Ventilator-associated lower respiratory tract infections (VALRTIs) are among the most common ICU-acquired infections in patients receiving invasive mechanical ventilation (IMV). Immunocompromised patients may have a lower incidence of VALRTI when compared with nonimmunocompromised patients, but the influence of the type of immunosuppression on the epidemiology of VALRTI has not been investigated. The study objectives were to assess the association of the type of immunosuppression with the incidence, microbiology, and outcomes (ICU mortality, ICU length of stay, and duration of IMV) of VALRTI related to bacterial pathogens.

Multicenter, international retrospective cohort study.

One hundred eighteen ICUs (118) in nine countries.

Eight hundred fifty-four immunocompromised adult patients (median age, 65 yr; 57.6% males) requiring IMV for greater than 48 hours, including 162 with hematologic malignancies.

None.

Patients with hematologic malignancies had a lower 28-day cumulative incidence of bacterial VALRTI than patients with other types of immunosuppression (13.6% vs. 20.1%; adjusted cause-specific hazard ratio, 0.61; 95% CI, 0.37-0.97), mostly due to a lower incidence of ventilator-associated pneumonia (9.3% vs. 13.9%). The proportion of VALRTI cases related to multidrug-resistant bacteria was similar between groups. Occurrence of bacterial VALRTI was associated with an increased mortality and a longer ICU length of stay, but this effect was independent of the type of immunosuppression.

Patients with hematologic malignancies had a lower 28-day cumulative incidence of bacterial VALRTI than patients with other types of immunosuppression, mainly due to a lower incidence of ventilator-associated pneumonia.

To describe in-hospital and one-year mortality and to identify prognostic variables associated with mortality.

Retrospective cohort study.

Tertiary referral hospital in Barcelona (Spain).

Consecutive patients with solid cancer and unplanned admission to the ICU over a ten year period (2010-2019).

In-hospital mortality, one-year mortality, type of cancer, metastatic disease, ECOG, APACHE, SOFA, invasive mechanical ventilation, vasoactive drugs, renal replacement therapy.

Three hundred and ninety-five patients were admitted to the ICU; 193 (48.8%) had metastatic disease, and 22 (5.9%) presented neutropenia. The median SOFA score on day 1 of ICU admission was 6 (3-9). ICU, in-hospital, and one-year mortality were 27.9% (110 patients), 39% (139 patients), and 61.1% (236 patients), respectively. A non-surgical admission, a higher ECOG, a SOFA score > 9 on day 1, a non-decreasing SOFA score on day 5, and requiring invasive mechanical ventilation were factors associated with in-hospital mortality. ECOG, inability to resume anticancer therapy, and ICU admission due to respiratory failure were associated with one-year mortality in hospital survivors.

Survival in critically ill solid cancer patients is substantial, even when metastatic disease exists. Short-term outcomes were associated with ECOG and organ dysfunction, not cancer per se. The prognosis of patients with a non-decreasing SOFA score on day 5 is poor, especially when the SOFA score on day 1 was >9. Long-term mortality was associated with functional status and inability to resume anticancer therapy.

Prognostic systems predicting death risk may vary for patients with haematological malignancies needing ICU care. This study externally validated SAPS 3 using a retrospective cohort of adults with these conditions in the ICU. The score was calculated at admission using the general and South America-adjusted formulas. Mortality discrimination was assessed via AUC-ROC, and calibration by Hosmer-Lemeshow goodness-of-fit and graphical analysis with a calibration belt. The analysis included 273 admissions, with 119 deaths. Discriminative capacity was low (AUC-ROC 0.56, CI 95% 0.49-0.63). There was a poor correlation between expected and observed events across all risk deciles (Hosmer-Lemeshow 10.45, p = 0.0635). Similar results were found with the South America-adjusted formula. SAPS 3 does not effectively discriminate between survivors and non-survivors, underestimating risk in low-risk groups and overestimating it in high-risk groups. Mortality risk estimation in this scenario should rely on clinical judgment.

Cancer patients who are exposed to sepsis and had previous chemotherapy may have increased severity. Among chemotherapeutic agents, anthracyclines have been associated with cardiac toxicity. Like other chemotherapeutic agents, they may cause endothelial toxicity. The aim of this study was to evaluate the effect of anthracycline treatment on the outcome of cancer patients with sepsis.

Data from cancer patients admitted to intensive care units (ICUs) for sepsis or septic shock were extracted from the Groupe de Recherche Respiratoire en Réanimation Onco-Hématologique database (1994-2015). Comparison between patients who received anthracycline and those who did not was performed using a propensity score, including confounding variables (age and underlying diseases). A competing risk adjusted for severity of illness (Sequential Organ Failure Assessment [SOFA] score) was used to analyze the duration of vasopressor requirement.

Among 2046 patients, 1070 (52.3%) patients who received anthracycline were compared with 976 (47.7%) who did not. The underlying disease was mostly acute hematological malignancy (49.2%). Sepsis, mostly pneumonia (47.7%), had developed 2 days (interquartile range [IQR]:1-4 days) prior to ICU admission. Most patients (n=1156/1980,58.4%) required vasopressors for 3 days (IQR: 2-6 days). Factors associated with the need for vasopressors were aplasia (hazard ratio [HR]=1.72, 95% confidence interval [CI]: 1.21 to 2.47, P=0.002) and day 1 respiratory SOFA score (HR=7.07, 95% CI: 2.75 to 22.1, P <0.001). Previous anthracycline treatment was not associated with an increased risk of vasopressor use. The duration of vasopressors was not different between patients who received anthracycline and those who did not (P=0.79). Anthracycline was not associated with ICU mortality.

Previous anthracycline treatment did not alter the course of sepsis in a cohort of cancer patients admitted to intensive care with sepsis.

To evaluate the predictive ability of mortality prediction scales in cancer patients admitted to intensive care units (ICUs).

A systematic review of the literature was conducted using a search algorithm in October 2022. The following databases were searched: PubMed, Scopus, Virtual Health Library (BVS), and Medrxiv. The risk of bias was assessed using the QUADAS-2 scale.

ICUs admitting cancer patients.

Studies that included adult patients with an active cancer diagnosis who were admitted to the ICU.

Integrative study without interventions.

Mortality prediction, standardized mortality, discrimination, and calibration.

Seven mortality risk prediction models were analyzed in cancer patients in the ICU. Most models (APACHE II, APACHE IV, SOFA, SAPS-II, SAPS-III, and MPM II) underestimated mortality, while the ICMM overestimated it. The APACHE II had the SMR (Standardized Mortality Ratio) value closest to 1, suggesting a better prognostic ability compared to the other models.

Predicting mortality in ICU cancer patients remains an intricate challenge due to the lack of a definitive superior model and the inherent limitations of available prediction tools. For evidence-based informed clinical decision-making, it is crucial to consider the healthcare team's familiarity with each tool and its inherent limitations. Developing novel instruments or conducting large-scale validation studies is essential to enhance prediction accuracy and optimize patient care in this population.

The onset of hematological malignancies can lead to acute and critical situations. It can also result in adverse outcome despite the significant advancements made in their therapeutic management. In this context, advance care planning and, in particular, advance directives (AD) play an essential role. However, the use of AD in patients with malignant hematological conditions remains very rare.

The aim was to evaluate the perception of AD by hematologists. We conducted a national online survey in France. All hematologist working in a hospital setting and treating malignant hemopathies were solicited. The questionnaire covered five areas: personal perception of AD; assistance in writing AD; patient information about AD; use of ADs; and demographic data.

318 hematologists (33.7% of the whole population), working in 103 different centers across France participated in the study. 72.6% (n = 231) of the respondents believed that AD could be beneficial for patient's care. Only 32.7% talked about AD with their patients on a regular basis. The lack of utilization was correlated with the fear of creating anxiety for the patient (64.9%; n = 172) or for relatives (30.9%; n = 80), as well as the belief that AD were deemed inappropriate for their patients (57.8%; n = 145). 19.5% (n = 62) of responding hematologist offered their assistance to patients in writing AD. This proportion was higher in physicians who had previously worked in palliative care unit (35,6% vs. 16,8%, p = 0,0004).

The majority of the surveyed hematologist hold a positive opinion about AD. However, only a few discuss the matter with their patients. The fear of consequences for patients and relatives, particularly anxiety, remains the primary barrier to providing information about AD.

Our study aimed to identify relevant features associated with the reprisal of antineoplastic treatment in patients with solid cancers after unplanned admittance to the intensive care unit (ICU) and to assess 60th-month survival in patients with solid neoplasms admitted to the ICU.

This single-centre retrospective study of critically ill patients with active cancers was performed over a 13-year period (2005-2018). Patients' characteristics, overall survival, and antineoplastic treatment reprisal were extracted from digital medical files and compared.

134 patients were included in the study. Solid neoplasms were mostly localised to the head and neck (n = 53) followed by lung cancers (n = 29). Sepsis was the leading cause of ICU admission (62.1%) with 41/82 patients presenting with septic shock. Antineoplastic treatments were resumed in 40 patients. An age ≤60 years and an Eastern Cooperative Oncology Group (ECOG) performance status (PS) ≤1 were found to be predictors for treatment reprisal, with odd ratios of, respectively, 2.83 (95% CI, 1.15-6.99) and 5.45 (95% CI, 2.01-14.82); area under the ROC curve of 72% (95% CI, 63-81%). Survival after the immediate discharge from the ICU was 101/134 (75%) and the 60-month survival rate was 29% and significantly higher in the treatment-reprisal group.

Age and ECOG PS were found to be predictors for treatment reprisal in patients with solid neoplasms admitted to the ICU. The latter benefits from better long-term survival.

Little is known about outcomes from cancer chemotherapy--associated infections in sub-Saharan Africa. Accordingly, among patients with cancer admitted with postchemotherapy infection in Mbarara, Uganda, we aimed to determine (1) the 30-day case fatality rate, (2) factors associated with mortality rate, and (3) clinical risk score performance.

We enrolled participants aged ≥18 years if they (1) received cancer chemotherapy within the past 30 days, (2) were admitted to the oncology ward, and (3) were prescribed intravenous antibiotics. We used Cox proportional hazards regression to determine predictors of death at 30 days and calculated the area under the receiver operating characteristic curve (AUC) for each clinical risk score.

Among 150 participants, 67 (45%) were female, and the median (interquartile range) age was 56 (43-66) years. Esophageal cancer (18%) and pneumonia (42%) were the most common cancer and infection, respectively. Death occurred within 30 days in 63 participants (42%). Quick Sequential Organ Failure Assessment (qSOFA) score ≥2 (adjusted hazard ratio, 2.51 [95% confidence interval, 1.42-4.44]; P = .001), and Universal Vital Assessment (UVA) score >4 (2.13 [.08-4.18, P = .03) were independently associated with death at 30 days. An Eastern Cooperative Oncology Group (ECOG) score ≥3 was similarly independently associated with death at 30 days in the qSOFA and UVA models. The AUCs for qSOFA and UVA scores were 0.70 (95% confidence interval, .63-.79) and 0.72 (.64-.80), respectively.

In participants with postchemotherapy infection in Mbarara, Uganda, the case fatality rate was high. ECOG, qSOFA, and UVA scores were associated with death at 30 days.

To compare the 18-month survival between patients with newly diagnosed cancer discharged home after early unplanned ICU admission and those without early unplanned ICU admission; we also evaluated the frequency and risk factors for early unplanned ICU admission.

Observational study with prospectively collected data from September 2019 to June 2021 and 18 months follow-up.

Single dedicated cancer center in São Paulo, Brazil.

We screened consecutive adults with suspected cancer and included those with histologically proven cancer from among 20 highly prevalent cancers.

None.

The exposure was early unplanned ICU admission, defined as admission for medical reasons or urgent surgery during the first 6 months after cancer diagnosis. The main outcome was 18-month survival after cancer diagnosis, and the main analysis was Cox's proportional hazards model adjusted for confounders and immortal time bias. Propensity score matching was used in the sensitivity analysis. We screened 4738 consecutive adults with suspected cancer and included 3348 patients. Three hundred twelve (9.3%) had early unplanned ICU admission, which was associated with decreased 18-month survival both in the unadjusted (hazard ratio, 4.03; 95% CI, 2.89-5.62) and adjusted (hazard ratio, 1.84; 95% CI, 1.29-2.64) models. The sensitivity analysis confirmed the results because the groups were balanced after matching, and the 18-month survival of patients with early ICU admission was lower compared with patients without early ICU admission (87.0% vs. 93.9%; p = 0.01 log-rank test). Risk factors for early unplanned ICU admission were advanced age, comorbidities, worse performance status, socioeconomic deprivation, metastatic tumors, and hematologic malignancies.

Patients with newly diagnosed cancer discharged home after early unplanned ICU admission have decreased 18-month survival compared with patients without early unplanned ICU admission.

The intensive care unit (ICU) mortality rate remains high, especially in developing countries, regardless of the advances in critical management. There is a lack of studies about mortality causes in hospitals and particularly ICUs in Palestine.This study evaluated the demographic and clinical characteristics of critically ill patients and determined the predictors of mortality among patients in the ICU.

A retrospective study assessed all patients who stayed in the ICU for more than 24 h from January 2017 to January 2019. Data were collected from the patient's files. Patient characteristics (background, clinical variables, and comorbidities) were recorded.

The study included 227 eligible ICU patients. The cases' mean age was 55.5 (SD ± 18.2) years. The overall ICU mortality rate was 31.7%. The following factors were associated with high adjusted mortality odds: admission from inside the hospital (adjusted odds ratio (aOR), 2.1, 95% CI: 1.1-3.9, p < 0.05), creatinine level ≥2 mg/dl on admission (aOR, 2.7, 95% CI: 1.3-5.8, p < 0.01), hematology malignancy patients (aOR, 3.4, 95% CI: 1.6-6.7, p = 0.001), immune-compromised (aOR, 2.5, 95% CI: 1.3-4.7, p < 0.01), septic shock (aOR, 27.1, 95% CI: 7.9-88.3, p < 0.001), hospital-acquired infections (aOR: 13.4, 95% CI: 4.1-57.1, p < 0.001), and patients with multiple-source infection (aOR: 16.3, 95% CI: 6.4-57.1, p < 0.001). Also, high SOFA and APACHE scores predicted morality (p < 0.001).

The mortality rate among ICU patients was high. It was higher among those admitted from the hospital wards, septic shock, hospital-acquired infection, multiple infection sources, and multi-drug resistance infections. Thus, strategies should be developed to enhance the ICU environment and provide sufficient resources to minimize the effects of these predictors.

Outcomes of patients with hematologic malignancies requiring ICU care for critical illness are suboptimal and represent a major unmet need in this population. We present data from a dedicated haematology oncology setting including 63 patients with a median age of 60 years admitted to the ICU for critical illness with organ dysfunction. The most common underlying diagnosis was multiple myeloma (30%) followed by acute myeloid leukemia (25%). Chemotherapy had been initiated for 90.7% patients before ICU admission. The most common indication for ICU care was respiratory failure (36.5%) and shock (17.5%) patients. Evidence of sepsis was present in 44 (69%) patients. After shifting to ICU, 32 (50%) patients required inotropic support and 18 (28%) required invasive mechanical ventilation. After a median of 5 days of ICU stay, 43.1% patients had died, most commonly due to multiorgan dysfunction. Risk of mortality was higher with involvement of more than two major organs (p = .001), underlying AML (p = .001), need for mechanical ventilation (p = .001) and high inotrope usage (p = .004). Neutropenia was not associated with mortality. Our study indicates high rates of short term mortality and defines prognostic factors which can be used to prognosticate patients and establish goals of care.

The online version contains supplementary material available at 10.1007/s12288-024-01757-3.

Prognosis in oncology has improved with early diagnosis and novel therapies. However, critical illness continues to trigger clinical and ethical dilemmas for the treating oncology and intensive care unit (ICU) doctors.

The objective of this study was to investigate the perceptions of oncology and ICU doctors in managing critically ill cancer patients.

A cross-sectional web-based survey exploring the management of a fictitious acutely deteriorating case vignette with solid-organ malignancy. The survey weblink was distributed between May and July 2022 to all Australian oncology and ICU doctors via newsletters to the members of the Medical Oncology Group of Australia, the Australian and New Zealand Intensive Care Society, and the College of Intensive Care Medicine inviting them to participate. The weblink was active till August 2022. The six domains included patient prognostication, advanced care plan, collaborative management, legal/ethical/moral challenges, ICU referral, and protocol-based ICU admission. The outcomes were reported as the level of agreement between oncology and ICU doctors for each domain/question.

184 responses (64 oncology and 120 ICU doctors) were analysed. Most respondents were specialists (78.1% [n = 50] oncology, 78.3% [n = 94] ICU doctors). Oncology doctors more commonly reported managing cancer patients with poor prognosis than ICU doctors (p < 0.001). Oncology doctors less commonly referred such patients for ICU admission (29.7% [n = 19] vs. 80.8% [n = 97], p < 0.001; odds ratio [OR] = 0.07; 95% confidence interval [CI]: 0.03-0.16) and infrequently encountered patients with prior goals of care (GOC) in medical emergency team escalations (40.6% [n = 26] vs. 86.7% [n = 104]; p < 0.001; OR = 0.06; 95% CI: 0.02-0.15; p < 0.001). Oncology doctors were less likely to discuss GOC during medical emergency team calls or within 24 h of ICU admission. More oncology doctors than ICU doctors thought that training rotation in the corresponding speciality group was beneficial (56.3% [n = 36] vs. 31.7% [n = 38]; p = 0.012; OR = 2.07; 95% CI: 1.02-4.23; p = 0.045).

Oncology doctors were less likely to encounter acute patient deterioration or establish timely GOC for such patients. Oncology doctors believed that an ICU rotation during their training may have helped manage challenging situations.

Sepsis is a significant and common cause of death and burden among critically ill patients, which has increasing incidence and mortality in adults over 60 and advanced age. This study aimed to develop an easy-to-use clinical tool for assessing 28-day mortality risk in older sepsis patients upon their initial assessment in the emergency department (ED).

A retrospective cohort study was conducted using electronic medical records of older (≥60 years) ED patients with suspected sepsis from August 1, 2018, to December 31, 2018. A new prediction score was formulated based on the logistic coefficients of clinical predictors through multivariable regression analyses. Then, the score's screening performance was evaluated and compared to existing scoring systems; Systemic Inflammatory Response Syndrome (SIRS), quick Sequential Organ Failure Assessment (qSOFA), National early warning score (NEWS), and The Ramathibodi early warning score (REWS); using receiver operating characteristic curve analysis (AuROC).

The study included 599 patients with the mean age of 77.13 (range: 60-101) years (56.43% male) and an overall 28-day mortality rate of 7.01%. The newly developed prediction score had seven independent predictors of 28-day mortality: malignancy, dependent status, heart rate, respiratory rate, oxygen saturation, consciousness, and lactate, which demonstrated excellent discriminative ability (AuROC: 0.87, 95% confidence interval (CI): 0.82 - 0.92), significantly outperforming SIRS (AuROC: 0.62), qSOFA (AuROC: 0.72), NEWS (AuROC: 0.74), and REWS (AuROC: 0.71), all with p-values <0.01. The score allowed risk stratification into low-risk (positive likelihood ratio (LR+): 0.37, 95% CI: 0.24 - 0.58) and high-risk (LR+: 4.14, 95% CI: 3.14 - 5.44) groups with sensitivity of 69.0% and specificity of 83.3% at a cut-off point of 6.

The novel prediction score demonstrates a remarkable ability to predict 28-day mortality risk in older sepsis patients during their initial ED assessment, offering potential for improved risk stratification and treatment guidance in older patients.

Background The antecedents of readmission among survivors of intensive care units (ICUs) are complex and comprise an array of elements that impact the rehabilitation process after leaving the ICU. The aforementioned determinants may comprise socioeconomic factors, access to follow-up healthcare, the nature and severity of the initial illness or injury, the presence of comorbidities, the sufficiency of transitional care and rehabilitation services, and patient and family support systems. Added to this, the risk of readmission may be increased by complications that develop during the ICU stay, including but not limited to infections, organ dysfunction, and psychological distress. Comprehending these determinants is of the utmost importance for healthcare providers in order to execute focused interventions that seek to diminish readmission rates, enhance patient outcomes, and elevate the standard of care for survivors of ICUs. Objective The objective of the study is to determine the factors associated with readmission among ICU survivors and the cause of readmission. Methodology This prospective observational study was conducted in a tertiary-level ICU. The duration of the study was one year and we enrolled 108 ICU survivors in our study. We have recorded patient demographic data, comorbidity, primary diagnosis, previous treatment history (vasopressor, sedation), causes of readmission, duration of previous ICU stay, and outcome of readmitted patient (discharge, death, and transfer to lower facility). Result The incidence of readmission in our ICU is 10.4%; 50-70 age groups are more prone to readmission of which the male sex is predominant (64.81%). In our study, hypertension (cardiac, 18.52%) and diabetes mellitus (11.11%) were the most common comorbidities reported in readmitted patients. The majority of patients who get readmission suffered from blunt trauma abdomen. In the majority of readmitted patients, sedation was used in the previous admission for ventilation and patient comfort (66.67%). Most of the readmitted patients (68.51%) have a previous ICU stay of more than five days. Patients were readmitted mainly because of respiratory (30.56%) and neurological (25%) complications. In this study, readmitted patients have high mortality (59.26%). Conclusion In a tertiary care ICU, the incidence rate of readmitted patients was 10.4%. Respiratory and neurological problems were the main cause of readmission. In readmitted patients, mortality was high up to 59.26%. Old age, male sex, prolonged ICU stay, comorbidities like hypertension, blunt trauma abdomen, use of sedation, and prolonged mechanical ventilation in previous ICU admission are major risk factors for ICU readmission.

To determine the epidemiological effect-magnitude and outcomes of patients with cancer vs those without cancer who are hospitalized with acute respiratory failure (ARF).

We reviewed hospitalizations within the National Inpatient Sample (NIS) database between January 1, 2016, and December 31, 2018. Patients were classified based on a diagnosis of solid-organ cancer, hematologic cancer, or no cancer. Noninvasive positive pressure ventilation (NIPPV) failure was defined as patients who initially received NIPPV and had progression to invasive mechanical ventilation. Weighted samples were used to derive population estimates.

During the study period, there were an estimated 8,837,209 admissions with ARF in the United States, 8.9% (783,625) of which had solid-organ cancer and 2.0% (176,095) had hematologic cancers. Annually, 319,907 patients with cancer are admitted with ARF, with 27.3% (87,302) requiring invasive mechanical ventilation and 10.0% (31,998) requiring NIPPV. In-hospital mortality was higher in patients with cancer vs those without cancer (24.0% [76,813] vs 12.3% [322,465]; P<.001), and this proprotion persisted when stratified by the highest method of oxygen delivery. Patients with cancer had longer hospital length of stay (7.0 days [3.0 to 12.0 days] vs 5.0 days [3.0 to 10.0 days]; P<.001) and were more likely to have NIPPV failure (14.9% [3,992] vs 12.8% [41,875]). Compared with those with solid-organ cancer, patients with hematologic cancers experienced worse outcomes. The association between underlying cancer diagnosis and outcomes remained consistent when adjusted for age, sex, and comorbidities.

In the United States, patients with cancer account for over 10% of ARF hospital admissions (959,720 of 8,837,209). They experience an approximately 2-fold higher mortality versus those without cancer. Those with hematologic cancers appear to experience worse outcomes than patients with solid-organ cancers.

Despite the increasing number of ICU admissions among patients with solid tumours, there is a lack of tools with which to identify patients who may benefit from critical support. We aim to characterize the clinical profile and outcomes of patients with solid malignancies admitted to the ICU.

Retrospective observational study of patients with cancer non-electively admitted to the ICU of the Hospital Clinic of Barcelona (Spain) between January 2019 and December 2019. Data regarding patient and neoplasm characteristics, ICU admission features and outcomes were collected from medical records.

97 ICU admissions of 84 patients were analysed. Lung cancer (22.6%) was the most frequent neoplasm. Most of the patients had metastatic disease (79.5%) and were receiving oncological treatment (75%). The main reason for ICU admission was respiratory failure (38%). Intra-ICU and in-hospital mortality rates were 9.4% and 24%, respectively. Mortality rates at 1, 3 and 6 months were 19.6%, 36.1% and 53.6%. Liver metastasis, gastrointestinal cancer, hypoalbuminemia, elevated basal C-reactive protein, ECOG-PS greater than 2 at ICU admission, admission from ward and an APACHE II score over 14 were related to higher mortality. Functional status was severely affected at discharge, and oncological treatment was definitively discontinued in 40% of the patients.

Medium-term mortality and functional deterioration of patients with solid cancers non-electively admitted to the ICU are high. Surrogate markers of cachexia, liver metastasis and poor ECOG-PS at ICU admission are risk factors for mortality.

Thrombocytopenia is common in critically ill patients with cancer. However, the association of platelet count with spontaneous bleeding is controversial in critically ill patients and the association with cancer-related characteristics is unknown.

This observational study includes patients with active cancer and severe thrombocytopenia. A logistic regression model adjusted for confounders was used to evaluate the association of daily platelet count and cancer-related characteristics (type of cancer and presence of metastasis) with spontaneous bleeding. Confounders were identified using directed acyclic graphs.

We screened 5822 patients, 255 (4.4%) met eligibility criteria resulting in 1401 daily observations. Fifty-three patients (20.8%) had spontaneous bleeding during the intensive care unit stay, 64% presenting minor, and 36% major bleeding. The adjusted odds ratio (OR) for spontaneous bleeding with platelet count between 49 and 20 × 109 /L was 4.6 (1.1-19.6), with platelet count between 19 and 10 × 109 /L was 14.2 (3.1-66.2), and with platelet count below 10 × 109 /L was 39.6 (6.9-228.5). The adjusted OR for spontaneous bleeding in patients with hematologic malignancies was 0.6 (0.4-1.2), and 4.3 (2.0-9.0) for patients with metastatic tumor.

In critically ill patients with active cancer and severe thrombocytopenia, lower counts of platelets and presence of metastasis are associated with increased risk of spontaneous bleeding, while hematologic malignancy is not associated with increased risk of spontaneous bleeding.

The aim of the present study was to identify factors predicting in-hospital mortality in patients with cancer admitted to a medical Intensive Care Unit (ICU), and to evaluate their functional status and survival during follow-up at the oncology service in the initial 12 months after hospital discharge. A retrospective observational study was performed on 129 consecutive oncological patients with solid tumours admitted to the medical ICU of the Hospital del Mar (Barcelona, Spain) between January 2016 and June 2018. Demographics, and clinical data in-ICU and in-hospital mortality were recorded. Post-hospital discharge follow-up was also carried out. ICU and hospital mortality rates were 24% (n=31) and 40.3% (n=52), respectively. Sequential Organ Failure Assessment (SOFA) score (HR, 1.20; 95% CI, 1.01-1.42; P=0.037), neutropenia on admission (HR, 8.53; 95% CI, 2.15-33.82; P=0.002), metastatic disease (HR, 3.92; 95% CI, 1.82-8.45; P<0.001), need for invasive mechanical ventilation (HR, 5.78; 95% CI, 1.61-20.73; P=0.007), surgery during hospital admission (HR, 0.23; 95% CI, 0.09-0.61; P=0.003) and ICU stay (>48 h) (HR, 0.11; 95% CI, 0.04-0.29; P<0.001) were the independent risk factors for ICU mortality. Overall, 59.5% of the survivors had good functional status at hospital discharge and 28.7% of patients with cancer admitted to the ICU were alive 1 year after hospital discharge, most of them (85.7%) with good functional status (Eastern Cooperative Oncology Group 0-1). In conclusion, hospital mortality may be associated with SOFA score at ICU admission, the need for invasive mechanical ventilation, neutropenia and metastatic disease. Only 40% of patients with oncological disease admitted to the ICU died during their hospital stay, and >50% of the survivors presented good functional status at hospital discharge. Notably, 1 year after hospital discharge, 28.7% of patients were alive, most of them with a good functional status.

Sepsis is not only a leading cause of intensive care unit (ICU) admission but also one of the variables which affect outcomes of cancer patients. We aimed to assess the clinical characteristics, clinical course, mortality and risk factors associated with 30-day mortality in medical oncology patients admitted in a multi-disciplinary medical ICU.

We conducted a retrospective analysis of 435 consecutive cancer patients admitted in medical ICU over a 28 months period. Patients were divided into two groups based on the presence of sepsis at the time of ICU admission. Data regarding baseline patient characteristics, clinical and laboratory data, need for organ support and 30-day mortality were collected. Sepsis patients were further classified as 30-day survivors and non-survivors and risk factors for mortality in these patients were determined.

Overall 30-day mortality was 57.8%. It was significantly higher in sepsis group patients (73.9%) as compared to non-sepsis patients (46.6%) (p < 0.001). Most common reason for ICU admission in non-sepsis group was respiratory distress (51.4%) followed by altered sensorium (28.4%). Presence of metastasis [odds ratio, OR: 3.89 (95% confidence interval, CI: 1.536-9.901)], high lactate [OR: 1.374 (95% CI: 1.024-1.843)] and need of invasive mechanical ventilator (IMV) support [OR: 7.634 (95% CI: 2.519-23.256)] or vasopressor support [OR: 3.268 (95% CI: 1.179-9.090)] were directly associated with 30-day mortality.

Critically ill cancer patients admitted with sepsis had high mortality. Presence of metastasis, high lactate and need of IMV or vasopressor support was associated with worse prognosis in cancer patients admitted with sepsis in ICU.

Enterococcal bacteremia is associated with high mortality and long-term hospitalization. Here, we aimed to investigate the clinical outcomes and evaluate the risk factors for mortality in adult patients treated with vancomycin (VCM) for vancomycin-susceptible Enterococcus faecium (E. faecium) bacteremia.

This is a retrospective, record-based study. The data were collected from inpatients at a single university hospital between January 2009 and December 2020. The area under the curve (AUC) of VCM was calculated using the Bayesian approach. The primary outcome was a 30-day in-hospital mortality.

A univariate analysis showed significant differences in the concomitant use of vasopressors, history of the use of no clinically relevant activity antimicrobial agents against E. faecium, VCM plasma trough concentration, and renal dysfunction during VCM administration between the 30-day in-hospital mortality and survival groups. However, the groups' AUC/minimum inhibitory concentration (MIC) were not significantly different. A multivariate analysis suggested that concomitant vasopressors may be an independent risk factor for 30-day in-hospital mortality (odds ratio, 7.81; 95% confidence interval, 1.16-52.9; p = 0.035). The VCM plasma trough concentrations and the AUC/MIC in the mortality group were higher than those in the surviving group. No association between the AUC/MIC and the treatment effect in E. faecium bacteremia was assumed, because the known, target AUC/MIC were sufficiently achieved in the mortality group.

There may be no association between the AUC/MIC and the treatment effect in E. faecium bacteremia. When an immunocompromised host develops E. faecium bacteremia with septic shock, especially when a vasopressor is used in a patient with unstable hemodynamics, it may be difficult to treat it, despite efforts to ensure the appropriate AUC/MIC and therapeutic vancomycin concentration levels.

Cancer patients who are admitted to hospitals are at high risk of short-term deterioration due to treatment-related or cancer-specific complications. A rapid response system (RRS) is initiated when patients who are deteriorating or at risk of deteriorating are identified. This study was conducted to develop a deep learning-based early warning score (EWS) for cancer patients (Can-EWS) using delta values in vital signs.

A retrospective cohort study was conducted on all oncology patients who were admitted to the general ward between 2016 and 2020. The data were divided into a training set (January 2016-December 2019) and a held-out test set (January 2020-December 2020). The primary outcome was clinical deterioration, defined as the composite of in-hospital cardiac arrest (IHCA) and unexpected intensive care unit (ICU) transfer.

During the study period, 19,739 cancer patients were admitted to the general wards and eligible for this study. Clinical deterioration occurred in 894 cases. IHCA and unexpected ICU transfer prevalence was 1.77 per 1000 admissions and 43.45 per 1000 admissions, respectively. We developed two models: Can-EWS V1, which used input vectors of the original five input variables, and Can-EWS V2, which used input vectors of 10 variables (including an additional five delta variables). The cross-validation performance of the clinical deterioration for Can-EWS V2 (AUROC, 0.946; 95% confidence interval [CI], 0.943-0.948) was higher than that for MEWS of 5 (AUROC, 0.589; 95% CI, 0.587-0.560; p < 0.001) and Can-EWS V1 (AUROC, 0.927; 95% CI, 0.924-0.931). As a virtual prognostic study, additional validation was performed on held-out test data. The AUROC and 95% CI were 0.588 (95% CI, 0.588-0.589), 0.890 (95% CI, 0.888-0.891), and 0.898 (95% CI, 0.897-0.899), for MEWS of 5, Can-EWS V1, and the deployed model Can-EWS V2, respectively. Can-EWS V2 outperformed other approaches for specificities, positive predictive values, negative predictive values, and the number of false alarms per day at the same sensitivity level on the held-out test data.

We have developed and validated a deep learning-based EWS for cancer patients using the original values and differences between consecutive measurements of basic vital signs. The Can-EWS has acceptable discriminatory power and sensitivity, with extremely decreased false alarms compared with MEWS.

Over the past decade, ECMO has provided temporary cardiopulmonary support to an increasing number of patients, but the use of extracorporeal membrane oxygenation (ECMO) to provide temporary respiratory and circulatory support to adult patients with malignancy remains controversial.

This paper reviews the specific use of extracorporeal membrane oxygenation (ECMO) in oncology patients.

We searched PubMed, CINAHL, Cochrane Library, and Embase databases for studies on the use of ECMO in cancer patients between 1998 and 2022. Twenty-four retrospective, prospective, and case reports were included. The primary outcome was survival during extracorporeal membrane oxygenation.

Most studies suggest that ECMO can be used in oncology patients requiring life support during surgery, solid tumor patients with respiratory failure, and hematological tumor patients requiring ECOM as a supportive means of chemotherapy; however, in patients with hematologic oncology undergoing hematopoietic stem cell transplantation, there was no clear benefit after the use of ECMO.

Current research suggests that ECMO may be considered as a salvage support in specific cancer patients. Future studies should include larger sample sizes than those already conducted, including studies on efficacy, adverse events, and health.

Increasing evidence argues for the promotion of tumorigenesis through activation of the renin-angiotensin system pathway. Accordingly, a benefit of renin-angiotensin system blockers (RABs) treatments has been suggested in patients with solid cancers in terms of survival. We aimed to evaluate in-ICU survival and one-year survival in cancer patients admitted to the ICU with respect to the use of RABs. We conducted a retrospective observational single-center study in a 24-bed medical ICU. We included all solid cancer patients (age ≥ 18 years) requiring unplanned ICU admission. From 2007 to 2020, 1845 patients with solid malignancies were admitted (median age 67 years (59-75), males 61.7%). The most frequent primary tumor sites were the gastrointestinal tract (26.8%), the lung (24.7%), the urological tract (20.1%), and gynecologic and breast cancers (13.9%). RABs were used in 414 patients, distributed into 220 (53.1%) with angiotensin-receptor blockers (ARBs) and 194 (46.9%) with angiotensin-converting enzyme inhibitors (ACEis). After multivariate adjustment, ARBs use (OR = 0.62, 95%CI (0.40-0.92), p = 0.03) and ACEis use (OR = 0.52, 95%CI (0.32-0.82), p = 0.006) were both associated with improved in-ICU survival. Treatment with ARBs was independently associated with decreased one-year mortality (OR = 0.6, 95%CI (0.4-0.9), p = 0.02), whereas treatment with ACEis was not. In conclusion, this study argues for a beneficial impact of RABs use on the prognosis of critically ill cancer patients.

Delirium, a common neuropsychiatric syndrome among hospitalized patients, has been associated with significant morbidity and mortality in patients undergoing hematopoietic stem cell transplantation (HSCT). Although delirium is often reversible with prompt diagnosis and appropriate management, timely screening of hospitalized patients, including HSCT recipients at risk for delirium, is lacking. The association between delirium symptoms and healthcare utilization among HSCT recipients is also limited. We conducted a retrospective analysis of 502 hospitalized patients admitted for allogeneic or autologous HSCT at 2 tertiary care hospitals between April 2016 and April 2021. We used Natural Language Processing (NLP) to identify patients with delirium symptoms, as defined by an NLP-assisted chart review of the electronic health record (EHR). We used multivariable regression models to examine the associations between delirium symptoms, clinical outcomes, and healthcare utilization, adjusting for patient-, disease-, and transplantation-related factors. Overall, 44.4% (124 of 279) of patients undergoing allogeneic HSCT and 39.0% (87 of 223) of those undergoing autologous HSCT were identified as having delirium symptoms during their index hospitalization. Two-thirds (139 of 211) of the patients with delirium symptoms were prescribed treatment with antipsychotic medications. Among allogeneic HSCT recipients, delirium symptoms were associated with longer hospital length of stay (β = 7.960; P < .001), fewer days alive and out of the hospital (β = -23.669; P < .001), and more intensive care unit admissions (odds ratio, 2.854; P = .002). In autologous HSCT recipients, delirium symptoms were associated with longer hospital length of stay (β = 2.204; P < .001). NLP-assisted EHR review is a feasible approach to identifying hospitalized patients, including HSCT recipients at risk for delirium. Because delirium symptoms are negatively associated with health care utilization during and after HSCT, our findings underscore the need to efficiently identify patients hospitalized for HSCT who are at risk of delirium to improve their outcomes. © 2023 American Society for Transplantation and Cellular Therapy. Published by Elsevier Inc.

Mortality rates in patients with haematological malignancies who required intensive care unit (ICU) admission have in the past been high. More recently, however, improved outcomes for critically ill haematological patients have been reported.

To determine outcomes, average length of ICU stay, and factors associated with mortality in patients with haematological malignancies and neutropenic fever in the multidisciplinary ICU (MICU) at Universitas Academic Hospital (UAH), Bloemfontein, Free State Province, South Africa.

We conducted a retrospective review of medical and laboratory records of all patients admitted to the UAH MICU with haematological malignancies and febrile neutropenia between 2010 and 2019.

A total of 182 patients with haematological malignancies were admitted to the MICU between 1 January 2010 and 31 December 2019, of whom 51 (28.0%) fulfilled the inclusion criteria for the study. The median age was 33 years, and 29 patients (56.9%) were female. Most patients had either acute myeloid leukaemia (n=22; 43.1%) or acute lymphocytic leukaemia (n=16; 31.4%), while B-cell lymphoma (n=12; 23.5%) and multiple myeloma (n=1; 2%) were less frequent. The median length of stay in the ICU was 3 days. ICU mortality was 76.5% and hospital mortality 82.4%. Factors associated with mortality included septic shock, vasoactive agent use and mechanical ventilation.

Patients with haematological malignancies and febrile neutropenia in the UAH MICU have high ICU and hospital mortality rates. More needs to be done with regard to timeous management of patients with haematological malignancies and septic shock in our setting to improve survival.

This is the first study to report on ICU mortality of adult patients with haematological malignancies and neutropenic sepsis in a tertiary hospital ICU in the Free State. These patients had a high mortality rate. What the study adds. Our study shows that septic shock, vasoactive agent use and mechanical ventilation were associated with increased ICU mortality.Implications of the findings. Strict adherence to infection prevention and control measures in haematology wards is required. Early recognition and treatment of sepsis before it progresses to septic shock is important. ICUs must be designed so that isolation cubicles are readily available to prevent cross-infection of patients.

Prognosis of sarcoma patients is improving, with a better understanding of sarcomagenesis revealing novel therapeutic targets. However, aggressive chemotherapy remains an essential part of treatment, bearing the risk of severe side effects that require intensive medical treatment. Available data on the characteristics and clinical outcome of sarcoma patients admitted to intensive care units (ICU) are sparse.

We performed a retrospective analysis of sarcoma patients admitted to the ICU from 2005 to 2022. Patients ≥18 years with histologically proven sarcoma were included in our study.

Sixty-six patients were eligible for analysis. The following characteristics had significant impact on overall survival: sex (p=0.046), tumour localization (p=0.02), therapeutic intention (p=0.02), line of chemotherapy (p<0.001), SAPS II score (p=0.03) and SOFA score (p=0.02).

Our study confirms the predictive relevance of established sepsis and performance scores in sarcoma patients. For overall survival, common clinical characteristics are also of significant value. Further investigation is needed to optimize ICU treatment of sarcoma patients.

Patients with cancer are at risk of multidrug-resistant bacteria colonization, but association of colonization with in-hospital mortality and one-year survival has not been established in critically ill patients with cancer.

Using logistic and Cox-regression analyses adjusted for confounders, in adult patients admitted at intensive care unit (ICU) with active cancer, we evaluate the association of colonization by carbapenem-resistant Gram-negative bacteria or vancomycin-resistant enterococci with in-hospital mortality and one-year survival.

We included 714 patients and among them 140 were colonized (19.6%). Colonized patients more frequently came from ward, had longer hospital length of stay before ICU admission, had unplanned ICU admission, had worse performance status, higher predicted mortality upon ICU admission, and more hematological malignancies than patients without colonization. None of the patients presented conversion of colonization to infection by the same bacteria during hospital stay, but 20.7% presented conversion to infection after hospital discharge. Colonized patients had a higher in-hospital mortality compared to patients without colonization (44.3 vs. 33.4%; p < 0.01), but adjusting for confounders, colonization was not associated with in-hospital mortality [Odds ratio = 1.03 (0.77-1.99)]. Additionally, adjusting for confounders, colonization was not associated with one-year survival [Hazard ratio = 1.10 (0.87-1.40)].

Adult critically ill patients with active cancer and colonized by carbapenem-resistant Gram-negative bacteria or vancomycin-resistant enterococci active cancer have a worse health status compared to patients without colonization. However, adjusting for confounders, colonization by carbapenem-resistant Gram-negative bacteria or vancomycin-resistant enterococci are not associated with in-hospital mortality and one-year survival.

To identify predictors for in-hospital mortality in patients with metastatic cancer in intensive care units (ICUs) and established a prediction model for in-hospital mortality in those patients.

In this cohort study, the data of 2,462 patients with metastatic cancer in ICUs were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. Least absolute shrinkage and selection operator (LASSO) regression analysis was applied to identify the predictors for in-hospital mortality in metastatic cancer patients. Participants were randomly divided into the training set (n = 1,723) and the testing set (n = 739). Patients with metastatic cancer in ICUs from MIMIC-IV were used as the validation set (n = 1,726). The prediction model was constructed in the training set. The area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were employed for measuring the predictive performance of the model. The predictive performance of the model was validated in the testing set and external validation was performed in the validation set.

In total, 656 (26.65%) metastatic cancer patients were dead in hospital. Age, respiratory failure, the sequential organ failure assessment (SOFA) score, the Simplified Acute Physiology Score II (SAPS II) score, glucose, red cell distribution width (RDW) and lactate were predictors for the in-hospital mortality in patients with metastatic cancer in ICUs. The equation of the prediction model was ln(P/(1 + P)) = -5.9830 + 0.0174 × age + 1.3686 × respiratory failure + 0.0537 × SAPS II + 0.0312 × SOFA + 0.1278 × lactate - 0.0026 × glucose + 0.0772 × RDW. The AUCs of the prediction model was 0.797 (95% CI,0.776-0.825) in the training set, 0.778 (95% CI, 0.740-0.817) in the testing set and 0.811 (95% CI, 0.789-0.833) in the validation set. The predictive values of the model in lymphoma, myeloma, brain/spinal cord, lung, liver, peritoneum/pleura, enteroncus and other cancer populations were also assessed.

The prediction model for in-hospital mortality in ICU patients with metastatic cancer exhibited good predictive ability, which might help identify patients with high risk of in-hospital death and provide timely interventions to those patients.

Patients with hematologic malignancies (HMs) have a significantly elevated risk of mortality compared to other cancer patients treated in the intensive care unit (ICU). The prognostic impact of numerous poor outcome indicators has changed, and research has yielded conflicting results. This study aims to determine the ICU and hospital outcomes and risk factors that predict the prognosis of critically ill patients with HMs. In this retrospective study, conducted at a referral hospital in Taiwan, 213 adult patients with HMs who were admitted to the medical ICU were evaluated. We collected clinical data upon hospital and ICU admission. Using a multivariate regression analysis, the predictors of ICU and hospital mortality were assessed. Then, a scoring system (Hospital outcome of critically ill patients with Hematological Malignancies (HHM)) was built to predict hospital outcomes. Most HMs (76.1%) were classified as high grade, and more than one-third of patients experienced a relapsed or refractory disease. The ICU and hospital mortality rates were 55.9% and 71.8%, respectively. Moreover, the disease severity was high (median Sequential Organ Failure Assessment (SOFA) score: 11 and Acute Physiology and Chronic Health Evaluation (APACHE II) score: 28). The multivariate analysis revealed that high-grade HMs, invasive mechanical ventilation requirement, renal replacement therapy initiation in the ICU, and a high SOFA score correlated with ICU mortality. Furthermore, a higher HHM score predicted hospital mortality. This study demonstrates that ICU mortality primarily correlates with the severity of organ dysfunction, whereas the disease status markedly influences hospital outcomes. Furthermore, the HHM score significantly predicts hospital mortality.

There are a diverse range of haematological malignancies with varying clinical presentations and prognoses. Patients with haematological malignancy may require admission to critical care at the time of diagnosis or due to treatment related effects and complications. Although the prognosis for such patients requiring critical care has improved, there remain uncertainties in optimal clinical management. Identification of patients who will benefit from critical care admission is challenging and selective involvement of palliative care may help to reduce unnecessary and non-beneficial treatments. While patients with haematological malignancy can present a challenge to critical care physicians, good outcomes can be achieved. In this narrative review, we provide a brief overview of relevant haematological malignancies for the critical care physician and a summary of recent treatment advances. Subsequently, we focus on critical care management for the patient with haematological malignancy including sepsis; acute respiratory failure; prevention and treatment of tumour lysis syndrome; thrombocytopaenia; and venous thromboembolism. We also discuss immunotherapeutic-specific related complications and their management, including cytokine release syndrome and immune effector cell associated neurotoxicity syndrome associated with chimeric antigen receptor T-cell therapy. While the management of haematological malignancies is highly specialised and increasingly centralised, acutely unwell patients often present to their local hospital with complications requiring critical care expertise. The aim of this review is to provide a contemporary overview of disease and management principles for non-specialist critical care teams.

Although cancer patients are increasingly admitted to the intensive care unit (ICU) for cancer- or treatment-related complications, improved mortality prediction remains a big challenge. This study describes a new ML-based mortality prediction model for critically ill cancer patients admitted to ICU.

We developed CanICU, a machine learning-based 28-day mortality prediction model for adult cancer patients admitted to ICU from Medical Information Mart for Intensive Care (MIMIC) database in the USA (n = 766), Yonsei Cancer Center (YCC, n = 3571), and Samsung Medical Center in Korea (SMC, n = 2563) from 2 January 2008 to 31 December 2017. The accuracy of CanICU was measured using sensitivity, specificity, and area under the receiver operating curve (AUROC).

A total of 6900 patients were included, with a 28-day mortality of 10.2%/12.7%/36.6% and a 1-year mortality of 30.0%/36.6%/58.5% in the YCC, SMC, and MIMIC-III cohort. Nine clinical and laboratory factors were used to construct the classifier using a random forest machine-learning algorithm. CanICU had 96% sensitivity/73% specificity with the area under the receiver operating characteristic (AUROC) of 0.94 for 28-day, showing better performance than current prognostic models, including the Acute Physiology and Chronic Health Evaluation (APACHE) or Sequential Organ Failure Assessment (SOFA) score. Application of CanICU in two external data sets across the countries yielded 79-89% sensitivity, 58-59% specificity, and 0.75-0.78 AUROC for 28-day mortality. The CanICU score was also correlated with one-year mortality with 88-93% specificity.

CanICU offers improved performance for predicting mortality in critically ill cancer patients admitted to ICU. A user-friendly online implementation is available and should be valuable for better mortality risk stratification to allocate ICU care for cancer patients.

The anatomic site for central venous catheter insertion influences the risk of central venous catheter-related intravascular complications. We developed and validated a predictive score of required catheter dwell time to identify critically ill patients at higher risk of intravascular complications.

We retrospectively conducted a cohort study from three multicenter randomized controlled trials enrolling consecutive patients requiring central venous catheterization. The primary outcome was the required catheter dwell time, defined as the period between the first catheter insertion and removal of the last catheter for absence of utility. Predictors were identified in the training cohort (3SITES trial; 2336 patients) through multivariable analyses based on the subdistribution hazard function accounting for death as a competing event. Internal validation was performed in the training cohort by 500 bootstraps to derive the CVC-IN score from robust risk factors. External validation of the CVC-IN score were performed in the testing cohort (CLEAN, and DRESSING2; 2371 patients).

The analysis was restricted to patients requiring mechanical ventilation to comply with model assumptions. Immunosuppression (2 points), high creatinine > 100 micromol/L (2 points), use of vasopressor (1 point), obesity (1 point) and older age (40-59, 1 point; ≥ 60, 2 points) were independently associated with the required catheter dwell time. At day 28, area under the ROC curve for the CVC-IN score was 0.69, 95% confidence interval (CI) [0.66-0.72] in the training cohort and 0.64, 95% CI [0.61-0.66] in the testing cohort. Patients with a CVC-IN score ≥ 4 in the overall cohort had a median required catheter dwell time of 24 days (versus 11 days for CVC-IN score < 4 points). The positive predictive value of a CVC-IN score ≥ 4 was 76.9% for > 7 days required catheter dwell time in the testing cohort.

The CVC-IN score, which can be used for the first catheter, had a modest ability to discriminate required catheter dwell time. Nevertheless, preference of the subclavian site may contribute to limit the risk of intravascular complications, in particular among ventilated patients with high CVC-IN score. Trials Registration NCT01479153, NCT01629550, NCT01189682.

Although short- and long-term survival in critically ill patients with cancer has been described, data on their quality of life (QoL) after an intensive care unit (ICU) stay are scarce. This study aimed to determine the impact of an ICU stay on QoL assessed at 3 months in patients with solid malignancies.

A prospective case-control study was conducted in three French ICUs between February 2020 and February 2021. Adult patients with lung, colorectal, or head and neck cancer who were admitted in the ICU were matched in a 1:2 ratio with patients who were not admitted in the ICU regarding their type of cancer, curative or palliative anticancer treatment, and treatment line. The primary endpoint was the QoL assessed at 3 months from inclusion using the mental and physical components of the Short Form 36 (SF-36) Health Survey. The use of anticancer therapies at 3 months was also evaluated.

In total, 23 surviving ICU cancer patients were matched with 46 non-ICU cancer patients. Four patients in the ICU group did not respond to the questionnaire. The mental component score of the SF-36 was higher in ICU patients than in non-ICU patients: median of 54 (interquartile range: 42-57) vs. 47 (37-52), respectively (p = 0.01). The physical component score of the SF-36 did not differ between groups: 35 (31-47) vs. 42 (34-47) (p = 0.24). In multivariate analysis, no association was found between patient QoL and an ICU stay. A good performance status and a non-metastatic cancer at baseline were independently associated with a higher physical component score. The use of anticancer therapies at 3 months was comparable between the two groups.

In patients with solid malignancies, an ICU stay had no negative impact on QoL at 3 months after discharge when compared with matched non-ICU patients.

A reliable prognostic score for minimizing futile treatments in advanced cancer patients with septic shock is rare. A machine learning (ML) model to classify the risk of advanced cancer patients with septic shock is proposed and compared with the existing scoring systems. A multi-center, retrospective, observational study of the septic shock registry in patients with stage 4 cancer was divided into a training set and a test set in a 7:3 ratio. The primary outcome was 28-day mortality. The best ML model was determined using a stratified 10-fold cross-validation in the training set. A total of 897 patients were included, and the 28-day mortality was 26.4%. The best ML model in the training set was balanced random forest (BRF), with an area under the curve (AUC) of 0.821 to predict 28-day mortality. The AUC of the BRF to predict the 28-day mortality in the test set was 0.859. The AUC of the BRF was significantly higher than those of the Sequential Organ Failure Assessment score and the Acute Physiology and Chronic Health Evaluation II score (both p < 0.001). The ML model outperformed the existing scores for predicting 28-day mortality in stage 4 cancer patients with septic shock. However, further studies are needed to improve the prediction algorithm and to validate it in various countries. This model might support clinicians in real-time to adopt appropriate levels of care.

To analyze clinical features associated to mortality in oncological patients with unplanned admission to the Intensive Care Unit (ICU), and to determine whether such risk factors differ between patients with solid tumors and those with hematological malignancies.

An observational study was carried out.

A total of 123 Intensive Care Units across Spain.

All cancer patients with unscheduled admission due to acute illness related to the background oncological disease.

None.

Demographic parameters, severity scores and clinical condition were assessed, and mortality was analyzed. Multivariate binary logistic regression analysis was performed.

A total of 482 patients were included: solid cancer (n=311) and hematological malignancy (n=171). Multivariate regression analysis showed the factors independently associated to ICU mortality to be the APACHE II score (OR 1.102; 95% CI 1.064-1.143), medical admission (OR 3.587; 95% CI 1.327-9.701), lung cancer (OR 2.98; 95% CI 1.48-5.99) and mechanical ventilation after the first 24h of ICU stay (OR 2.27; 95% CI 1.09-4.73), whereas no need for mechanical ventilation was identified as a protective factor (OR 0.15; 95% CI 0.09-0.28). In solid cancer patients, the APACHE II score, medical admission, antibiotics in the previous 48h and lung cancer were identified as independent mortality indicators, while no need for mechanical ventilation was identified as a protective factor. In the multivariate analysis, the APACHE II score and mechanical ventilation after 24h of ICU stay were independently associated to mortality in hematological cancer patients, while no need for mechanical ventilation was identified as a protective factor. Neutropenia was not identified as an independent mortality predictor in either the total cohort or in the two subgroups.

The risk factors associated to mortality did not differ significantly between patients with solid cancers and those with hematological malignancies. Delayed intubation in patients requiring mechanical ventilation might be associated to ICU mortality.

There is still not a mortality prediction model built for breast cancer admitted to intensive care unit (ICU).

We aimed to build a prognostic model with comprehensive data achieved from eICU database.

Outcome was defined as all-cause in-hospital mortality. Least absolute shrinkage and selection operator (LASSO) was conducted to select important variables which were then taken into logistic regression to build the model. Bootstrap method was then conducted for internal validation.

448 patients were included in this study and 79 (17.6%) died in hospital. Only 5 items were included in the model and the area under the curve (AUC) was 0.844 (95% confidence interval [CI]: 0.804-0.884). Calibration curve and Brier score (0.111, 95% CI: 0.090-0.127) showed good calibration of the model. After internal validation, corrected AUC and Brier score were 0.834 and 0.116. Decision curve analysis (DCA) also showed effective clinical use of the model. The model can be easily assessed on website of https://breastcancer123.shinyapps.io/BreastCancerICU/.

The model derived in this study can provide an accurate prognosis for breast cancer admitted to ICU easily, which can help better clinical management.

Our aim was to assess impact of frailty on short-term clinical outcomes in critically ill patients with cancer.

We conducted a cohort study at a medical and surgical intensive care unit (ICU) in Argentina. We included 269 consecutive patients, ≥18 years old, with diagnosis of cancer. We recorded demographic and clinical characteristics, Clinical Frailty Scale (CFS, ≥5 defined a patient as frail), and the number and duration of organ support therapies during ICU stay. Primary outcome was ICU and hospital mortality.

Median age 69 (range 20-90); 152 (56%) patients were male. Sixty-eight (25.2%) patients presented frailty at admission. Older adults (≥65 years old) made up 62.8% of patients. Frail patients were 69.7 years versus 64.4 years for non-frail, P = 0.007, with higher Acute Physiology and Chronic Health Evaluation II (APACHE II) 14.7 ± 7 versus 10.8 ± 6, P = 0.001 and Simplified Acute Physiology Score (SAPS II) 40.1 ± 17 versus 28.7 ± 14, P = 0.001, respectively. After adjusting by age, severity score, type of admission, and type of cancer, frailty was independently associated with hospital mortality, odds ratio (OR) 4.87 (95% confidence interval [CI], 2.19-11.19, P ≤0.001). Median ICU length of stay was five days (interquartile range [IQR] 3-7) versus six days (IQR 3.8-9), in non-frail versus frail patients, respectively (P = 0.100), and hospital stay was nine days (IQR 6-17) versus 11.5 days (IQR 7-19.5) in non-frail versus frail patients, respectively (P = 0.085).

Frailty as a medical condition was strongly associated with worse clinical outcomes among oncologic critically ill patients.