligdowicz A, Matthay MA. Heterogeneity in sepsis: new biological evidence with clinical applications. Crit Care. 2019;23:80.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 64]  [Cited by in F6Publishing: 107]  [Article Influence: 21.4]  [Reference Citation Analysis (0)]
10.  Nakada TA, Takahashi W, Nakada E, Shimada T, Russell JA, Walley KR. Genetic Polymorphisms in Sepsis and Cardiovascular Disease: Do Similar Risk Genes Suggest Similar Drug Targets? Chest. 2019;155:1260-1271.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 14]  [Cited by in F6Publishing: 7]  [Article Influence: 1.4]  [Reference Citation Analysis (0)]
11.  Lorente-Sorolla C, Garcia-Gomez A, Català-Moll F, Toledano V, Ciudad L, Avendaño-Ortiz J, Maroun-Eid C, Martín-Quirós A, Martínez-Gallo M, Ruiz-Sanmartín A, Del Campo ÁG, Ferrer-Roca R, Ruiz-Rodriguez JC, Álvarez-Errico D, López-Collazo E, Ballestar E. Inflammatory cytokines and organ dysfunction associate with the aberrant DNA methylome of monocytes in sepsis. Genome Med. 2019;11:66.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 39]  [Cited by in F6Publishing: 57]  [Article Influence: 11.4]  [Reference Citation Analysis (0)]
12.  Zheng Z, Huang G, Gao T, Huang T, Zou M, Zou Y, Duan S. Epigenetic Changes Associated With Interleukin-10. Front Immunol. 2020;11:1105.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 11]  [Cited by in F6Publishing: 19]  [Article Influence: 4.8]  [Reference Citation Analysis (0)]
13.  Tacke F, Roderburg C, Benz F, Cardenas DV, Luedde M, Hippe HJ, Frey N, Vucur M, Gautheron J, Koch A, Trautwein C, Luedde T. Levels of circulating miR-133a are elevated in sepsis and predict mortality in critically ill patients. Crit Care Med. 2014;42:1096-1104.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 90]  [Cited by in F6Publishing: 94]  [Article Influence: 9.4]  [Reference Citation Analysis (0)]
14.  Binnie A, Walsh CJ, Hu P, Dwivedi DJ, Fox-Robichaud A, Liaw PC, Tsang JLY, Batt J, Carrasqueiro G, Gupta S, Marshall JC, Castelo-Branco P, Dos Santos CC; Epigenetic Profiling in Severe Sepsis (EPSIS) Study of the Canadian Critical Care Translational Biology Group (CCCTBG). Epigenetic Profiling in Severe Sepsis: A Pilot Study of DNA Methylation Profiles in Critical Illness. Crit Care Med. 2020;48:142-150.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 34]  [Cited by in F6Publishing: 31]  [Article Influence: 7.8]  [Reference Citation Analysis (0)]
15.  Maslove DM, Tang BM, McLean AS. Identification of sepsis subtypes in critically ill adults using gene expression profiling. Crit Care. 2012;16:R183.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 38]  [Cited by in F6Publishing: 42]  [Article Influence: 3.5]  [Reference Citation Analysis (0)]
16.  Davenport EE, Burnham KL, Radhakrishnan J, Humburg P, Hutton P, Mills TC, Rautanen A, Gordon AC, Garrard C, Hill AV, Hinds CJ, Knight JC. Genomic landscape of the individual host response and outcomes in sepsis: a prospective cohort study. Lancet Respir Med. 2016;4:259-271.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 351]  [Cited by in F6Publishing: 477]  [Article Influence: 59.6]  [Reference Citation Analysis (0)]
17.  Sweeney TE, Azad TD, Donato M, Haynes WA, Perumal TM, Henao R, Bermejo-Martin JF, Almansa R, Tamayo E, Howrylak JA, Choi A, Parnell GP, Tang B, Nichols M, Woods CW, Ginsburg GS, Kingsmore SF, Omberg L, Mangravite LM, Wong HR, Tsalik EL, Langley RJ, Khatri P. Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters. Crit Care Med. 2018;46:915-925.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 140]  [Cited by in F6Publishing: 193]  [Article Influence: 38.6]  [Reference Citation Analysis (0)]
18.  Wong HR, Cvijanovich N, Lin R, Allen GL, Thomas NJ, Willson DF, Freishtat RJ, Anas N, Meyer K, Checchia PA, Monaco M, Odom K, Shanley TP. Identification of pediatric septic shock subclasses based on genome-wide expression profiling. BMC Med. 2009;7:34.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 167]  [Cited by in F6Publishing: 196]  [Article Influence: 13.1]  [Reference Citation Analysis (0)]
19.  Wong HR, Cvijanovich NZ, Allen GL, Thomas NJ, Freishtat RJ, Anas N, Meyer K, Checchia PA, Lin R, Shanley TP, Bigham MT, Wheeler DS, Doughty LA, Tegtmeyer K, Poynter SE, Kaplan JM, Chima RS, Stalets E, Basu RK, Varisco BM, Barr FE. Validation of a gene expression-based subclassification strategy for pediatric septic shock. Crit Care Med. 2011;39:2511-2517.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 96]  [Cited by in F6Publishing: 97]  [Article Influence: 7.5]  [Reference Citation Analysis (0)]
20.  Ludwig KR, Hummon AB. Mass spectrometry for the discovery of biomarkers of sepsis. Mol Biosyst. 2017;13:648-664.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 65]  [Cited by in F6Publishing: 62]  [Article Influence: 8.9]  [Reference Citation Analysis (0)]
21.  Vincent JL, Brealey D, Libert N, Abidi NE, O'Dwyer M, Zacharowski K, Mikaszewska-Sokolewicz M, Schrenzel J, Simon F, Wilks M, Picard-Maureau M, Chalfin DB, Ecker DJ, Sampath R, Singer M; Rapid Diagnosis of Infections in the Critically Ill Team. Rapid Diagnosis of Infection in the Critically Ill, a Multicenter Study of Molecular Detection in Bloodstream Infections, Pneumonia, and Sterile Site Infections. Crit Care Med. 2015;43:2283-2291.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 129]  [Cited by in F6Publishing: 133]  [Article Influence: 16.6]  [Reference Citation Analysis (0)]
22.  Su L, Huang Y, Zhu Y, Xia L, Wang R, Xiao K, Wang H, Yan P, Wen B, Cao L, Meng N, Luan H, Liu C, Li X, Xie L. Discrimination of sepsis stage metabolic profiles with an LC/MS-MS-based metabolomics approach. BMJ Open Respir Res. 2014;1:e000056.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 38]  [Cited by in F6Publishing: 41]  [Article Influence: 4.1]  [Reference Citation Analysis (0)]
23.  Neugebauer S, Giamarellos-Bourboulis EJ, Pelekanou A, Marioli A, Baziaka F, Tsangaris I, Bauer M, Kiehntopf M. Metabolite Profiles in Sepsis: Developing Prognostic Tools Based on the Type of Infection. Crit Care Med. 2016;44:1649-1662.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 67]  [Cited by in F6Publishing: 74]  [Article Influence: 10.6]  [Reference Citation Analysis (0)]
24.  Mickiewicz B, Duggan GE, Winston BW, Doig C, Kubes P, Vogel HJ; Alberta Sepsis Network. Metabolic profiling of serum samples by 1H nuclear magnetic resonance spectroscopy as a potential diagnostic approach for septic shock. Crit Care Med. 2014;42:1140-1149.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 73]  [Cited by in F6Publishing: 74]  [Article Influence: 7.4]  [Reference Citation Analysis (0)]
25.  Cho WH, Park T, Park YY, Huh JW, Lim CM, Koh Y, Song DK, Hong SB. Clinical significance of enzymatic lysophosphatidylcholine (LPC) assay data in patients with sepsis. Eur J Clin Microbiol Infect Dis. 2012;31:1805-1810.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 27]  [Cited by in F6Publishing: 27]  [Article Influence: 2.1]  [Reference Citation Analysis (0)]
26.  Drobnik W, Liebisch G, Audebert FX, Frohlich D, Gluck T, Vogel P, Rothe G, Schmitz G. Plasma ceramide and lysophosphatidylcholine inversely correlate with mortality in sepsis patients. J Lipid Res. 2003;44:754-761.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 235]  [Cited by in F6Publishing: 243]  [Article Influence: 11.6]  [Reference Citation Analysis (0)]
27.  Lee SH, Park MS, Park BH, Jung WJ, Lee IS, Kim SY, Kim EY, Jung JY, Kang YA, Kim YS, Kim SK, Chang J, Chung KS. Prognostic Implications of Serum Lipid Metabolism over Time during Sepsis. Biomed Res Int. 2015;2015:789298.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 33]  [Cited by in F6Publishing: 54]  [Article Influence: 6.0]  [Reference Citation Analysis (0)]
28.  Ferrario M, Cambiaghi A, Brunelli L, Giordano S, Caironi P, Guatteri L, Raimondi F, Gattinoni L, Latini R, Masson S, Ristagno G, Pastorelli R. Mortality prediction in patients with severe septic shock: a pilot study using a target metabolomics approach. Sci Rep. 2016;6:20391.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 93]  [Cited by in F6Publishing: 108]  [Article Influence: 13.5]  [Reference Citation Analysis (0)]
29.  Pitarch A, Nombela C, Gil C. [Proteomics, a new challenge for clinical microbiology]. Enferm Infecc Microbiol Clin. 2010;28:489-491.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3]  [Cited by in F6Publishing: 3]  [Article Influence: 0.2]  [Reference Citation Analysis (0)]
30.  Siqueira-Batista R, Mendonça EG, Gomes AP, Vitorino RR, Miyadahira R, Alvarez-Perez MC, Oliveira MG. Proteomic updates on sepsis. Rev Assoc Med Bras (1992). 2012;58:376-382.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1]  [Cited by in F6Publishing: 1]  [Article Influence: 0.1]  [Reference Citation Analysis (0)]
31.  Su L, Pan P, Yan P, Long Y, Zhou X, Wang X, Zhou R, Wen B, Xie L, Liu D. Role of vimentin in modulating immune cell apoptosis and inflammatory responses in sepsis. Sci Rep. 2019;9:5747.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 25]  [Cited by in F6Publishing: 31]  [Article Influence: 6.2]  [Reference Citation Analysis (0)]
32.  Punyadeera C, Schneider EM, Schaffer D, Hsu HY, Joos TO, Kriebel F, Weiss M, Verhaegh WF. A biomarker panel to discriminate between systemic inflammatory response syndrome and sepsis and sepsis severity. J Emerg Trauma Shock. 2010;3:26-35.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 48]  [Cited by in F6Publishing: 50]  [Article Influence: 3.8]  [Reference Citation Analysis (0)]
33.  Latour-Pérez J, Alcalá-López A, García-García MA, Sánchez-Hernández JF, Abad-Terrado C, Viedma-Contreras JA, Masiá-Canuto M, Broch-Porcar MJ, Arizo-León D, González-Tejera M, Bonilla-Rovira F, Gutiérrez F. [Prognostic value of the sTREM-1 plasma values in patients with sepsis: a cohort study]. Med Intensiva. 2010;34:231-236.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 5]  [Cited by in F6Publishing: 5]  [Article Influence: 0.4]  [Reference Citation Analysis (0)]
34.  Gibot S, Cravoisy A, Kolopp-Sarda MN, Béné MC, Faure G, Bollaert PE, Levy B. Time-course of sTREM (soluble triggering receptor expressed on myeloid cells)-1, procalcitonin, and C-reactive protein plasma concentrations during sepsis. Crit Care Med. 2005;33:792-796.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 163]  [Cited by in F6Publishing: 169]  [Article Influence: 8.9]  [Reference Citation Analysis (0)]
35.  DeCoux A, Tian Y, DeLeon-Pennell KY, Nguyen NT, de Castro Brás LE, Flynn ER, Cannon PL, Griswold ME, Jin YF, Puskarich MA, Jones AE, Lindsey ML. Plasma Glycoproteomics Reveals Sepsis Outcomes Linked to Distinct Proteins in Common Pathways. Crit Care Med. 2015;43:2049-2058.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 36]  [Cited by in F6Publishing: 36]  [Article Influence: 4.0]  [Reference Citation Analysis (0)]
36.  Bauzá-Martinez J, Aletti F, Pinto BB, Ribas V, Odena MA, Díaz R, Romay E, Ferrer R, Kistler EB, Tedeschi G, Schmid-Schönbein GW, Herpain A, Bendjelid K, de Oliveira E. Proteolysis in septic shock patients: plasma peptidomic patterns are associated with mortality. Br J Anaesth. 2018;121:1065-1074.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 21]  [Cited by in F6Publishing: 30]  [Article Influence: 5.0]  [Reference Citation Analysis (0)]
37.  Seymour CW, Liu VX, Iwashyna TJ, Brunkhorst FM, Rea TD, Scherag A, Rubenfeld G, Kahn JM, Shankar-Hari M, Singer M, Deutschman CS, Escobar GJ, Angus DC. Assessment of Clinical Criteria for Sepsis: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315:762-774.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2092]  [Cited by in F6Publishing: 2356]  [Article Influence: 294.5]  [Reference Citation Analysis (0)]
38.  Seymour CW, Kennedy JN, Wang S, Chang CH, Elliott CF, Xu Z, Berry S, Clermont G, Cooper G, Gomez H, Huang DT, Kellum JA, Mi Q, Opal SM, Talisa V, van der Poll T, Visweswaran S, Vodovotz Y, Weiss JC, Yealy DM, Yende S, Angus DC. Derivation, Validation, and Potential Treatment Implications of Novel Clinical Phenotypes for Sepsis. JAMA. 2019;321:2003-2017.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 517]  [Cited by in F6Publishing: 706]  [Article Influence: 141.2]  [Reference Citation Analysis (0)]
39.  Ribas V, Vellido A, Ruiz-Rodríguez JC, Rello J. Severe sepsis mortality prediction with logistic regression over latent factors. Expert Syst Appl. 2012;1937.  [PubMed]  [DOI]  [Cited in This Article: ]
40.  Raghu A, Celi L, Szolovits P, Ghassemi M.   Continuous state-space models for optimal sepsis treatment-a deep reinforcement learning approach. arXiv preprint arXiv:170508422. Cited 23 May 2017.  [PubMed]  [DOI]  [Cited in This Article: ]
41.  Aushev A, Ripoll VR, Vellido A, Aletti F, Pinto BB, Herpain A, Post EH, Medina ER, Ferrer R, Baselli G, Bendjelid K. Feature selection for the accurate prediction of septic and cardiogenic shock ICU mortality in the acute phase. PLoS One. 2018;13:e0199089.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 17]  [Cited by in F6Publishing: 17]  [Article Influence: 2.8]  [Reference Citation Analysis (0)]
42.  Ribas Ripoll VJ, Vellido A, Romero E, Ruiz-Rodríguez JC. Sepsis mortality prediction with the Quotient Basis Kernel. Artif Intell Med. 2014;61:45-52.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 25]  [Cited by in F6Publishing: 21]  [Article Influence: 2.1]  [Reference Citation Analysis (0)]
43.  Plata-Menchaca EP, Ferrer R. Procalcitonin Is Useful for Antibiotic Deescalation in Sepsis. Crit Care Med. 2021;49:693-696.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3]  [Cited by in F6Publishing: 3]  [Article Influence: 1.0]  [Reference Citation Analysis (0)]
44.  Marik PE, Khangoora V, Rivera R, Hooper MH, Catravas J. Hydrocortisone, Vitamin C, and Thiamine for the Treatment of Severe Sepsis and Septic Shock: A Retrospective Before-After Study. Chest. 2017;151:1229-1238.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 671]  [Cited by in F6Publishing: 604]  [Article Influence: 86.3]  [Reference Citation Analysis (0)]
45.  Clec'h C, Ferriere F, Karoubi P, Fosse JP, Cupa M, Hoang P, Cohen Y. Diagnostic and prognostic value of procalcitonin in patients with septic shock. Crit Care Med. 2004;32:1166-1169.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 148]  [Cited by in F6Publishing: 165]  [Article Influence: 8.3]  [Reference Citation Analysis (0)]
46.  Patnaik R, Azim A, Mishra P. Should serial monitoring of procalcitonin be done routinely in critically ill patients of ICU: A systematic review and metaanalysis. J Anaesthesiol Clin Pharmacol. 2020;36:458-464.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 4]  [Cited by in F6Publishing: 5]  [Article Influence: 1.7]  [Reference Citation Analysis (0)]
47.  Ruiz-Rodríguez JC, Caballero J, Ruiz-Sanmartin A, Ribas VJ, Pérez M, Bóveda JL, Rello J. Usefulness of procalcitonin clearance as a prognostic biomarker in septic shock. A prospective pilot study. Med Intensiva. 2012;36:475-480.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 32]  [Cited by in F6Publishing: 36]  [Article Influence: 3.0]  [Reference Citation Analysis (0)]
48.  Ruiz-Rodríguez J, Rello J. Predicting treatment failure in severe sepsis and septic shock: looking for the Holy Grail. Crit Care. 2013;17:180.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1]  [Cited by in F6Publishing: 2]  [Article Influence: 0.2]  [Reference Citation Analysis (0)]
49.  Schuetz P, Birkhahn R, Sherwin R, Jones AE, Singer A, Kline JA, Runyon MS, Self WH, Courtney DM, Nowak RM, Gaieski DF, Ebmeyer S, Johannes S, Wiemer JC, Schwabe A, Shapiro NI. Serial Procalcitonin Predicts Mortality in Severe Sepsis Patients: Results From the Multicenter Procalcitonin MOnitoring SEpsis (MOSES) Study. Crit Care Med. 2017;45:781-789.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 172]  [Cited by in F6Publishing: 172]  [Article Influence: 24.6]  [Reference Citation Analysis (0)]
50.  Lam SW, Bauer SR, Fowler R, Duggal A. Systematic Review and Meta-Analysis of Procalcitonin-Guidance Versus Usual Care for Antimicrobial Management in Critically Ill Patients: Focus on Subgroups Based on Antibiotic Initiation, Cessation, or Mixed Strategies. Crit Care Med. 2018;46:684-690.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 42]  [Cited by in F6Publishing: 44]  [Article Influence: 7.3]  [Reference Citation Analysis (0)]
51.  Wirz Y, Meier MA, Bouadma L, Luyt CE, Wolff M, Chastre J, Tubach F, Schroeder S, Nobre V, Annane D, Reinhart K, Damas P, Nijsten M, Shajiei A, deLange DW, Deliberato RO, Oliveira CF, Shehabi Y, van Oers JAH, Beishuizen A, Girbes ARJ, de Jong E, Mueller B, Schuetz P. Effect of procalcitonin-guided antibiotic treatment on clinical outcomes in intensive care unit patients with infection and sepsis patients: a patient-level meta-analysis of randomized trials. Crit Care. 2018;22:191.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 155]  [Cited by in F6Publishing: 146]  [Article Influence: 24.3]  [Reference Citation Analysis (0)]
52.  Schuetz P, Beishuizen A, Broyles M, Ferrer R, Gavazzi G, Gluck EH, González Del Castillo J, Jensen JU, Kanizsai PL, Kwa ALH, Krueger S, Luyt CE, Oppert M, Plebani M, Shlyapnikov SA, Toccafondi G, Townsend J, Welte T, Saeed K. Procalcitonin (PCT)-guided antibiotic stewardship: an international experts consensus on optimized clinical use. Clin Chem Lab Med. 2019;57:1308-1318.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 111]  [Cited by in F6Publishing: 160]  [Article Influence: 40.0]  [Reference Citation Analysis (0)]
53.  Önal U, Valenzuela-Sánchez F, Vandana KE, Rello J. Mid-Regional Pro-Adrenomedullin (MR-proADM) as a Biomarker for Sepsis and Septic Shock: Narrative Review. Healthcare (Basel). 2018;6.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 29]  [Cited by in F6Publishing: 36]  [Article Influence: 6.0]  [Reference Citation Analysis (0)]
54.  Baldirà J, Ruiz-Rodríguez JC, Wilson DC, Ruiz-Sanmartin A, Cortes A, Chiscano L, Ferrer-Costa R, Comas I, Larrosa N, Fàbrega A, González-López JJ, Ferrer R. Biomarkers and clinical scores to aid the identification of disease severity and intensive care requirement following activation of an in-hospital sepsis code. Ann Intensive Care. 2020;10:7.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 15]  [Cited by in F6Publishing: 15]  [Article Influence: 3.8]  [Reference Citation Analysis (0)]
55.  Schuetz P, Hausfater P, Amin D, Amin A, Haubitz S, Faessler L, Kutz A, Conca A, Reutlinger B, Canavaggio P, Sauvin G, Bernard M, Huber A, Mueller B; TRIAGE Study group. Biomarkers from distinct biological pathways improve early risk stratification in medical emergency patients: the multinational, prospective, observational TRIAGE study. Crit Care. 2015;19:377.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 68]  [Cited by in F6Publishing: 67]  [Article Influence: 7.4]  [Reference Citation Analysis (0)]
56.  Gibot S, Béné MC, Noel R, Massin F, Guy J, Cravoisy A, Barraud D, De Carvalho Bittencourt M, Quenot JP, Bollaert PE, Faure G, Charles PE. Combination biomarkers to diagnose sepsis in the critically ill patient. Am J Respir Crit Care Med. 2012;186:65-71.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 202]  [Cited by in F6Publishing: 214]  [Article Influence: 17.8]  [Reference Citation Analysis (0)]
57.  Angeletti S, Ciccozzi M, Fogolari M, Spoto S, Lo Presti A, Costantino S, Dicuonzo G. Procalcitonin and MR-proAdrenomedullin combined score in the diagnosis and prognosis of systemic and localized bacterial infections. J Infect. 2016;72:395-398.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 14]  [Cited by in F6Publishing: 16]  [Article Influence: 1.8]  [Reference Citation Analysis (0)]
58.  Belushkin A, Yesilkoy F, González-López JJ, Ruiz-Rodríguez JC, Ferrer R, Fàbrega A, Altug H. Rapid and Digital Detection of Inflammatory Biomarkers Enabled by a Novel Portable Nanoplasmonic Imager. Small. 2020;16:e1906108.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 53]  [Cited by in F6Publishing: 44]  [Article Influence: 11.0]  [Reference Citation Analysis (0)]
59.  Angus DC, van der Poll T. Severe sepsis and septic shock. N Engl J Med. 2013;369:840-851.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2315]  [Cited by in F6Publishing: 2427]  [Article Influence: 220.6]  [Reference Citation Analysis (0)]
60.  Werdan K, Pilz G, Bujdoso O, Fraunberger P, Neeser G, Schmieder RE, Viell B, Marget W, Seewald M, Walger P, Stuttmann R, Speichermann N, Peckelsen C, Kurowski V, Osterhues HH, Verner L, Neumann R, Müller-Werdan U; Score-Based Immunoglobulin Therapy of Sepsis (SBITS) Study Group. Score-based immunoglobulin G therapy of patients with sepsis: the SBITS study. Crit Care Med. 2007;35:2693-2701.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 97]  [Cited by in F6Publishing: 98]  [Article Influence: 5.8]  [Reference Citation Analysis (0)]
61.  Alejandria MM, Lansang MA, Dans LF, Mantaring JB 3rd. Intravenous immunoglobulin for treating sepsis, severe sepsis and septic shock. Cochrane Database Syst Rev. 2013;CD001090.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 74]  [Cited by in F6Publishing: 114]  [Article Influence: 10.4]  [Reference Citation Analysis (0)]
62.  Bermejo-Martin JF, Andaluz-Ojeda D, Almansa R, Gandía F, Gómez-Herreras JI, Gomez-Sanchez E, Heredia-Rodríguez M, Eiros JM, Kelvin DJ, Tamayo E. Defining immunological dysfunction in sepsis: A requisite tool for precision medicine. J Infect. 2016;72:525-536.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 59]  [Cited by in F6Publishing: 58]  [Article Influence: 7.3]  [Reference Citation Analysis (0)]
63.  Orange JS, Hossny EM, Weiler CR, Ballow M, Berger M, Bonilla FA, Buckley R, Chinen J, El-Gamal Y, Mazer BD, Nelson RP Jr, Patel DD, Secord E, Sorensen RU, Wasserman RL, Cunningham-Rundles C; Primary Immunodeficiency Committee of the American Academy of Allergy, Asthma and Immunology. Use of intravenous immunoglobulin in human disease: a review of evidence by members of the Primary Immunodeficiency Committee of the American Academy of Allergy, Asthma and Immunology. J Allergy Clin Immunol. 2006;117:S525-S553.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 465]  [Cited by in F6Publishing: 448]  [Article Influence: 24.9]  [Reference Citation Analysis (0)]
64.  Bonilla FA, Khan DA, Ballas ZK, Chinen J, Frank MM, Hsu JT, Keller M, Kobrynski LJ, Komarow HD, Mazer B, Nelson RP Jr, Orange JS, Routes JM, Shearer WT, Sorensen RU, Verbsky JW, Bernstein DI, Blessing-Moore J, Lang D, Nicklas RA, Oppenheimer J, Portnoy JM, Randolph CR, Schuller D, Spector SL, Tilles S, Wallace D; Joint Task Force on Practice Parameters, representing the American Academy of Allergy, Asthma & Immunology;  the American College of Allergy, Asthma & Immunology;  and the Joint Council of Allergy, Asthma & Immunology. Practice parameter for the diagnosis and management of primary immunodeficiency. J Allergy Clin Immunol. 2015;136:1186-205.e1.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 359]  [Cited by in F6Publishing: 427]  [Article Influence: 47.4]  [Reference Citation Analysis (0)]
65.  Picard C, Al-Herz W, Bousfiha A, Casanova JL, Chatila T, Conley ME, Cunningham-Rundles C, Etzioni A, Holland SM, Klein C, Nonoyama S, Ochs HD, Oksenhendler E, Puck JM, Sullivan KE, Tang ML, Franco JL, Gaspar HB. Primary Immunodeficiency Diseases: an Update on the Classification from the International Union of Immunological Societies Expert Committee for Primary Immunodeficiency 2015. J Clin Immunol. 2015;35:696-726.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 470]  [Cited by in F6Publishing: 450]  [Article Influence: 50.0]  [Reference Citation Analysis (0)]
66.  Bermejo-Martín JF, Rodriguez-Fernandez A, Herrán-Monge R, Andaluz-Ojeda D, Muriel-Bombín A, Merino P, García-García MM, Citores R, Gandía F, Almansa R, Blanco J; GRECIA Group (Grupo de Estudios y Análisis en Cuidados Intensivos). Immunoglobulins IgG1, IgM and IgA: a synergistic team influencing survival in sepsis. J Intern Med. 2014;276:404-412.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 57]  [Cited by in F6Publishing: 67]  [Article Influence: 6.7]  [Reference Citation Analysis (0)]
67.  Venet F, Gebeile R, Bancel J, Guignant C, Poitevin-Later F, Malcus C, Lepape A, Monneret G. Assessment of plasmatic immunoglobulin G, A and M levels in septic shock patients. Int Immunopharmacol. 2011;11:2086-2090.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 52]  [Cited by in F6Publishing: 53]  [Article Influence: 4.1]  [Reference Citation Analysis (0)]
68.  Shankar-Hari M, Culshaw N, Post B, Tamayo E, Andaluz-Ojeda D, Bermejo-Martín JF, Dietz S, Werdan K, Beale R, Spencer J, Singer M. Endogenous IgG hypogammaglobulinaemia in critically ill adults with sepsis: systematic review and meta-analysis. Intensive Care Med. 2015;41:1393-1401.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 47]  [Cited by in F6Publishing: 42]  [Article Influence: 4.7]  [Reference Citation Analysis (0)]
69.  Taccone FS, Stordeur P, De Backer D, Creteur J, Vincent JL. Gamma-globulin levels in patients with community-acquired septic shock. Shock. 2009;32:379-385.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 65]  [Cited by in F6Publishing: 68]  [Article Influence: 4.5]  [Reference Citation Analysis (0)]
70.  Andaluz-Ojeda D, Iglesias V, Bobillo F, Almansa R, Rico L, Gandía F, Loma AM, Nieto C, Diego R, Ramos E, Nocito M, Resino S, Eiros JM, Tamayo E, de Lejarazu RO, Bermejo-Martin JF. Early natural killer cell counts in blood predict mortality in severe sepsis. Crit Care. 2011;15:R243.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 61]  [Cited by in F6Publishing: 76]  [Article Influence: 5.8]  [Reference Citation Analysis (0)]
71.  Tian L, Zhu J, Jin J, Tong C, Zeng W, Deng S, Zou S. Prognostic value of circulating lymphocyte B and plasma immunoglobulin M on septic shock and sepsis: a systematic review and meta-analysis. Am J Transl Res. 2019;11:7223-7232.  [PubMed]  [DOI]  [Cited in This Article: ]
72.  Krautz C, Maier SL, Brunner M, Langheinrich M, Giamarellos-Bourboulis EJ, Gogos C, Armaganidis A, Kunath F, Grützmann R, Weber GF. Reduced circulating B cells and plasma IgM levels are associated with decreased survival in sepsis - A meta-analysis. J Crit Care. 2018;45:71-75.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 22]  [Cited by in F6Publishing: 29]  [Article Influence: 4.8]  [Reference Citation Analysis (0)]
73.  Welte T, Dellinger RP, Ebelt H, Ferrer M, Opal SM, Singer M, Vincent JL, Werdan K, Martin-Loeches I, Almirall J, Artigas A, Ignacio Ayestarán J, Nuding S, Ferrer R, Sirgo Rodríguez G, Shankar-Hari M, Álvarez-Lerma F, Riessen R, Sirvent JM, Kluge S, Zacharowski K, Bonastre Mora J, Lapp H, Wöbker G, Achtzehn U, Brealey D, Kempa A, Sánchez García M, Brederlau J, Kochanek M, Reschreiter HP, Wise MP, Belohradsky BH, Bobenhausen I, Dälken B, Dubovy P, Langohr P, Mayer M, Schüttrumpf J, Wartenberg-Demand A, Wippermann U, Wolf D, Torres A. Efficacy and safety of trimodulin, a novel polyclonal antibody preparation, in patients with severe community-acquired pneumonia: a randomized, placebo-controlled, double-blind, multicenter, phase II trial (CIGMA study). Intensive Care Med. 2018;44:438-448.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 71]  [Cited by in F6Publishing: 83]  [Article Influence: 13.8]  [Reference Citation Analysis (0)]
74.  Busani S, Damiani E, Cavazzuti I, Donati A, Girardis M. Intravenous immunoglobulin in septic shock: review of the mechanisms of action and meta-analysis of the clinical effectiveness. Minerva Anestesiol. 2016;82:559-572.  [PubMed]  [DOI]  [Cited in This Article: ]
75.  Kreymann KG, de Heer G, Nierhaus A, Kluge S. Use of polyclonal immunoglobulins as adjunctive therapy for sepsis or septic shock. Crit Care Med. 2007;35:2677-2685.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 122]  [Cited by in F6Publishing: 120]  [Article Influence: 7.1]  [Reference Citation Analysis (0)]
76.  Rodríguez A, Rello J, Neira J, Maskin B, Ceraso D, Vasta L, Palizas F. Effects of high-dose of intravenous immunoglobulin and antibiotics on survival for severe sepsis undergoing surgery. Shock. 2005;23:298-304.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 84]  [Cited by in F6Publishing: 83]  [Article Influence: 4.4]  [Reference Citation Analysis (0)]
77.  Nierhaus A, Berlot G, Kindgen-Milles D, Müller E, Girardis M. Best-practice IgM- and IgA-enriched immunoglobulin use in patients with sepsis. Ann Intensive Care. 2020;10:132.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 18]  [Cited by in F6Publishing: 29]  [Article Influence: 7.3]  [Reference Citation Analysis (0)]
78.  Berlot G, Vassallo MC, Busetto N, Bianchi M, Zornada F, Rosato I, Tartamella F, Prisco L, Bigotto F, Bigolin T, Ferluga M, Batticci I, Michelone E, Borelli M, Viviani M, Tomasini A. Relationship between the timing of administration of IgM and IgA enriched immunoglobulins in patients with severe sepsis and septic shock and the outcome: a retrospective analysis. J Crit Care. 2012;27:167-171.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 45]  [Cited by in F6Publishing: 46]  [Article Influence: 3.5]  [Reference Citation Analysis (0)]
79.  Pildal J, Gøtzsche PC. Polyclonal immunoglobulin for treatment of bacterial sepsis: a systematic review. Clin Infect Dis. 2004;39:38-46.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 93]  [Cited by in F6Publishing: 98]  [Article Influence: 4.9]  [Reference Citation Analysis (0)]
80.  Cui J, Wei X, Lv H, Li Y, Li P, Chen Z, Liu G. The clinical efficacy of intravenous IgM-enriched immunoglobulin (pentaglobin) in sepsis or septic shock: a meta-analysis with trial sequential analysis. Ann Intensive Care. 2019;9:27.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 39]  [Cited by in F6Publishing: 57]  [Article Influence: 11.4]  [Reference Citation Analysis (0)]
81.  Cavazzuti I, Serafini G, Busani S, Rinaldi L, Biagioni E, Buoncristiano M, Girardis M. Early therapy with IgM-enriched polyclonal immunoglobulin in patients with septic shock. Intensive Care Med. 2014;40:1888-1896.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 36]  [Cited by in F6Publishing: 34]  [Article Influence: 3.4]  [Reference Citation Analysis (0)]
82.  Olivares MM, Olmos CE, Álvarez MI, Fajardo AM, Zea-Vera AF, Ortega MC, Medina D, Pérez PM, Beltrán DG, Duque B, Álvarez CA, Lenis G, Solano JM, Gómez D, Franco JL, Díaz MC, Orrego JC, Velásquez MM, Chaparro M, Pinto JL, Izquierdo Á, Ramírez SF. [Colombian Guidelines of clinical practice for the use of immunoglobulins in the treatment of replacement and immunomodulation]. Rev Alerg Mex. 2017;64 Suppl 2:s5-s65.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2]  [Cited by in F6Publishing: 3]  [Article Influence: 0.4]  [Reference Citation Analysis (0)]
83.  Berlot G, Vassallo MC, Busetto N, Nieto Yabar M, Istrati T, Baronio S, Quarantotto G, Bixio M, Barbati G, Dattola R, Longo I, Chillemi A, Scamperle A, Iscra F, Tomasini A. Effects of the timing of administration of IgM- and IgA-enriched intravenous polyclonal immunoglobulins on the outcome of septic shock patients. Ann Intensive Care. 2018;8:122.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 19]  [Cited by in F6Publishing: 28]  [Article Influence: 4.7]  [Reference Citation Analysis (0)]
84.  Ankawi G, Neri M, Zhang J, Breglia A, Ricci Z, Ronco C. Extracorporeal techniques for the treatment of critically ill patients with sepsis beyond conventional blood purification therapy: the promises and the pitfalls. Crit Care. 2018;22:262.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 73]  [Cited by in F6Publishing: 90]  [Article Influence: 15.0]  [Reference Citation Analysis (0)]
85.  Lakshmikanth CL, Jacob SP, Chaithra VH, de Castro-Faria-Neto HC, Marathe GK. Sepsis: in search of cure. Inflamm Res. 2016;65:587-602.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 41]  [Cited by in F6Publishing: 46]  [Article Influence: 5.8]  [Reference Citation Analysis (0)]
86.  Marshall JC, Foster D, Vincent JL, Cook DJ, Cohen J, Dellinger RP, Opal S, Abraham E, Brett SJ, Smith T, Mehta S, Derzko A, Romaschin A; MEDIC study. Diagnostic and prognostic implications of endotoxemia in critical illness: results of the MEDIC study. J Infect Dis. 2004;190:527-534.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 224]  [Cited by in F6Publishing: 230]  [Article Influence: 11.5]  [Reference Citation Analysis (0)]
87.  Ronco C. Endotoxin removal: history of a mission. Blood Purif. 2014;37 Suppl 1:5-8.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 21]  [Cited by in F6Publishing: 20]  [Article Influence: 2.0]  [Reference Citation Analysis (0)]
88.  Bottiroli M, Monti G, Pinciroli R, Vecchi I, Terzi V, Ortisi G, Casella G, Fumagalli R. Prevalence and clinical significance of early high Endotoxin Activity in septic shock: An observational study. J Crit Care. 2017;41:124-129.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 14]  [Cited by in F6Publishing: 13]  [Article Influence: 1.9]  [Reference Citation Analysis (0)]
89.  Levin J, Bang FB. Clottable protein in Limulus; its localization and kinetics of its coagulation by endotoxin. Thromb Diath Haemorrh. 1968;19:186-197.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 35]  [Cited by in F6Publishing: 17]  [Article Influence: 2.8]  [Reference Citation Analysis (0)]
90.  Romaschin AD, Harris DM, Ribeiro MB, Paice J, Foster DM, Walker PM, Marshall JC. A rapid assay of endotoxin in whole blood using autologous neutrophil dependent chemiluminescence. J Immunol Methods. 1998;212:169-185.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 107]  [Cited by in F6Publishing: 101]  [Article Influence: 3.9]  [Reference Citation Analysis (0)]
91.  Vincent JL, Laterre PF, Cohen J, Burchardi H, Bruining H, Lerma FA, Wittebole X, De Backer D, Brett S, Marzo D, Nakamura H, John S. A pilot-controlled study of a polymyxin B-immobilized hemoperfusion cartridge in patients with severe sepsis secondary to intra-abdominal infection. Shock. 2005;23:400-405.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 196]  [Cited by in F6Publishing: 206]  [Article Influence: 10.8]  [Reference Citation Analysis (0)]
92.  Cruz DN, Antonelli M, Fumagalli R, Foltran F, Brienza N, Donati A, Malcangi V, Petrini F, Volta G, Bobbio Pallavicini FM, Rottoli F, Giunta F, Ronco C. Early use of polymyxin B hemoperfusion in abdominal septic shock: the EUPHAS randomized controlled trial. JAMA. 2009;301:2445-2452.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 534]  [Cited by in F6Publishing: 513]  [Article Influence: 34.2]  [Reference Citation Analysis (0)]
93.  Payen DM, Guilhot J, Launey Y, Lukaszewicz AC, Kaaki M, Veber B, Pottecher J, Joannes-Boyau O, Martin-Lefevre L, Jabaudon M, Mimoz O, Coudroy R, Ferrandière M, Kipnis E, Vela C, Chevallier S, Mallat J, Robert R; ABDOMIX Group. Early use of polymyxin B hemoperfusion in patients with septic shock due to peritonitis: a multicenter randomized control trial. Intensive Care Med. 2015;41:975-984.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 211]  [Cited by in F6Publishing: 238]  [Article Influence: 26.4]  [Reference Citation Analysis (0)]
94.  Dellinger RP, Bagshaw SM, Antonelli M, Foster DM, Klein DJ, Marshall JC, Palevsky PM, Weisberg LS, Schorr CA, Trzeciak S, Walker PM; EUPHRATES Trial Investigators. Effect of Targeted Polymyxin B Hemoperfusion on 28-Day Mortality in Patients With Septic Shock and Elevated Endotoxin Level: The EUPHRATES Randomized Clinical Trial. JAMA. 2018;320:1455-1463.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 223]  [Cited by in F6Publishing: 243]  [Article Influence: 40.5]  [Reference Citation Analysis (0)]
95.  Klein DJ, Foster D, Walker PM, Bagshaw SM, Mekonnen H, Antonelli M. Polymyxin B hemoperfusion in endotoxemic septic shock patients without extreme endotoxemia: a post hoc analysis of the EUPHRATES trial. Intensive Care Med. 2018;44:2205-2212.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 87]  [Cited by in F6Publishing: 119]  [Article Influence: 19.8]  [Reference Citation Analysis (0)]
96.  Monti G, Terzi V, Calini A, Di Marco F, Cruz D, Pulici M, Brioschi P, Vesconi S, Fumagalli R, Casella G. Rescue therapy with polymyxin B hemoperfusion in high-dose vasopressor therapy refractory septic shock. Minerva Anestesiol. 2015;81:516-525.  [PubMed]  [DOI]  [Cited in This Article: ]
97.  Iba T, Klein DJ. The wind changed direction and the big river still flows: from EUPHRATES to TIGRIS. J Intensive Care. 2019;7:31.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 8]  [Cited by in F6Publishing: 8]  [Article Influence: 1.6]  [Reference Citation Analysis (0)]
98.  Cohen J. The immunopathogenesis of sepsis. Nature. 2002;420:885-891.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1936]  [Cited by in F6Publishing: 1926]  [Article Influence: 87.5]  [Reference Citation Analysis (0)]
99.  Levi M, van der Poll T. Coagulation and sepsis. Thromb Res. 2017;149:38-44.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 380]  [Cited by in F6Publishing: 588]  [Article Influence: 73.5]  [Reference Citation Analysis (0)]
100.  Matsumoto H, Ogura H, Shimizu K, Ikeda M, Hirose T, Matsuura H, Kang S, Takahashi K, Tanaka T, Shimazu T. The clinical importance of a cytokine network in the acute phase of sepsis. Sci Rep. 2018;8:13995.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 82]  [Cited by in F6Publishing: 110]  [Article Influence: 18.3]  [Reference Citation Analysis (0)]
101.  Hack CE, Aarden LA, Thijs LG. Role of cytokines in sepsis. Adv Immunol. 1997;66:101-195.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 203]  [Cited by in F6Publishing: 196]  [Article Influence: 7.3]  [Reference Citation Analysis (0)]
102.  van der Poll T, van Deventer SJ. Cytokines and anticytokines in the pathogenesis of sepsis. Infect Dis Clin North Am. 1999;13:413-426, ix.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 222]  [Cited by in F6Publishing: 205]  [Article Influence: 8.2]  [Reference Citation Analysis (0)]
103.  Nakae H, Endo S, Inada K, Takakuwa T, Kasai T. Changes in adhesion molecule levels in sepsis. Res Commun Mol Pathol Pharmacol. 1996;91:329-338.  [PubMed]  [DOI]  [Cited in This Article: ]
104.  Shimaoka M, Park EJ. Advances in understanding sepsis. Eur J Anaesthesiol Suppl. 2008;42:146-153.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 46]  [Cited by in F6Publishing: 54]  [Article Influence: 3.4]  [Reference Citation Analysis (0)]
105.  Schouten M, Wiersinga WJ, Levi M, van der Poll T. Inflammation, endothelium, and coagulation in sepsis. J Leukoc Biol. 2008;83:536-545.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 432]  [Cited by in F6Publishing: 436]  [Article Influence: 27.3]  [Reference Citation Analysis (0)]
106.  Fong Y, Tracey KJ, Moldawer LL, Hesse DG, Manogue KB, Kenney JS, Lee AT, Kuo GC, Allison AC, Lowry SF. Antibodies to cachectin/tumor necrosis factor reduce interleukin 1 beta and interleukin 6 appearance during lethal bacteremia. J Exp Med. 1989;170:1627-1633.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 479]  [Cited by in F6Publishing: 529]  [Article Influence: 15.1]  [Reference Citation Analysis (0)]
107.  Chai Z, Gatti S, Toniatti C, Poli V, Bartfai T. Interleukin (IL)-6 gene expression in the central nervous system is necessary for fever response to lipopolysaccharide or IL-1 beta: a study on IL-6-deficient mice. J Exp Med. 1996;183:311-316.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 258]  [Cited by in F6Publishing: 252]  [Article Influence: 9.0]  [Reference Citation Analysis (0)]
108.  Kopf M, Baumann H, Freer G, Freudenberg M, Lamers M, Kishimoto T, Zinkernagel R, Bluethmann H, Köhler G. Impaired immune and acute-phase responses in interleukin-6-deficient mice. Nature. 1994;368:339-342.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1342]  [Cited by in F6Publishing: 1362]  [Article Influence: 45.4]  [Reference Citation Analysis (0)]
109.  Tilg H, Dinarello CA, Mier JW. IL-6 and APPs: anti-inflammatory and immunosuppressive mediators. Immunol Today. 1997;18:428-432.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 440]  [Cited by in F6Publishing: 431]  [Article Influence: 16.0]  [Reference Citation Analysis (0)]
110.  Schindler R, Mancilla J, Endres S, Ghorbani R, Clark SC, Dinarello CA. Correlations and interactions in the production of interleukin-6 (IL-6), IL-1, and tumor necrosis factor (TNF) in human blood mononuclear cells: IL-6 suppresses IL-1 and TNF. Blood. 1990;75:40-47.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 8]  [Cited by in F6Publishing: 9]  [Article Influence: 0.3]  [Reference Citation Analysis (0)]
111.  Steensberg A, Fischer CP, Keller C, Møller K, Pedersen BK. IL-6 enhances plasma IL-1ra, IL-10, and cortisol in humans. Am J Physiol Endocrinol Metab. 2003;285:E433-E437.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 669]  [Cited by in F6Publishing: 680]  [Article Influence: 32.4]  [Reference Citation Analysis (0)]
112.  Tilg H, Trehu E, Atkins MB, Dinarello CA, Mier JW. Interleukin-6 (IL-6) as an anti-inflammatory cytokine: induction of circulating IL-1 receptor antagonist and soluble tumor necrosis factor receptor p55. Blood. 1994;83:113-118.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 10]  [Cited by in F6Publishing: 12]  [Article Influence: 0.4]  [Reference Citation Analysis (0)]
113.  Zhang XL, Topley N, Ito T, Phillips A. Interleukin-6 regulation of transforming growth factor (TGF)-beta receptor compartmentalization and turnover enhances TGF-beta1 signaling. J Biol Chem. 2005;280:12239-12245.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 156]  [Cited by in F6Publishing: 176]  [Article Influence: 9.3]  [Reference Citation Analysis (0)]
114.  de Waal Malefyt R, Abrams J, Bennett B, Figdor CG, de Vries JE. Interleukin 10(IL-10) inhibits cytokine synthesis by human monocytes: an autoregulatory role of IL-10 produced by monocytes. J Exp Med. 1991;174:1209-1220.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2625]  [Cited by in F6Publishing: 2797]  [Article Influence: 84.8]  [Reference Citation Analysis (0)]
115.  Fiorentino DF, Zlotnik A, Mosmann TR, Howard M, O'Garra A. IL-10 inhibits cytokine production by activated macrophages. J Immunol. 1991;147:3815-3822.  [PubMed]  [DOI]  [Cited in This Article: ]
116.  Kellum JA, Kong L, Fink MP, Weissfeld LA, Yealy DM, Pinsky MR, Fine J, Krichevsky A, Delude RL, Angus DC; GenIMS Investigators. Understanding the inflammatory cytokine response in pneumonia and sepsis: results of the Genetic and Inflammatory Markers of Sepsis (GenIMS) Study. Arch Intern Med. 2007;167:1655-1663.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 510]  [Cited by in F6Publishing: 576]  [Article Influence: 33.9]  [Reference Citation Analysis (0)]
117.  Oda S, Hirasawa H, Shiga H, Nakanishi K, Matsuda K, Nakamua M. Sequential measurement of IL-6 blood levels in patients with systemic inflammatory response syndrome (SIRS)/sepsis. Cytokine. 2005;29:169-175.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 160]  [Cited by in F6Publishing: 167]  [Article Influence: 8.4]  [Reference Citation Analysis (0)]
118.  Bozza FA, Salluh JI, Japiassu AM, Soares M, Assis EF, Gomes RN, Bozza MT, Castro-Faria-Neto HC, Bozza PT. Cytokine profiles as markers of disease severity in sepsis: a multiplex analysis. Crit Care. 2007;11:R49.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 461]  [Cited by in F6Publishing: 525]  [Article Influence: 32.8]  [Reference Citation Analysis (0)]
119.  Tschaikowsky K, Hedwig-Geissing M, Braun GG, Radespiel-Troeger M. Predictive value of procalcitonin, interleukin-6, and C-reactive protein for survival in postoperative patients with severe sepsis. J Crit Care. 2011;26:54-64.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 95]  [Cited by in F6Publishing: 85]  [Article Influence: 6.1]  [Reference Citation Analysis (0)]
120.  Jekarl DW, Lee SY, Lee J, Park YJ, Kim Y, Park JH, Wee JH, Choi SP. Procalcitonin as a diagnostic marker and IL-6 as a prognostic marker for sepsis. Diagn Microbiol Infect Dis. 2013;75:342-347.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 101]  [Cited by in F6Publishing: 104]  [Article Influence: 9.5]  [Reference Citation Analysis (0)]
121.  Kumar AT, Sudhir U, Punith K, Kumar R, Ravi Kumar VN, Rao MY. Cytokine profile in elderly patients with sepsis. Indian J Crit Care Med. 2009;13:74-78.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 23]  [Cited by in F6Publishing: 26]  [Article Influence: 1.9]  [Reference Citation Analysis (0)]
122.  Gogos CA, Drosou E, Bassaris HP, Skoutelis A. Pro- vs anti-inflammatory cytokine profile in patients with severe sepsis: a marker for prognosis and future therapeutic options. J Infect Dis. 2000;181:176-180.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 620]  [Cited by in F6Publishing: 609]  [Article Influence: 25.4]  [Reference Citation Analysis (0)]
123.  Chaudhry H, Zhou J, Zhong Y, Ali MM, McGuire F, Nagarkatti PS, Nagarkatti M. Role of cytokines as a double-edged sword in sepsis. In Vivo. 2013;27:669-684.  [PubMed]  [DOI]  [Cited in This Article: ]
124.  Friesecke S, Stecher SS, Gross S, Felix SB, Nierhaus A. Extracorporeal cytokine elimination as rescue therapy in refractory septic shock: a prospective single-center study. J Artif Organs. 2017;20:252-259.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 96]  [Cited by in F6Publishing: 103]  [Article Influence: 14.7]  [Reference Citation Analysis (0)]
125.  Paul R, Sathe P, Kumar S, Prasad S, Aleem M, Sakhalvalkar P. Multicentered prospective investigator initiated study to evaluate the clinical outcomes with extracorporeal cytokine adsorption device (CytoSorb®) in patients with sepsis and septic shock. World J Crit Care Med. 2021;10:22-34.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 25]  [Cited by in F6Publishing: 21]  [Article Influence: 7.0]  [Reference Citation Analysis (0)]
126.  Brouwer WP, Duran S, Kuijper M, Ince C. Hemoadsorption with CytoSorb shows a decreased observed vs expected 28-day all-cause mortality in ICU patients with septic shock: a propensity-score-weighted retrospective study. Crit Care. 2019;23:317.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 87]  [Cited by in F6Publishing: 115]  [Article Influence: 23.0]  [Reference Citation Analysis (0)]
127.  Hawchar F, László I, Öveges N, Trásy D, Ondrik Z, Molnar Z. Extracorporeal cytokine adsorption in septic shock: A proof of concept randomized, controlled pilot study. J Crit Care. 2019;49:172-178.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 82]  [Cited by in F6Publishing: 102]  [Article Influence: 17.0]  [Reference Citation Analysis (0)]
128.  Rugg C, Klose R, Hornung R, Innerhofer N, Bachler M, Schmid S, Fries D, Ströhle M. Hemoadsorption with CytoSorb in Septic Shock Reduces Catecholamine Requirements and In-Hospital Mortality: A Single-Center Retrospective 'Genetic' Matched Analysis. Biomedicines. 2020;8.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 23]  [Cited by in F6Publishing: 45]  [Article Influence: 11.3]  [Reference Citation Analysis (0)]
129.  Bone RC. Sir Isaac Newton, sepsis, SIRS, and CARS. Crit Care Med. 1996;24:1125-1128.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 717]  [Cited by in F6Publishing: 619]  [Article Influence: 22.1]  [Reference Citation Analysis (0)]
130.  Le Tulzo Y, Pangault C, Amiot L, Guilloux V, Tribut O, Arvieux C, Camus C, Fauchet R, Thomas R, Drénou B. Monocyte human leukocyte antigen-DR transcriptional downregulation by cortisol during septic shock. Am J Respir Crit Care Med. 2004;169:1144-1151.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 118]  [Cited by in F6Publishing: 126]  [Article Influence: 6.3]  [Reference Citation Analysis (0)]
131.  Leijte GP, Rimmelé T, Kox M, Bruse N, Monard C, Gossez M, Monneret G, Pickkers P, Venet F. Monocytic HLA-DR expression kinetics in septic shock patients with different pathogens, sites of infection and adverse outcomes. Crit Care. 2020;24:110.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 38]  [Cited by in F6Publishing: 70]  [Article Influence: 17.5]  [Reference Citation Analysis (0)]
132.  Cajander S, Bäckman A, Tina E, Strålin K, Söderquist B, Källman J. Preliminary results in quantitation of HLA-DRA by real-time PCR: a promising approach to identify immunosuppression in sepsis. Crit Care. 2013;17:R223.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 39]  [Cited by in F6Publishing: 46]  [Article Influence: 4.2]  [Reference Citation Analysis (0)]
133.  Monneret G, Venet F. Monocyte HLA-DR in sepsis: shall we stop following the flow? Crit Care. 2014;18:102.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 36]  [Cited by in F6Publishing: 36]  [Article Influence: 3.6]  [Reference Citation Analysis (0)]
134.  Cazalis MA, Friggeri A, Cavé L, Demaret J, Barbalat V, Cerrato E, Lepape A, Pachot A, Monneret G, Venet F. Decreased HLA-DR antigen-associated invariant chain (CD74) mRNA expression predicts mortality after septic shock. Crit Care. 2013;17:R287.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 48]  [Cited by in F6Publishing: 58]  [Article Influence: 5.3]  [Reference Citation Analysis (0)]
135.  Meisel C, Schefold JC, Pschowski R, Baumann T, Hetzger K, Gregor J, Weber-Carstens S, Hasper D, Keh D, Zuckermann H, Reinke P, Volk HD. Granulocyte-macrophage colony-stimulating factor to reverse sepsis-associated immunosuppression: a double-blind, randomized, placebo-controlled multicenter trial. Am J Respir Crit Care Med. 2009;180:640-648.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 419]  [Cited by in F6Publishing: 452]  [Article Influence: 30.1]  [Reference Citation Analysis (0)]
136.  Spinetti T, Hirzel C, Fux M, Walti LN, Schober P, Stueber F, Luedi MM, Schefold JC. Reduced Monocytic Human Leukocyte Antigen-DR Expression Indicates Immunosuppression in Critically Ill COVID-19 Patients. Anesth Analg. 2020;131:993-999.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 43]  [Cited by in F6Publishing: 59]  [Article Influence: 14.8]  [Reference Citation Analysis (0)]
137.  Pinder EM, Rostron AJ, Hellyer TP, Ruchaud-Sparagano MH, Scott J, Macfarlane JG, Wiscombe S, Widdrington JD, Roy AI, Linnett VC, Baudouin SV, Wright SE, Chadwick T, Fouweather T, Juss JK, Chilvers ER, Bowett SA, Parker J, McAuley DF, Conway Morris A, Simpson AJ. Randomised controlled trial of GM-CSF in critically ill patients with impaired neutrophil phagocytosis. Thorax. 2018;73:918-925.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 35]  [Cited by in F6Publishing: 35]  [Article Influence: 5.8]  [Reference Citation Analysis (0)]