To compare the performance of machine learning and logistic regression algorithms in predicting emergence delirium (ED) in elderly patients.

A prospective study was carried out in a Chinese teaching tertiary hospital and collected the details of 1045 patients who underwent noncardiac surgery with general anesthesia. Characteristic variables related to ED were selected by least absolute shrinkage and selection operator (LASSO). Finally, seven machine learning models (gradient boosting machine, extreme gradient boosting, light gradient boosting machine, support vector machine, decision tree, neural network, and random forest) and logistic regression were used in the training set, and the predictive performance of the models was validated in the test set.

ED was identified in 316 (30.2%) patients. The logistic regression model performed better than the machine learning models (area under the curve [AUC] of 0.790, 95% confidence interval [CI] 0.736-0.843). Besides, the calibration curve indicated good consistency between predicted and actual ED probabilities, and decision curve analysis demonstrated that the logistic regression model could bring clinical benefits.

The optimal application of logistic regression can provide rapid and efficient risk prediction of ED for medical workers so that reasonable prevention and treatment measures can be taken.

To refine and validate an electronic version of the Aggressive Behaviour Risk Assessment Tool (ABRAT) and determine the sensitivity and specificity for identifying potentially violent patients in non-psychiatric inpatient units.

A prospective cohort study design was used.

All patients admitted or transferred to three inpatient units of an acute care hospital in Nebraska, USA, from 7 February to 9 April 2023, were included. The 10-item ABRAT assessments were performed daily for the first 3 days of admission. The violent events were collected until discharge in three categories: Physical aggression towards others, physical aggression towards property and verbal intimidation/threat towards others. Kendall's tau tests and a multivariate logistic regression procedure were performed to select a parsimonious set of items that best predict violent events.

Of 1179 patients, 69 had ≥1 violent event (5.9%). The revised six-item tool with item weighting was named ABRAT for Hospitalised Patients (ABRAT-H). The area under the curve from the Receiver Operating Characteristics analysis was 0.82. The sensitivity and specificity at a cutoff score of two were 68.1% and 85.2%, respectively. As ABRAT-H scores increased, the percentage of violent patients also increased and for patients with scores ≥5, 55.2% became violent.

ABRAT-H appears to be useful for identifying potentially violent patients in non-psychiatric inpatient units with satisfactory sensitivity and specificity.

The availability of ABRAT-H may help provide focused preventive measures that target patients at high risk for violence and reduce violent events.

A majority of the nursing workforce is employed in acute care hospital setting, and the availability of ABRAT-H can further enhance the culture of a safe work environment and have positive impacts not only on the nurses' physical and mental health but also on the quality of patient care.

We have adhered to relevant STROBE guidelines for reporting observational studies.

No Patient or Public Contribution.

Delirium is a common issue in critical care, yet its prevention and management strategies are often inconsistent. Understanding the factors that lead to the omission or delay in delirium-related care by critical care nurses is essential for enhancing patient outcomes.

This study aimed to identify the specific delirium-related prevention and management strategies that are frequently missed or delayed by critical care nurses. It also explored factors influencing nurses' prioritisation of care, including delirium-related strategies.

A mixed-method approach was utilised, combining quantitative data from online surveys and qualitative insights from interviews with critical care nurses in a Canadian health authority. The Missed Nursing Care Survey identified instances of missed or delayed care, while interviews provided deeper insights into care prioritisation decisions.

Quantitative findings indicated frequent delays in patient mobilisation and physical care that were attributed to staffing shortages, high patient volume, and increased admissions and discharges. Qualitative findings revealed that factors such as patient acuity, structured routines, knowledge gaps, limited support, unit culture, and resource inadequacies influenced the prioritisation of delirium-related care, often leading to its inadvertent deprioritisation.

This study underscores the need to integrate delirium care into patient acuity assessments and establish sustainable education programs to enhance the recognition and prioritisation of delirium by critical care nurses. Addressing these factors is critical for improving patient outcomes in critical care settings.

Strengthening critical care nurses' capacity to consistently recognise and prioritise delirium-related care through targeted education and system-level support could potentially contribute to better patient outcomes.

 Chronic subdural hematoma (cSDH) is a common neurosurgical condition of growing importance due to the aging population and increasing use of antithrombotic agents. Due to the lack of guidelines, great variability is observed in the treatment of cSDH. We conducted a multicenter, nationwide survey to assess the differences in treatment across Germany in the context of surgical practices discussed in the literature.

 A web-based survey was designed using the REDCap electronic data capture tool hosted at the Charité - Universitätsmedizin Berlin. The survey was divided into four parts: preoperative management and indication for surgery, perioperative management of medication, surgical technique, and postoperative management. The survey was distributed to German neurosurgical departments through the newsletter of the German Society of Neurosurgery and direct e-mail contact and could be answered by one member of each department between March 1 and May 31, 2023.

 Overall, representatives of 46 German neurosurgical departments completed the survey. Participants needed a mean time of 16:25 minutes (standard deviation [SD] ± 27:47 minutes) to complete the survey. The mean caseload of the participating departments was 1,831.5 (range: 300-6,000; SD ± 1,130.7) operations per year, including 87.8 procedures for cSDH (range: 15-300; SD ± 73.6). Evidence found in the literature regarding the performance of a burr hole craniotomy, use of a drain, passive drainage, removal of the drain 48 hours after surgery, and early mobilization after surgery was consistently implemented in the management of the surveyed departments. On the contrary, recommendations regarding the performance of surgery under local anesthesia, use of subgaleal drains, postoperative Valsalva maneuvers, and avoidance of postoperative computed tomography (CT) if possible were not universally implemented.

 This survey indicates that there is no consensus on the treatment of cSDH in Germany and that the steadily increasing evidence from clinical trials must be implemented in national and international guidelines. The development of tailored treatment strategies for older patients with multiple risk factors and comorbidities is of particular importance.

Delirium, acute brain dysfunction, is present in 10% to 35% of older adults in the emergency department (ED) but unrecognized in ∼80% of cases leading to significant adverse outcomes. Thus, routine screening for delirium is vital to improve prevention and management in the ED. The treatment of delirium focuses on addressing the underlying cause. For agitation, nonpharmacologic measures using the Tolerate, Anticipate, and Don't Agitate (TADA) approach and the Assess, Diagnose, Evaluate, Prevent, and Treat (ADEPT) tool are prioritized for management. If unsuccessful, only the lowest effective dose of pharmacologic agents (atypical antipsychotics) should be used for severe symptom control.

In this study, Pinto et al. identified significantly higher levels of neuron-specific enolase and Tau protein in older patients with sepsis-associated delirium in the emergency department, suggesting the potential of these biomarkers as diagnostic tools in this population.

Sepsis-associated delirium is a common cerebral manifestation in patients with sepsis, potentially caused by a combination of neuroinflammation and other neurophysiological disorders. This study investigated the expression of neuron-specific enolase and Tau protein as biomarkers in patients with sepsis-associated delirium. While neuron-specific enolase and Tau protein are known to be associated with brain injury, their diagnostic potential in patients with sepsis-associated delirium is not well understood.

This cross-sectional pilot study evaluated plasma levels of neuron-specific enolase and Tau protein in patients with delirium and sepsis to explore their potential for identifying sepsis in patients admitted to the emergency department.

A total of 25 patients with delirium were analyzed, 56% of whom had sepsis. Patients with sepsis exhibited significantly higher neuron-specific enolase levels (2.7ng/mL [95%CI= 2.2-3.2] versus 1.3 ng/mL [95%CI= 0.8-2.5], p<0.003) and Tau protein levels (96.1pg/mL [95%CI= 77.0-111.3] versus 43.0pg/mL [95%CI= 31.2-84.5], p<0.003) compared to patients without sepsis. Neuron-specific enolase and Tau protein thresholds of >2.08ng/mL and >59.27pg/mL, respectively, demonstrated 90% specificity for identifying sepsis in patients.

Neuron-specific enolase and Tau protein levels were significantly higher in patients with sepsis than in those without, underscoring their potential ability to identify the infectious etiology of delirium in older patients admitted to emergency departments. Clinical Trials #RBR-233bct.

■ Biomarkers of brain injury, such as neuron-specific enolase and Tau proteins, are higher in older patients with sepsis and delirium.

■ Diagnosing sepsis in patients with delirium can be challenging.

■ Early identification of sepsis is key to managing sepsisassociated delirium.

Delirium in intensive care unit (ICU) patients poses a significant challenge, affecting patient outcomes and health care efficiency. Developing an accurate, real-time prediction model for delirium represents an advancement in critical care, addressing needs for timely intervention and resource optimization in ICUs.

We aimed to create a novel machine learning model for delirium prediction in ICU patients using only continuous physiological data.

We developed models integrating routinely available clinical data, such as age, sex, and patient monitoring device outputs, to ensure practicality and adaptability in diverse clinical settings. To confirm the reliability of delirium determination records, we prospectively collected results of Confusion Assessment Method for the ICU (CAM-ICU) evaluations performed by qualified investigators from May 17, 2021, to December 23, 2022, determining Cohen κ coefficients. Participants were included in the study if they were aged ≥18 years at ICU admission, had delirium evaluations using the CAM-ICU, and had data collected for at least 4 hours before delirium diagnosis or nondiagnosis. The development cohort from Yongin Severance Hospital (March 1, 2020, to January 12, 2022) comprised 5478 records: 5129 (93.62%) records from 651 patients for training and 349 (6.37%) records from 163 patients for internal validation. For temporal validation, we used 4438 records from the same hospital (January 28, 2022, to December 31, 2022) to reflect potential seasonal variations. External validation was performed using data from 670 patients at Ajou University Hospital (March 2022 to September 2022). We evaluated machine learning algorithms (random forest [RF], extra-trees classifier, and light gradient boosting machine) and selected the RF model as the final model based on its performance. To confirm clinical utility, a decision curve analysis and temporal pattern for model prediction during the ICU stay were performed.

The κ coefficient between labels generated by ICU nurses and prospectively verified by qualified researchers was 0.81, indicating reliable CAM-ICU results. Our final model showed robust performance in internal validation (area under the receiver operating characteristic curve [AUROC]: 0.82; area under the precision-recall curve [AUPRC]: 0.62) and maintained its accuracy in temporal validation (AUROC: 0.73; AUPRC: 0.85). External validation supported its effectiveness (AUROC: 0.84; AUPRC: 0.77). Decision curve analysis showed a positive net benefit at all thresholds, and the temporal pattern analysis showed a gradual increase in the model scores as the actual delirium diagnosis time approached.

We developed a machine learning model for delirium prediction in ICU patients using routinely measured variables, including physiological waveforms. Our study demonstrates the potential of the RF model in predicting delirium, with consistent performance across various validation scenarios. The model uses noninvasive variables, making it applicable to a wide range of ICU patients, with minimal additional risk.

Cerebrospinal fluid Aβ42 has been proposed as a potential indicator for cerebral β-amyloidosis and may be involved in the pathophysiology of delirium. Whether perioperative plasma Aβ42 alternation is associated with postoperative delirium risk among elderly patients remains unknown.

This was a secondary analysis of a randomized controlled trial evaluating the effects of acupuncture (intervention) compared to standard care (control) on the incidence of delirium in patients undergoing major abdominal surgery. Participants with blood samples collected were included in this cohort study. The exposure variable was the Aβ42 ratio, calculated with the plasma Aβ42 level immediately after surgery divided by the preoperative plasma Aβ42 level. The primary endpoint was the occurrence of delirium within the first 7 days following surgery or until hospital discharge, whichever happened first, evaluated using either the Confusion Assessment Method or the Confusion Assessment Method-intensive care unit for intubated patients. Delirium severity was a secondary outcome assessed by the Memorial Delirium Assessment Scale. The logistic regression models and a restricted cubic spline were performed to examine the association between the Aβ42 ratio and delirium incidence, with receiver operating characteristic curve (ROC) analysis for diagnostic power. The mediation effects of the matrix metalloproteinase-9 ratio were further explored by causal mediation analysis. The linear regression and generalized linear mixed models assessed the association between the Aβ42 ratio and delirium severity.

A total of 195 patients with blood samples collected were included in the final analysis. Among them, the mean age was 70.2 ± 4.2 years; 134 were female (68.7%), and 26 (13.3%) patients experienced postoperative delirium. The plasma Aβ42 ratio was positively correlated with an increased delirium risk (adjusted odds ratio 3.21, 95% confidence interval 1.71-6.05, p < 0.001) and delirium severity, as measured by the highest postoperative Memorial Delirium Assessment Scale score (adjusted β coefficient 3.04, 95% confidence interval 0.9-5.18, p = 0.006) in the fully adjusted multivariable analysis models. The restricted cubic spline indicated a linear relationship between the plasma Aβ42 ratio and delirium incidence (p = 0.202). The ROC showed that the area under the curve for the Aβ42 ratio to predict delirium risk was 0.698 (95% CI, 0.582-0.814), with the optimal cut-off point of 0.137. Mediation analyses showed that the Aβ42 ratio does not mediate postoperative delirium through the matrix metalloproteinase-9 ratio (proportion: 1.3%).

This cohort study showed that a higher Aβ42 ratio was associated with an increased delirium risk and severity, and the association was linear. The plasma Aβ42 ratio might be a mini-invasive biomarker to identify postoperative delirium.

Hospitalized elderly patients frequently suffer from delirium, especially in the context of sepsis-associated encephalopathy. Current treatments of delirium are merely symptomatic. Calorie restriction (CR) is both a promising strategy to protect against sepsis and has beneficial effects on aging-induced neurodegeneration. In this study, we investigated whether six weeks of 30% CR had protective effects on lipopolysaccharide (LPS) induced (neuro)inflammation in wild-type (WT) and progeroid mice deficient in the DNA excision-repair gene Ercc1 (Ercc1Δ/-). While CR did not affect the LPS-induced inflammatory response in WT mice, CR exaggerated the peripheral inflammatory response in Ercc1Δ/- mice, as evidenced by an increase of pro-inflammatory serum cytokines (TNF-α, IL-1β, and IFN-γ) and kidney injury marker Ngal. Neuroinflammatory effects were assessed by RNA-sequencing of isolated microglia. Similarly, CR did not affect microglia gene expression in WT mice, but increased neuroinflammation-associated gene expression in Ercc1Δ/- mice. In conclusion, CR increases the peripheral and brain inflammatory response of Ercc1Δ/- mice to a systemic inflammatory stimulus.

Postoperative delirium (POD) is generally associated with increased postoperative adverse events. We aimed to investigate whether preoperative quantitative quadriceps muscle ultrasound could predict POD in older patients after gastrointestinal surgery in order to provide more targeted prevention and treatment measures.

We prospectively collected data from elderly patients who underwent elective gastrointestinal surgery from August to December 2023 at a tertiary hospital in China. Intergroup difference analysis and univariate and multivariate logistic regression analyses were used to explore independent risk factors. We calculated and assessed the parameters via sensitivity, specificity, the Youden index, and the area under the receiver operating characteristic curve (AUC), calibration curves and the Hosmer-Lemeshow test. The nomogram was validated internally through bootstrap resampling. The decision curve analysis (DCA) was used to evaluate its clinical validity.

A total of 695 patients who underwent gastrointestinal surgery were analyzed in this investigation, among which 137 patients experienced POD with an incidence rate of 19.7%. After conducting multivariate logistic regression analyses using R software, six independent risk factors associated with POD were identified, including age, quadriceps muscle thickness (Q-MT), quadriceps echo intensity (Q-EI), Charlson Comorbidity Index (CCI), preoperative frailty and preoperative Minimum Mental State Examination (MMSE) scores. The AUC value of the model was 0.966 (95% CI: 0.950-0.982; p < 0.05). The calibration curve revealed that the predicted probability of the nomogram was consistent with the actual probability, and the Hosmer-Lemeshow goodness-of-fit test value was 0.811. DCA revealed that the nomogram has a net benefit for POD.

Quantitative quadriceps ultrasound parameters, including the Q-MT and Q-EI, could predict POD after gastrointestinal surgery in older patients. We have developed a new nomogram for predicting POD in older patients who undergo gastrointestinal surgery.

The trial was registered in the Chinese Clinical Trial Registry ( http://www.chictr.org.cn/ ) on August 3, 2023, with the registration number of ChiCTR2300074304.

Delirium is an acute fluctuating impairment of attention and awareness, common in acute ischemic stroke (AIS). This study aimed to evaluate the prognostic significance of delirium for neurological function at 3 months post-stroke, and develop a predictive model integrating delirium and biomarkers to enhance prognostic accuracy.

We conducted a prospective cohort study of patients admitted to the stroke unit (n=722). All patients were screened for daily delirium during clinical care. Plasma biomarkers were measured within 24 hours after admission. The main outcomes were evaluated with the 3-months modified Rankin Scale (mRS).

Delirium developed in 10.2% of patients during the acute phase of stroke. Patients with post-stroke delirium (PSD) was significantly older (median age 74 vs 68 years, P<0.001), more likely to have pre-stroke cognitive impairment (14.9% vs 4.8%, P=0.001), a higher prevalence of cardiovascular history (35.1% vs 16.2%, P<0.001). PSD was also associated with higher scores of NIHSS (14.3 vs 9.1, P<0.001) and greater scores of mRS (3.0 vs 1.5, P<0.001) at admission. PSD patients showed worse outcomes, with elevated NIHSS and mRS scores at discharge and 3-month follow-up, as well as higher mortality rates (5.4% vs 1.4%, P=0.025). Biomarker analysis revealed increased plasma levels of inflammatory (white blood cells, neutrophils, C-reactive protein) and coagulation biomarkers (fibrinogen, D-dimer) in PSD patients, particularly those with poorer outcomes (P<0.01). Our model, which incorporated delirium and biomarkers of inflammation and coagulation dysfunction, demonstrated strong predictive accuracy for adverse outcomes at 3 months with an AUC of 0.779 (95% CI=0.736-0.822), with clinical utility confirmed by decision curve analysis.

PSD is a strong independent predictor of poor 3-month outcomes in AIS, including higher mortality and disability. Our findings highlight the critical role of inflammation and coagulation dysfunction in the pathogenesis of PSD. Furthermore, we present the clinical utility of a predictive model integrating delirium and relevant biomarkers to assess the risk of adverse outcomes at 3 months, suggesting potential targets for intervention.

Postoperative delirium, a common neurocognitive complication after surgery and anesthesia, requires early detection for potential intervention. Herein, we constructed a multidimensional postoperative delirium risk-prediction model incorporating multiple demographic parameters and blood biomarkers to enhance prediction accuracy.

We included 555 patients undergoing radical surgery for colorectal cancer. Demographic characteristics and lipid profiles were collected preoperatively, and perioperative anesthesia and surgical conditions were recorded; blood biomarkers were measured before and after surgery. The 3D-CAM scale was used to assess postoperative delirium occurrence within 3 days after surgery. Patients were divided into the postoperative delirium (N = 100) and non-postoperative delirium (N = 455) groups. Based on machine learning, linear and nine non-linear models were developed and compared to select the optimal model. Shapley value-interpretation methods and mediation analysis were used to assess feature importance and interaction.

The median age of the participants was 65 years (interquartile range: 56-71 years; 57.8% male). Among the 10 machine-learning models, the random forest model performed the best (validation cohort, area under the receiver operating characteristic curve of 0.795 [0.704-0.885]). Lipid profile (total cholesterol, triglycerides, and trimethylamine-N-oxide) levels were identified as key postoperative delirium predictors. Mediation analysis further confirmed mediating effects among total cholesterol, trimethylamine-N-oxide, and postoperative delirium; a nomogram model was developed as a web-based tool for external validation and use by other clinicians.

Blood biomarkers are crucial in predicting postoperative delirium and aid anesthesiologists in identifying its risks in a timely manner. This model facilitates personalized perioperative management and reduces the occurrence of postoperative delirium.

ChiCTR2300075723.

Analyze the risk factors for postoperative delirium (POD) in elderly patients undergoing radical prostatectomy, and built a predictive nomogram model for early identification of high-risk individuals.

A total of 156 patients was recruited and categorized based on whether the development of POD within 7 days post-surgery. After identifying independent risk factors through univariate and multivariate logistic regression analyses, predictive models were established. The discrimination and calibration were determined by C-index and calibration curve, with five-fold cross-validation executed. A nomogram model representing the optimal model was constructed based on the results.

POD occurred in 24 (15.38%) patients. Significant differences were observed in age, anxiety, physical status, sleep disorders, blood glucose, age-adjusted Charlson comorbidity index (ACCI), anticholinergic, blood loss, postoperative infection, and postoperative pain assessed by the numerical rating scale (NRS). Logistic regression analyses showed that sleep disorders (OR:12.931, 95% CI:1.191-140.351, P = 0.035), ACCI (OR:2.608, 95% CI:1.143-5.950, P = 0.023), postoperative infection (OR:19.298, 95% CI:2.53-147.202, P = 0.04), and NRS (OR:4.033, 95% CI:1.062-15.324, P = 0.041) were independent risk factors for POD. Model 1 (postoperative infection, ACCI, preoperative sleep disorder, NRS) showed better diagnostic performance than the others, of which the area under the curve (AUC) was 0.973. The best diagnostic performance was found in model 1 through five-fold cross-validation, with a C-index of 0.963.

This prospective cohort study highlighted that ACCI, preoperative sleep disorder, postoperative pain, and postoperative infection were identified as independent risk factors for POD. Furthermore, the nomogram derived from model 1 proved to be effective in predicting POD in elderly patients undergoing radical prostatectomy.

This study aims to evaluate the diagnostic accuracy of significant intraoperative neurophysiological monitoring (IONM) changes as an independent predictor of postoperative delirium (POD) in patients undergoing aneurysm clipping.

IONM and clinical data from 273 patients who underwent craniotomy for aneurysm clipping from 2019 until 2021 were retrospectively reviewed. Significant IONM changes and POD were respectively evaluated based on visual review of data and clinical documentation. POD was assessed multiple times in the ICU using the Intensive Care Delirium Screening Checklist (ICDSC).

Of the 273 patients undergoing craniotomy with IONM, 83 had POD (30.4 %). Significant IONM changes were noted in 42 patients, of which 19 patients had POD (45.2 %). In contrast, 231 patients had no IONM changes during surgery, of which 64 (27.7 %) patients had POD. Multivariable analysis showed that significant IONM changes were associated with POD, OR: 2.09 (95 % CI 1.01-4.43, p-value: 0.046). Additionally, somatosensory evoked potentials (SSEP) changes were significantly associated with POD (p-value: 0.044).

Significant IONM changes are associated with an increased risk of POD in patients undergoing craniotomy for aneurysm clipping. Our findings offer a strong basis for future research and analysis of EEG and SSEP monitoring to detect and possibly prevent POD.

Ascorbic acid is a strong antioxidant that prevents postoperative delirium by inhibiting reactive oxygen species production. This pilot study was designed to investigate the prevalence of postoperative delirium among older patients undergoing cardiovascular surgery, who received perioperative ascorbic acid administration, to estimate an appropriate sample size for further randomized controlled trials.

This single-arm prospective interventional study enrolled patients aged > 70 years scheduled to undergo elective cardiovascular surgery using cardiopulmonary bypass. Ascorbic acid (500 mg) was administered intravenously every 6 h for a total of eight times following the induction of general anesthesia. The incidence of postoperative delirium was evaluated until discharge using the Confusion Assessment Method for the Intensive Care Unit.

Data from 48 patients were analyzed. Of the 48 patients, 16 developed postoperative delirium (33.3%). Patients in the delirium group had more severe heart failure (New York Heart Association Classification), higher European System for Cardiac Operative Risk Evaluation scores, lower intraoperative Bispectral Index, longer duration of cardiopulmonary bypass and surgery, incidence of postoperative cerebral infarction, longer intubation time, and length of intensive care unit stay.

The incidence of postoperative delirium among older patients undergoing cardiovascular surgery who received ascorbic acid perioperatively (2 g/day for 2 days) was 33%. This incidence was comparable to that observed in a previous observational study, suggesting that ascorbic acid administration may not be effective in preventing the incidence of postoperative delirium.

Postoperative delirium (POD) is a prevalent complication following cardiac surgery, characterized by acute brain dysfunction observed in critically ill patients. Despite the significant impact of POD, there is currently no established treatment. Recent research has suggested that modulation of cholinergic neurotransmission and α2-adrenergic receptors may offer a therapeutic strategy for managing delirium during critical illness. This study employs bibliometric analysis to examine the emerging evidence on the role of dexmedetomidine, an α2-receptor agonist drug, in the prevention and treatment of POD. A systematic bibliometric analysis was conducted to identify and evaluate the literature on the use of dexmedetomidine in relation to POD. The study period spanned from 2006 to 2022, and the search was conducted in the Web of Science (WOS) database, focusing on relevant references. The analysis included the examination of the most frequent keywords, research trends, and frontiers to provide a comprehensive overview of the field. The bibliometric analysis revealed 160 research papers on the topic, indicating a significant increase in research output over the past decades. The field distribution, knowledge structure, and research topic evolution were identified as key areas of exploration. The analysis also highlighted the emergence of new topics and trends in the study of POD and its management. This bibliometric analysis provides a robust framework for understanding the current state of research on dexmedetomidine's efficacy in managing POD. It highlights the need for continued investigation and underscores the potential of this pharmacological approach to improve patient outcomes following cardiac surgery.

To compare the POD rates in patients undergoing non-cardiac surgery who received remimazolam perioperatively versus placebo or other sedatives.

We systematically searched four major databases (Cochrane Central Register of Controlled Trials, Web of Science, Embase, and PubMed) for relevant randomized controlled trials (RCTs) up to July 11, 2024. Literature quality evaluation was used the bias risk table in Review Manager 5.4. The primary outcome of interest was POD, and secondary outcomes were the hypotension risk, bradycardia and, nausea and vomiting.

Across 11 trials involving 1985 participants, we recorded 309 cases of POD during follow-up. In trials where the control group received saline, remimazolam decrease the risk of POD significantly by 70% (RR 0.30, 95% CI [0.19, 0.46]; p < 0.00001). Statistical analysis did not show significant difference in the risk of POD between the remimazolam group and the groups receiving either dexmedetomidine (RR 1.23 [0.64, 2.37]; p = 0.53) or propofol (RR 0.83 [0.60, 1.16]; p = 0.28). Regarding adverse events, remimazolam significantly reduces the morbidity of hypotension compared to dexmedetomidine (RR 0.25 [0.10, 0.65]; p = 0.004) and propofol (RR 0.45 [0.33, 0.60]; p < 0.00001). In addition, there were no significant differences in the incidence of bradycardia (RR 0.85; 95% CI [0.34-2.12], p = 0.72) and nausea and vomiting (RR 1.06; 95% CI [0.74-1.51], p = 0.77) between remimazolam and the control group.

During the perioperative period, using remimazolam can lower POD risk after surgery for patients who had non-cardiac surgery, but remimazolam does not work better than dexmedetomidine or propofol. Compared with the dexmedetomidine and propofol, remimazolam also has apparent advantages in preventing intraoperative hypotension.

Postoperative delirium (POD) is a common postoperative complication and is associated with numerous adverse outcomes. Advanced age and hip surgery are high risk factors for POD. Both remimazolam tosilate for injection and sevoflurane can be used as sedatives for the maintenance of general anesthesia, but the comparison of their impacts on the incidence of POD has not been reported. This study aims to compare the effect of remimazolam tosilate vernus sevoflurane on the incidence of POD in older patients undergoing total hip arthroplasty.

This is a two-arm, parallel, prospective, multicenter, randomized controlled trial. A total of 456 older patients at six clinical trial centers in China will be randomly assigned in a 1:1 ratio to receive general anesthesia with remimazolam tosilate or sevoflurane as sedative. The primary outcome measure is the prevalence of POD during the first 4 postoperative days. Secondary outcomes include cognitive function [Mini-Mental State Examination (MMSE)], perioperative pain degree [Visual Analogue Scale (VAS)], postoperative nausea and vomiting (PONV) within 4 days after surgery, recovery time after drug withdrawal, the amount of vasoactive drugs used during operation, length of hospital stay, and in-hospital complications.

The Research Ethics Committee of Qilu Hospital of Shandong University has approved the study protocol (REF: KYLL-202206-25), which is applicable to all research centers. Participant recruitment begins in August 2022. Written informed consent will be obtained from each patient before randomization. The findings will be published in an international peer-reviewed medical journal.

The trial has been registered at the Chinese Clinical Trial Registry: ChiCTR2200062455; date of registration: 2022-08-08.

Delirium is a common and distressing mental disorder in palliative care. To date, no delirium prediction model is available for thepalliative care population. The research aimed to develop and validate a nomogram model for predicting the occurrence of delirium in advanced cancer patients admitted to palliative care units.

This was a prospective, multicenter, observational study. Logistic regression was used to identify the independent risk factors for incident delirium among advanced cancer patients in palliative care units. Advanced cancer patients admitted to palliative care units between February 2021 and January 2023 were recruited from four hospitals in Chengdu, Sichuan Province, China. Model performance was evaluated via the area under the receiver operating characteristic curve, calibration plots and decision curve analysis.

There were 592 advanced cancer patients receiving palliative care in the development cohort, 196 in the temporal validation cohort and 65 in the external validation cohort. The final nomogram model included 8 variables (age, the Charlson comorbidity index, cognitive function, the Barthel index, bilirubin, sodium, the opioid morphine equivalent dose and the use of anticholinergic drugs). The model revealed good performance in terms of discrimination, calibration, and clinical practicability, with an area under the receiver operating characteristic curve of 0.846 in the training set, 0.838 after bootstrapping, 0.829 in the temporal validation and 0.803 in the external validation set.

The model serves as a reliable tool to predict delirium onset for advanced cancer patients in palliative care units, which will facilitate early targeted preventive measures to reduce the burden of delirium.

To explore the risk factors related to perioperative neurocognitive disorders (PND) in elderly patients with hip fractures, with perioperative acute pain management as the core. This study used a retrospective case-control study method. 90 elderly patients who underwent artificial femoral head replacement or total hip replacement surgery in our hospital from 2022 to 2023 were collected, and divided into PND group and non-PND group based on the occurrence of PND. Collected data on 17 factors and conducted univariate and multivariate regression analysis to analyze the risk factors and contribution value of PND in elderly patients with hip fractures. Univariate analysis showed that compared with the non-PND group, patients in the PND group showed a significant increase in age, higher ASA class, longer surgical time, increased number of nerve block cases, increased postoperative 12 h visual analogue scale (VAS) scores, increased postoperative 24 h VAS scores, and increased levels of CRP, PCT, and BL-6 (P < 0.05). Multivariate regression analysis found that the risk factors for PND were postoperative 12 h VAS scores, postoperative 24 h VAS scores, CRP, PCT, and BL-6. The protective factors were ASA class III and ASA class II. The risk factors for PND in elderly patients undergoing hip fracture surgery included postoperative 12 h VAS scores (OR = 3.356), postoperative 24 h VAS scores (OR = 2.311), CRP (OR = 1.058), PCT (OR = 18.661), and BL-6 (OR = 1.061). The protective factors were ASA class III (OR = 0.039) and ASA class II (OR = 0.016).

Inpatient delirium and unplanned hospital readmissions are associated with increased mortality. This study aimed to determine the effect of 28-day unplanned hospital readmissions on 12-month mortality post-discharge in patients with delirium during index hospitalisation.

Retrospective longitudinal cohort study of adults aged 65 or above with delirium during hospitalisation at a Victorian quaternary hospital was performed. Delirium was identified by the inclusion of ICD-10 (International Classification of Diseases, 10th revision) codes in the hospital medical discharge summary. Descriptive statistics was obtained for baseline characteristics. Cox proportional hazards model was developed to identify independent predictors of 12-month post-discharge mortality.

One thousand six hundred thirty-four patients with delirium during in-patient admission were included. The overall 12-month mortality rate was 35% (572 patients). Of the 1,425 patients who survived their index admission, 11.2% had an unplanned 28-day readmission. In Cox regression analysis, unplanned readmission (hazard ratio (HR) 2.3, 95% confidence internal (CI) 1.7-2.9), older age (HR 1.38, CI 1.11-1.72), Charlson Comorbidity Index (HR 1.21, CI 1.17-1.27), and discharge to nursing home (HR 1.58, CI 1.23-2.02) were independent predictors of 12-month mortality. Readmitted patients with 12-month mortality were older, with higher rates of dementia, polypharmacy, and nursing home residence compared to readmitted patients who did not reach this endpoint.

Unplanned hospital readmission within 28 days of discharge is an independent predictor of 12-month mortality post in-hospital delirium admission. Admissions complicated by delirium and readmission episodes should instigate discussions regarding prognostication and goals of care. Greater research is required to minimise hospital readmission rates following discharge in this cohort.

Brain energy metabolism disorders, including glucose utilization disorders and abnormal insulin sensitivity, are linked to the pathogenesis of postoperative delirium. Intranasal insulin has shown significant benefits in improving glucose metabolism, insulin sensitivity and cognitive function. However, its impact on postoperative delirium and insulin sensitivity biomarkers remains unknown.

This randomized, double-blind, placebo-controlled trial was to evaluate whether intranasal insulin reduces the incidence and severity of postoperative delirium (POD) in older patients undergoing joint replacement, and its effect on insulin sensitivity-related biomarkers.

212 older patients (≥65 years) were randomly assigned to receive either 40 IU of intranasal insulin (n=106) or a placebo (n=106) for 8 days. The primary objective was to determine the incidence and severity of POD within 5 days after surgery, estimated using the Confusion Assessment Method (CAM) and the Delirium Rating Scale (DRS)-98. The secondary objective was insulin sensitivity, which was assessed using the homeostasis model Assessment of Insulin Resistance (HOMA-IR) and biomarkers, including total osteocalcin (tOC), uncarboxylated osteocalcin (ucOC), and brain-derived neurotrophic factor (BDNF).

Compared to placebo, intranasal insulin significantly reduced the incidence of delirium within 5 days after surgery (8 [8.33%] vs 23 [23.23%], P = 0.004, odds ratio [OR] = 3.33 [95% CI 1.41-7.88]) and the severity of delirium (P<0.001). Intranasal insulin elevated the levels of tOC, ucOC, and BDNF in the CSF on D0 (all P<0.001) and tOC levels in the plasma on D0, D1 and D3 (all P<0.001). It elevated ucOC levels in the plasma of the insulin group on D0 but not on D1 and D3 (all P<0.001). Intranasal insulin administration reduced the HOMA-IR on D3 (P=0.002).

Intranasal insulin notably reduced the incidence and severity of POD in older patients undergoing joint replacement, which may be related to the elevation in osteocalcin and BDNF levels.

Chinese Clinical Trial Registry (ChiCTR2300068073).

Midazolam is a short-acting benzodiazepine frequently used in the perioperative setting. This study aimed to investigate the potential impact of intraoperative midazolam on postoperative delirium in older patients undergoing noncardiac surgery.

This study included patients aged 65 yr and older who received general anesthesia between April 2020 and April 2022 in multiple hospitals across China. Postoperative delirium occurring within 7 days was assessed using the 3-min Diagnostic Interview for Confusion Assessment Method. Univariable and multivariable logistic regression models based on the random effects were used to determine the association between midazolam administration and the occurrence of postoperative delirium, presented as the risk ratio and 95% CI. A Kaplan-Meier cumulative incidence curve was plotted to compare the distribution of time to postoperative delirium onset between patients who received midazolam and those who did not. Subgroup analyses based on specific populations were performed to explore the relationship between midazolam and postoperative delirium.

In all, 5,663 patients were included, of whom 723 (12.8%) developed postoperative delirium. Univariate and multivariable logistic regression analyses based on random effects of different hospitals showed no significant association between midazolam medication and postoperative delirium among older population (unadjusted risk ratio, 0.96; 95% CI, 0.90 to 1.30; P = 0.38; and adjusted risk ratio, 1.09; 95% CI, 0.91 to 1.33; P = 0.35). The Kaplan-Meier curve showed no difference in the distribution of time to postoperative delirium onset (hazard ratio, 1.02; 95% CI, 0.88 to 1.18; P = 0.82). The results of subgroup analyses found that intraoperative midazolam treatment was not associated with postoperative delirium in the specific subgroups of patients.

Intraoperative administration of midazolam may not be associated with an increased risk of postoperative delirium in older patients undergoing noncardiac surgery.

Delirium is a common and serious neuropsychiatric syndrome affecting older adults, particularly after surgery. It manifests in three forms: hypoactive, hyperactive, and mixed, with symptoms ranging from lethargy and inattention to agitation and confusion. Delirium is often misdiagnosed or overlooked, especially in its hypoactive form, which can delay treatment and worsen patient outcomes. Distinguishing delirium from dementia is crucial, as delirium is typically reversible with prompt intervention. This article, presented in a case study format, explores the assessment and management of delirium in postoperative patients, highlighting the use of validated tools such as the Delirium Elderly at Risk (DEAR) and the Confusion Assessment Method (CAM). Early identification of at-risk patients and timely screening are critical for improving outcomes. Non-pharmacological interventions, including reorientation, sleep hygiene, sensory aids, early mobilization, and family involvement, play a vital role in preventing and managing delirium. The article emphasizes the importance of nurses in detecting early signs of delirium and implementing preventative measures. A multidisciplinary approach, integrating ongoing screening, patient-centered care, and non-pharmacological strategies, is essential for reducing the incidence and severity of delirium. Early detection and appropriate management can significantly improve recovery and reduce long-term complications, promoting better outcomes in older adults undergoing surgery.

Delirium after cardiac surgery is common, morbid, and costly, but may be prevented with risk stratification and targeted intervention. In this study, we aimed to identify protein biomarkers and develop a predictive model for postoperative delirium in older patients undergoing cardiac surgery.

SomaScan analysis of 1305 proteins in the plasma from 57 older adults undergoing cardiac surgery requiring cardiopulmonary bypass was conducted to define delirium-specific protein signatures at baseline (preoperative baseline timepoint [PREOP]) and postoperative day 2 (POD2). Selected proteins were validated in 115 patients using the Enzyme-Linked Lectin Assay (ELLA) multiplex immunoassay platform. Proteins were combined with clinical and demographic variables to build multivariable models that estimate the risk of postoperative delirium and bring light to the underlying pathophysiology.

Of the 115 patients, 21 (18.3%) developed delirium after surgery. The SomaScan proteome screening evidenced differential expression of 115 and 85 proteins in delirious patients compared to nondelirious preoperatively and at POD2, respectively ( P < .05). Following biological and methodological criteria, 12 biomarker candidates (Tukey's fold change [|tFC|] >1.4, Benjamini-Hochberg [BH]- P < .01) were selected for ELLA multiplex validation. Statistical analyses of model fit resulted in the combination of age, sex, and 3 proteins (angiopoietin-2; C-C motif chemokine 5; and metalloproteinase inhibitor 1; area under the curve [AUC] = 0.829) as the best performing predictive model for delirium. Analyses of pathways showed that delirium-associated proteins are involved in inflammation, glial dysfunction, vascularization, and hemostasis.

Our results support the identification of patients at higher risk of developing delirium after cardiac surgery using a multivariable model that combines demographic and physiological features, also bringing light to the role of immune and vascular dysregulation as underlying mechanisms.

Patients undergoing liver transplantation (LT) are at risk of perioperative neurocognitive dysfunction (PND), which significantly affects the patients' prognosis.

This study used machine learning (ML) algorithms with an aim to extract critical predictors and develop an ML model to predict PND among LT recipients.

In this retrospective study, data from 958 patients who underwent LT between January 2015 and January 2020 were extracted from the Third Affiliated Hospital of Sun Yat-sen University. Six ML algorithms were used to predict post-LT PND, and model performance was evaluated using area under the receiver operating curve (AUC), accuracy, sensitivity, specificity, and F1-scores. The best-performing model was additionally validated using a temporal external dataset including 309 LT cases from February 2020 to August 2022, and an independent external dataset extracted from the Medical Information Mart for Intensive Care Ⅳ (MIMIC-Ⅳ) database including 325 patients.

In the development cohort, 201 out of 751 (33.5%) patients were diagnosed with PND. The logistic regression model achieved the highest AUC (0.799) in the internal validation set, with comparable AUC in the temporal external (0.826) and MIMIC-Ⅳ validation sets (0.72). The top 3 features contributing to post-LT PND diagnosis were the preoperative overt hepatic encephalopathy, platelet level, and postoperative sequential organ failure assessment score, as revealed by the Shapley additive explanations method.

A real-time logistic regression model-based online predictor of post-LT PND was developed, providing a highly interoperable tool for use across medical institutions to support early risk stratification and decision making for the LT recipients.

Delirium, frequently experienced by ischemic stroke patients, is one of the most common neuropsychiatric syndromes reported in the Intensive Care Unit (ICU). Stroke patients with delirium have a high mortality rate and lengthy hospitalization. For these reasons, early diagnosis of delirium in the ICU is critical for better patient prognosis. Therefore, we developed and validated prediction models to classify the real-time delirium status in patients admitted to the ICU or Stroke Unit (SU) with ischemic stroke.

A total of 84 delirium patients and 336 non-delirium patients in the ICU of Ajou University Hospital were included. The 8 fixed features [Age, Sex, Alcohol Intake, National Institute of Health Stroke Scale (NIHSS), HbA1c, Prothrombin time, D-dimer, and Hemoglobin] identified at admission and 12 dynamic features [Mean or Variability indexes calculated from Body Temperature (BT), Heart Rate (HR), Respiratory Rate (RR), Oxygen saturation (SpO2), Systolic Blood Pressure (SBP), and Diastolic Blood Pressure (DBP)] based on vital signs were used for developing prediction models using the ensemble method.

The Area Under the Receiver Operating Characteristic curve (AUROC) for delirium-state classification was 0.80. In simulation-based evaluation, AUROC was 0.71, and the predicted probability increased closer to the time of delirium occurrence. We observed that the patterns of dynamic features, including BT, SpO2, RR, and Heart Rate Variability (HRV) kept changing as the time points were getting closer to the delirium occurrence time. Therefore, the model that employed these patterns showed increasing prediction performance.

Our model can predict the real-time possibility of delirium in patients with ischemic stroke and will be helpful to monitor high-risk patients.

Delirium is a severe neuropsychiatric symptom following acute ischemic stroke (IS) and is associated with poor outcomes. Systemic inflammation and immune dysregulation are believed to contribute to the pathophysiology of delirium. The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) are widely recognized as convenient and reliable biomarkers of systemic inflammation. However, their association with delirium after IS remains unclear.

In this study, we identified IS patients requiring ICU admission from the Medical Information Mart for Intensive Care (MIMIC)-IV database. We employed multivariable logistic regression and restricted cubic splines (RCS) to assess the association between the NLR, PLR, and LMR and delirium. Two-sample Mendelian randomization (MR) analysis was performed to further explore their causal relationship at the genetic level.

A total of 1,436 patients with IS were included in this study, of whom 214 (14.9%) had delirium. In the multivariate logistic regression analysis, after adjustment for confounders, the patients in the highest quartile of the NLR (odds ratio [OR] 2.080, 95% confidence interval [CI], 1.282-3.375) and LMR (OR 0.503, 95% CI 0.317-0.798) and the patients in the second quartile of the PLR (OR 1.574, 95% CI 1.019-2.431) were significantly associated with delirium. The RCS function showed a progressive increase in the risk of delirium with higher NLR and PLR and lower LMR. In the MR analysis, only the PLR was negatively associated with the risk of delirium.

The observational studies found significant associations between the NLR, PLR, and LMR and delirium. However, the MR analysis only demonstrated a potential protective causal relationship between the PLR and delirium. Further prospective studies are needed to validate their association and to elucidate the underlying mechanisms.

Delirium is a common symptom following a traumatic brain injury that is often overlooked by healthcare professionals. Early detection of posttraumatic delirium is crucial to improving patient outcomes and quality of life. The 4 As Test (4AT: alertness, attention, abbreviated mental test-4, and acute mental changes) is a brief and rapid tool for delirium assessment with acceptable reliability and validity. However, the 4AT has not yet been translated for use in the Taiwanese population.

To translate the 4AT into Traditional Chinese (TC-4AT), assess its reliability and validity, and explore the clinical effects of delirium in patients with a traumatic brain injury.

This prospective observational study was conducted at the neurosurgery wards of 2 Taiwanese hospitals. Patients who were aged 20 years or older, were diagnosed with a traumatic brain injury, and had a Glasgow Coma Scale score between 13 and 15 were included. Interrater reliability was assessed, and validity was verified using criterion-related comparisons with the Short Confusion Assessment Method. The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria were employed to assess the sensitivity and specificity of the TC-4AT for screening posttraumatic brain injury delirium.

A total of 100 patients with an average age of 67 years were enrolled, of whom 10% were diagnosed with delirium based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. The interrater reliability of the TC-4AT was 1.00. Patients with delirium tended to have a longer hospital stay than those without delirium (13 days vs. 7 days) although the difference was nonsignificant (P = 0.28). In terms of criterion validity, patients diagnosed with delirium using the Short Confusion Assessment Method had a significantly higher score on the TC-4AT than those not diagnosed with delirium (P < 0.001). The receiver operating characteristic curve indicated that the optimal cutoff point was 4, with sensitivity, specificity, and area under the characteristic curve of 0.90, 0.94, and 0.96, respectively.

The TC-4AT is an accurate tool for delirium assessment that aids early detection and in informed decision-making in preventive care.

Objective: This study evaluates clinical characteristics, hospitals outcomes, and mortality determinants in older sepsis patients before and during COVID-19. Methods: Retrospective of sepsis cases (aged 65+) from nine hospitals (2018-2020) using ICD codes. Multivariate logistic regression was used to analyze mortality predictors. Results: Of 4635 sepsis patients, 515 (11.1%) passed in-hospital, with mortality rising to 13.9% during the pandemic from 10% prior (p < .01). Pandemic admissions had more racial minorities and severe comorbidities. Patient safety indicator events decreased during the pandemic (14.8% vs. 17.9%, p < .01), while home discharge rates remained consistent. Pandemic admission and lack of insurance correlated with increased mortality, alongside advanced age, ICU admission, and opioid and sedative use. Conclusion: COVID-19 pandemic admission and socioeconomic factors heightened mortality risks in older sepsis patients, highlighting the need for targeted care strategies.

Postoperative delirium (POD) is a serious complication in elderly patients after major surgery, associated with high morbidity and mortality. Treatment and prevention methods are limited. Repetitive transcranial magnetic stimulation (rTMS) shows potential in enhancing cognitive function and improving consciousness.

To evaluate whether early postoperative rTMS has a protective effect against POD and to explore its potential mechanisms.

Patients aged 60 years or older, scheduled for major abdominal surgery, were randomly assigned to receive rTMS at 100 % RMT, 10 Hz, with 2000 pulses targeting the DLPFC after extubation in PACU, either as active rTMS(n = 61) or sham rTMS (n = 61). The primary outcome was the incidence of POD during the first 3 postoperative days.

In the modified intention-to-treat analysis of 122 patients (mean [SD] age, 70.2 [4.1] years; 53.3 % women), POD incidence was lower in the rTMS group (11.5 %) compared to the sham rTMS group (29.5 %) (relative risk, .39; 95 % CI, .18 to .86; P = .01). rTMS patients had higher BDNF (8.47 [2.68] vs. 5.76 [1.42] ng/mL; P < .001) and lower NfL (.05 [.04] vs. .06 [.04] ng/mL; P = .02) levels. Mediation analysis suggests that rTMS may reduce POD by increasing brain-derived neurotrophic factor (z = -3.72, P < .001) rather than decreasing neurofilament light (z = 1.92, P = .06).

Immediate postoperative rTMS can reduce the incidence of POD in elderly patients undergoing major abdominal surgery, probably by upregulating brain-derived neurotrophic factor levels.

Drug-induced delirium is known risk factors associated with increased morbidity and mortality in older patients. The objective was to evaluate the risk of drug-related delirium in older patients based on the FDA Adverse Event Reporting System (FAERS).

Delirium reports in older patients (age ≥65) extracted from the FAERS database using Open Vigil 2.1. The reported odds ratio and the proportional reported ratio were calculated to detect the adverse reaction signal of delirium. Combined with published evidence, suspected drugs were categorized as known, possible, or new potential delirium-risk-increasing drugs.

Of the 130,885 reports (including 28,850 delirium events and 1,857 drugs) analyzed for this study, 314 positive signal drugs were detected. Positive signal drugs are mainly concentrated on the drug of nervous system, cardiovascular system , alimentary tract and metabolism and anti-infectives for systemic use. Of the positive signal drugs, 26.11% (82/314) were known delirium-risk increasing drugs, 44.90% (141/314) were possible and 28.98% (91/314) were new potential.

Drug-induced delirium risk is prevalent in older patients, according to the FAERS. The risk level of drug-induced delirium should be taken into account to optimize drug therapy in clinical practice.

To summarize the delirium treatment trial literature, identify the unique challenges in delirium treatment trials, and formulate recommendations to address each in older adults.

A 39-member interprofessional and international expert working group of clinicians (physicians, nurses, and pharmacists) and nonclinicians (biostatisticians, epidemiologists, and trial methodologists) was convened. Four expert panels were assembled to explore key subtopics (pharmacological/nonpharmacologic treatment, methodological challenges, and novel research designs).

To provide background and context, a review of delirium treatment randomized controlled trials (RCTs) published between 2003 and 2023 was conducted and evidence gaps were identified. The four panels addressed the identified subtopics. For each subtopic, research challenges were identified and recommendations to address each were proposed through virtual discussion before a live, full-day, and in-person conference. General agreement was reached for each proposed recommendation across the entire working group via moderated conference discussion. Recommendations were synthesized across panels and iteratively discussed through rounds of virtual meetings and draft reviews.

We identified key evidence gaps through a systematic literature review, yielding 43 RCTs of delirium treatments. From this review, eight unique challenges for delirium treatment trials were identified, and recommendations to address each were made based on panel input. The recommendations start with design of interventions that consider the multifactorial nature of delirium, include both pharmacological and nonpharmacologic approaches, and target pathophysiologic pathways where possible. Selecting appropriate at-risk patients with moderate vulnerability to delirium may maximize effectiveness. Targeting patients with at least moderate delirium severity and duration will include those most likely to experience adverse outcomes. Delirium severity should be the primary outcome of choice; measurement of short- and long-term clinical outcomes will maximize clinical relevance. Finally, plans for handling informative censoring and missing data are key.

By addressing key delirium treatment challenges and research gaps, our recommendations may serve as a roadmap for advancing delirium treatment research in older adults.

The aim of this study was to identify hospital-based workplace violence (WPV) risk factors with the Haddon Matrix Model (HMM) to determine its potential utility to conceptualize multiple risks for WPV events. This descriptive study utilized two independent convenience samples Data from behavioral emergencies (2014-2015) for patient violence (N = 192) and from health care staff (N = 380) 12-month violence survey responses (2015) in a Midwestern academic hospital were analyzed. Logistic regression examined patient features associated with physical violence. Survey questions pertained to employee, environment, and cultural factors associated with WPV; responses were examined with Chi-square and two-sample t-tests. Violence risk factors populated the 4 Haddon Matrix domains at pre-event time frames as Host (worker)-age/demographics, Agent (patient)-age/gender, Physical Environment-door/window structure, and Social Environment-worker safety. Risks at event time frames populated for Agent-behavior/delirium, and Physical Environment-event medication/patient identification. The Haddon Matrix identification of hospital violence risks indicates its utility as a comprehensive approach to workplace violence.

Hospital at Home (HaH) programs are used throughout the United States and are beneficial in both providing patients care in environments most comfortable to them and freeing up inpatient beds. Better informing patients about HaH programs, while promoting shared decision-making (SDM), should be prioritized by health systems. SDM apps may promote increased patient agency and understanding of complex HaH care decisions. We previously developed, usability tested, and refined a HaH SDM app.

To evaluate the utility of SDM apps in assisting pneumonia patients with HaH admission.

Usability surveys (N = 16) and semistructured interviews with patients (N = 9) and nurse navigators (N = 3) were utilized to evaluate our app in assisting pneumonia patients as they contemplated HaH admission. Recruitment occurred at three hospitals in the southeastern United States. Surveys were analyzed consistent with their validated measures, while interviews were analyzed using inductive coding methodologies.

Patients supported receiving HaH information via an app, with many noting that presenting content via multiple modalities (e.g., videos, pictures, text) was helpful and that the app assisted their care decision. App-guided inquiries into patients' care preferences helped patients visualize their priorities and promoted feelings of agency, while providing important information to care teams. Participants found visuals effective at conveying program details, for example, HaH's in-home setup, which may assist with health literacy challenges. Potential barriers included the need to expand app accessibility for vision impaired and non-English speaking patients.

SDM apps may better inform patients' HaH care decisions, allowing patients self-directed access to information and engagement with visual content, which may address challenges related to health literacy and navigating complex, time-sensitive decisions.

Emergence delirium (ED) is one of the most frequent postoperative complications in pediatric patients after general anesthesia. In adults, a deeper intraoperative level of anesthesia has been reported as an independent predictor of postoperative delirium. However, the effect of anesthetic depth on ED has rarely been demonstrated in the pediatric population. We evaluated whether the depth of general anesthesia could affect the occurrence of emergence delirium (ED).

Patients aged 3-5 years, scheduled for strabismus surgery were enrolled in this prospective observational study. Intraoperative bispectral index (BIS) was monitored, and the pediatric anesthesia emergence delirium (PAED) scale was evaluated. When the PAED scale was 10 or more, it was designated as an ED case.

According to the intraoperative mean BIS range, enrolled patients were divided into two groups: the low BIS (BIS < 40; n = 28) and the normal BIS (BIS 40-60; n = 34) group. The incidence of ED was comparable between the two groups (67.6% vs. 67.9%, odds ratio = 0.99, 95% CI = 0.34-2.89, p = 0.986).

The intraoperative anesthetic depth did not seem to affect the occurrence of ED in pediatric patients undergoing strabismus surgery under general anesthesia. Future studies with a larger sample size are necessary for more authentic results.