Critical Care Medicine

Rationale. Racial disparities in outcomes among patients with acute respiratory failure are well-described, but the contributions of clinicians to these disparities have not been evaluated. Objectives. Among mechanically ventilated patients, we evaluated racial disparities in severity of illness trajectories and adapted value-added modeling to quantify nurse and physician relationships with these disparities. Methods. In a retrospective cohort of mechanically ventilated patients across five hospitals between 2018 and 2022, we used generalized estimating equations to model the change in Laboratory-based Acute Physiology Score version 2 (LAPS) from the start to end of intensive care unit admission ({Delta}LAPS). Consistent with value-added modeling, we randomly allocated the cohort into development and testing partitions, and fit separate multiple linear regression models of {Delta}LAPS using concurrent nurse and physician assignments (determined at 4-hour intervals), patient race, and clinician-race interaction terms as fixed effects. Clinician-specific and clinician-race interaction coefficients were extracted to determine race-specific value-add for each clinician. We defined the race-contextual value-add difference (RCVAD) as a clinician-level measurement of the difference in that clinician's value-add between Black and White patients in their care; a positive RCVAD indicates a more favorable severity of illness trajectory for Black relative to White patients and vice versa. Measurement and Main Results. Among 6,555 distinct patients, 7,247 clinical encounters, 405 nurses, and 70 physicians, Black patients accounted for 2,926 (40%) encounters. Overall, Black patients had significantly less improvement in {Delta}LAPS than White patients (difference in LAPS decline = 2.26 [0.23, 4.29], p=0.029). In the development partition, median nurse RCVAD was -0.10 (interquartile range [IQR]: -1.17, 1.14) with 191 (47%) nurses having a positive RCVAD; median physician RCVAD was -0.18 (IQR: -1.34, 0.56) with 29 (41%) having a positive RCVAD. Conclusions. Black mechanically ventilated patients experience less improvement in severity of illness during intensive care unit admission than White patients. While the majority of physicians and nurses were associated with disparities-exacerbating illness trajectories, many other clinicians were associated with disparities-mitigating trajectories. Future work to understand practices associated with disparities-exacerbating and disparities-mitigating care profiles could inform interventions to reduce disparities overall.

IntroductionIntraoperative glycemic dysregulation, including unrecognized hypoglycemia and stress-induced hyperglycemia, is common during elective surgery. Conventional point-of-care (POC) monitoring provides only intermittent measurements, limiting the anesthesiologists ability to detect rapid glucose fluctuations. Continuous glucose monitoring (CGM) enables real-time, trend-based assessment, potentially shifting intraoperative glycemic management from reactive to proactive. ObjectiveTo meta-analyze the analytical accuracy, intraoperative glycemic efficacy, and feasibility of subcutaneous CGM in adults undergoing elective surgery, informing anesthesiology practice. MethodsThis systematic review and meta-analysis followed the PRISMA 2020 statement. Searches were conducted in PubMed, Embase, and Cochrane Central Register of Controlled Trials from January 2010 to May 2025. Eligible studies included randomized controlled trials and prospective cohorts of adults undergoing elective surgery under general or neuraxial anesthesia using subcutaneous CGM. Primary outcomes were pooled mean absolute relative difference (MARD) and time in range (TIR, 70-180 mg/dL). Random-effects models were applied. ResultsTen studies (3 RCTs, 7 cohorts; N=557) were included. Pooled MARD was 14.1% (95% CI 11.3-16.9%; I{superscript 2}=78%), lower in non-cardiac surgery (12.7%) than cardiac procedures with hypothermia (19.2%; p=0.03). CGM improved TIR by +14.9 percentage points (95% CI 7.2-22.6; p<0.001). Clinically significant hypoglycemia was detected in 43% of patients, all missed by POC. Sensor availability exceeded 96%, with no serious device-related events. ConclusionSubcutaneous CGM provides acceptable intraoperative accuracy and improves glycemic control, supporting its integration into anesthetic management.

BackgroundSepsis is a recognized risk factor for upper gastrointestinal bleeding, yet sepsis-specific randomized evidence informing stress ulcer prophylaxis remains limited. ObjectiveTo describe the rationale, methods, and statistical analysis plan for a post hoc subgroup analysis evaluating pantoprazole versus placebo in invasively ventilated critically ill adults with septic shock enrolled in the REVISE trial (NCT03374800). MethodsThis study will be a post hoc extended subgroup analysis of the international, blinded, randomized REVISE trial, which enrolled 4,821 mechanically ventilated adults in 68 ICUs across 8 countries. Patients were randomized to intravenous pantoprazole 40 mg once daily or placebo during invasive mechanical ventilation. Septic shock will be defined as receipt of vasopressors or inotropes at baseline together with an admitting diagnosis of infection according to APACHE III diagnostic categories. ResultsThe primary efficacy outcome will be clinically important upper gastrointestinal bleeding in the ICU within 90 days after randomization, and the primary safety outcome will be all-cause mortality within 90 days. Additional trial outcomes will include patient-important upper gastrointestinal bleeding, ventilator-associated pneumonia, Clostridioides difficile infection during hospitalization, new renal replacement therapy, mortality in the ICU and hospital, and duration of ICU and hospital stay. Analyses will be adjusted for prehospital acid suppression; the mortality analyses will be additionally adjusted for APACHE II score. ConclusionThis protocol and statistical analysis plan describes an evaluation of the efficacy and safety of pantoprazole in patients with septic shock within a large randomized trial dataset.

The Epic Sepsis Model version 2 (ESMv2) is a prediction model embedded into the electronic medical record used to warn clinicians which hospitalized patients are at risk for sepsis. We conducted a retrospective cohort study of 31,951 hospitalizations of 25,760 patients to compare analyses conducted at the commonly used patient-level (where a maximum prediction prior to the onset of sepsis is used to measure performance) vs novel prediction-level (where each prediction is used to measure performance). Sepsis, defined by the Sepsis 3 criteria occurred during 1,049 hospitalizations (3.3%). Patient-level analyses suggested excellent discrimination AUC 0.86; [IQR 0.85, 0.87], whereas prediction-level analyses demonstrated lower performance AUC 0.62; [IQR 0.57, 0.65]. Low estimates of the positive predictive value (14.5% at the patient level vs 4% at the prediction level) imply a high number of false alerts. Common evaluation approaches may overstate the performance of dynamic prediction models and mislead clinical decision-making.

ObjectivesTo determine whether heterogeneous treatment effects (HTE) explain the inconclusive results of targeted temperature management (TTM) trials after cardiac arrest, using causal machine learning across four datasets. DesignSecondary analysis of one multicenter RCT and three observational ICU cohorts using S-learner and forest-based R-learner models to estimate conditional average treatment effects (CATE). SettingTwenty-six French ICUs (HYPERION), approximately 200 U.S. ICUs (eICU-CRD), Johns Hopkins Hospital (PMAP), and Beth Israel Deaconess Medical Center (MIMIC-IV). PatientsAdults ([&ge;]18 years) with cardiac arrest; 4,507 patients across the four datasets, of whom 1,814 (40.2%) received TTM. InterventionsTTM as administered clinically or per HYPERION protocol. Ascertainment: randomization (HYPERION), treatment documentation (eICU-CRD), sustained hypothermia <36{degrees}C for >12 hours (PMAP), or documented cooling device use [&ge;]12 hours (MIMIC-IV). Measurements and Main ResultsThe primary outcome was hospital mortality; the secondary outcome was favorable neurologic function (Cerebral Performance Category 1-2 at 90 days for HYPERION; last motor Glasgow Coma Scale = 6 for observational cohorts). Three S-learner models (XGBoost, neural network, Bayesian Additive Regression Trees) and one forest-based R-learner (CausalForestDML) estimated CATE. HTE was assessed by likelihood-ratio tests for CATExtreatment interaction, CausalForestDML 95% confidence intervals, Group Average Treatment Effects (GATES) across CATE quintiles, and SHAP feature importance. S-learner discrimination was adequate (AUROC 0.72-0.82). No model showed a significant CATExTTM interaction in any dataset (all p > 0.05). Individual CATE confidence intervals uniformly crossed zero, and GATES showed no monotonic gradient of benefit across quintiles in any dataset. ConclusionsAcross four diverse datasets and multiple causal machine-learning approaches, we found no evidence of heterogeneous treatment effects for TTM after cardiac arrest. The inconclusive findings of TTM trials are unlikely explained by differential effects in identifiable subgroups defined by routinely available clinical features. KEY POINTSQuestion: Do identifiable patient subgroups derive differential benefit from targeted temperature management (TTM) after cardiac arrest? Findings: In a causal machine-learning analysis of 4,507 patients across one randomized trial and three observational ICU cohorts, no model detected significant heterogeneous TTM effects on mortality or neurologic outcome. Meaning: Conflicting TTM trial results are unlikely explained by differential effects in identifiable subgroups, weakening the rationale for personalized TTM strategies based on routinely available clinical features.

Abstract Background: Medical residents and physicians face persistently high-demand environments marked by heavy workloads, time pressure, night duties, and emotionally intense clinical encounters. These conditions increase vulnerability to stress-related outcomes, including burnout and impaired mental health, and can affect functioning at work. Personality traits are relatively stable individual differences and might help explain why some doctors experience greater stress vulnerability or use less adaptive coping strategies than others. Evidence linking the Big Five personality traits to stress, coping, and performance outcomes in residents and physicians has grown, but it remains difficult to apply because of inconsistent findings and heterogeneous measures. This systematic review and meta-analysis aim to synthesize the existing literature on how the Big Five personality traits influence these outcomes in medical residents and physicians. Methods: We conducted a PRISMA-aligned systematic review and meta-analysis (PROSPERO CRD42023483408). PubMed, Embase, MEDLINE (Ovid), Cochrane Library, Scopus, and Web of Science were searched from database inception to Nov 15, 2023. Searches were updated periodically through Jan 2026. Eligible studies were primary research in English involving medical residents and/or practicing physicians that assessed at least one Big Five trait using a recognized Five-Factor Model instrument and reported an association with a validated or clearly defined stress, coping, performance, or professional skills/aptitudes related outcome in medical residents or physicians. Studies exclusively involving medical students were excluded. Risk of bias was assessed using the AXIS tool (supplemented by Joanna Briggs Institute items) for cross-sectional studies and the Cochrane Risk of Bias 2 tool for the randomized trial. Where at least three comparable studies were available, effect sizes were pooled using random-effects models with restricted maximum likelihood estimation after Fishers z transformation; remaining studies were synthesized narratively. Results: Of the 4,967 records identified, 34 studies (21,379 participants) met the inclusion criteria; most were cross-sectional (30/34), with three longitudinal studies and one randomized trial. Meta-analyses were restricted to 11 studies reporting Maslach Burnout Inventory subscales and three studies reporting GHQ-12 psychological distress. Neuroticism showed the clearest and most consistent adverse associations: for emotional exhaustion (pooled r=0.418, 95% CI 0.219 to 0.616, p<0.001), for depersonalization (pooled r=0.304, 95% CI 0.166 to 0.442, p<0.001), and for personal accomplishment (pooled r=-0.244, 95% CI -0.393 to -0.094, p=0.005). Conscientiousness, Extraversion, and Agreeableness showed small protective patterns, with lower emotional exhaustion and depersonalization and higher personal accomplishment, although associations with stress were weak and generally non-significant. Openness showed a weaker, selective pattern, with lower depersonalization and higher personal accomplishment, but no clear association with emotional exhaustion or stress. Moderator analyses suggested that associations for Neuroticism, Conscientiousness, and Agreeableness varied more by experience and region than by specialty, whereas Extraversion was moderated mainly by experience; Openness showed little evidence of consistent moderation. Narrative synthesis of studies not included in the main meta-analyses was broadly concordant: Neuroticism was the most consistent vulnerability marker for burnout, distress, maladaptive coping, and poorer work-related outcomes, whereas Conscientiousness and, to a lesser extent, Extraversion were linked to more adaptive coping and more favorable performance-related indicators. Agreeableness showed modest prosocial and attitudinal benefits, and Openness remained the least consistent trait across outcomes. Overall risk of bias was low to moderate for most observational studies, although heterogeneity was substantial across pooled analyses. Conclusions: Big Five personality traits have modest correlation with physicians and residents burnout, distress, coping, and work-related functioning. Neuroticism emerged as the clearest vulnerability marker, whereas Conscientiousness and, to a lesser extent, Extraversion and Agreeableness showed small protective associations. Interpretation is limited by the predominance of cross-sectional designs, reliance on self-report, substantial heterogeneity, and restricted geographic representation. These findings support the use of personality traits as a supportive and formative resource within medical education and workforce well-being, but not for deterministic selection or labelling. Larger longitudinal and intervention studies using multi-method outcomes are needed to clarify mechanisms and causal pathways.

IntroductionThere is increasing interest in the peripheral administration of vasopressors for two main reasons: (1) to expedite vasopressor initiation in patients with refractory shock and (2) to avoid the potential complications associated with central venous catheter placement. The current evidence on the use of peripheral vasopressor administration is primarily based on single-center observational studies. There are inconsistencies in the administration of peripheral vasopressors, including catheter gauge and location, monitoring practices, vasopressor concentrations, and duration of use. This has made it difficult for institutions to develop best practice guidelines. A randomized controlled trial is needed to address this knowledge gap. Methods and analysisThe Peripheral Use of Low-dose Vasopressors for Safety and Efficacy (PULSE) in the intensive care unit is a prospective, unblinded feasibility study. Eligible patients will be 18 years or older, have no existing central venous catheter or peripherally inserted central catheter and have the presence of shock requiring a minimum vasopressor dose of any of the following: norepinephrine 0.0625 mcg/kg/min, phenylephrine 0.625 mcg/kg/min, and epinephrine 0.0625 mcg/kg/min. Fifty patients will be randomized 1:1 into either the peripheral venous catheter or central venous catheter group. The primary outcome is feasibility, defined as (1) a recruitment rate of 4 participants per month, (2) a data capture rate of [&ge;]90%, and (3) a <50% conversion rate from peripheral to central access. The secondary outcomes include the safety of peripheral vasopressor use, alive and central-line-free days, the number of attempts needed to place a catheter, volume status, in-hospital mortality rate, ICU and hospital length of stay, and patient-centred important outcomes. ImplicationsThe data collected from this study will inform the design of a definitive randomized controlled trial to assess the safety and efficacy of protocol-driven peripheral vasopressor administration. Ethics and disseminationThis study received approval (6042888) from the Queens University Health Sciences/Affiliated Teaching Hospitals Research Ethics Boards. Results of this study will be presented at critical care conferences and submitted for publication. Trial registration numberNCT06920173 (https://clinicaltrials.gov/study/NCT06920173).

Background Hypercapnia may indicate a primary ventilatory syndrome, a complication of another illness, or an epiphenomenon of severe disease. The presenting context of hypercapnia is poorly quantified, limiting clinical interpretation and synthesis of epidemiologic studies. Methods We performed a retrospective cross-sectional study of Medical Information Mart for Intensive Care IV (MIMIC-IV) hospital admissions linked to an emergency department (ED) presentation from 2011 through 2019. Admissions were included if the triage chief complaint was not missing and at least one prespecified criterion for hypercapnia was met: an International Classification of Diseases (ICD) code for hypercapnic respiratory failure or obesity hypoventilation syndrome, arterial blood gas (ABG) PCO2 45 mmHg, venous blood gas (VBG) PCO2 50 mmHg, or indeterminate-source blood gas PCO2 50 mmHg. Triage chief-complaint text was classified by natural language processing (NLP) into 17 National Hospital Ambulatory Medical Care Survey reason-for-visit (RFV) categories using a multi-label framework. Primary analyses estimated admission-level RFV category prevalences; secondary analyses compared distributions by overlapping ascertainment indicator, age, and acidemia. Results The total cohort included 11,941 admissions: 1,542 (12.9%) met both blood-gas and ICD-code criteria, 9,958 (83.4%) met blood-gas criteria only, and 441 (3.7%) met ICD-code criteria only. Median age at admission was 68 years (IQR 56-78), and 6,423 admissions (53.8%) were for male patients. Respiratory RFV categories were most prevalent (30.2%), followed by administrative reasons (17.5%), digestive symptoms (14.0%), injuries and adverse effects (14.0%), and nervous-system symptoms (13.8%); categories were not mutually exclusive. Respiratory categories were more common in ICD-positive admissions (50.2%) than in VBG-defined (36.3%) or ABG-defined admissions (27.3%). Injuries and adverse effects were most prevalent among admissions for patients aged 18-39 years (34.4%), whereas respiratory categories increased from 13.7% among admissions for patients aged 18-39 years to 36.5% among admissions for patients aged 80 years. NLP-derived classifications showed mean set-F1 of 0.84 against adjudicated clinician labels in the full annotated benchmark sample. Conclusions Among ED-linked admissions with hypercapnia by diagnosis code, blood gas, or both, respiratory complaints were the most common chief-complaint category but represented fewer than one-third of admissions. Presentation context should be incorporated when defining, comparing, and interpreting hypercapnia cohorts, particularly those ascertained by blood-gas criteria.

Background: Accurate early identification of sepsis remains a major clinical challenge due to its heterogeneous presentation and overlap of clinical signs with the non-infectious systemic inflammatory response syndrome (SIRS). Timely differentiation is crucial for improving patient outcomes, meeting sepsis bundle requirements and reducing inappropriate antimicrobial use. We hypothesized that clinical and laboratory data available within the first 3 hours of patient presentation could be used to identify patients with sepsis to an actionable level of accuracy, in lieu of traditional microbiology results which would not become available until at least 12-24 hours. Data from two independent studies were used to quantify the diagnostic value of demographic, vital, clinical-laboratory, and microbiological data available at three time points for distinguishing retrospectively diagnosed critically ill patients with either sepsis or non-infectious SIRS. A particular focus of this work was an assessment of the utility of SeptiCyte RAPID (Immunexpress Inc., Seattle, Washington, USA) as an aid to sepsis diagnosis, producing actionable data within 1 hour. Methods: Data from two independent study cohorts were analysed. The 510k cohort consisted of 419 adult patients in intensive care (ICU) (MARS, VENUS, and NEPTUNE trials). The Andalusian cohort consisted of 353 ICU patients from the PANGEA study. Logistic regression models, selected by a greedy search algorithm and validated by repeated cross-validation, were used to determine the contributions of different variables to diagnostic accuracy. Diagnostic performance was quantified by area under the receiver operating characteristic curve (AUC). Results: For the 510k cohort, a baseline AUC of 0.69-0.73 was observed using 5-7 vital and demographic variables assessed immediately upon presentation (time T1). The addition of clinical-laboratory variables, in particular SeptiCyte RAPID, within 1-3 hours post-presentation (time T2) increased the AUC to 0.83-0.85). Finally, the addition of microbiological data 12-24 hours post-presentation (time T3) further improved the AUC to 0.90-0.91. Similar results were obtained for the Andalusian cohort. AUC values at the three time points were as follows: At time T1, AUC = 0.67 based solely on vital signs and demographics; at time T2, AUC = 0.87 based on vitals + demographics + SeptiCyte RAPID or other clinical laboratory data; at time T3, AUC = 0.93 based on vitals + demographics + SeptiCyte RAPID or other clinical laboratory data + microbiology results). For both cohorts, the most significant variables included temperature, mean arterial pressure, respiratory rate, suspected infection site; SeptiCyte RAPID, procalcitonin, confirmed bacterial infection and positive blood culture confirmation. Conclusions: Accuracy of identification of sepsis increases markedly as demographics and vital signs are supplemented with clinical-laboratory information, and ultimately with microbiological culture results. The fastest improvement occurs within the first 3 hours when laboratory data, and in particular SeptiCyte RAPID results, become available. Integrating rapid host-response testing with SeptiCyte RAPID into time-based diagnostic frameworks may enhance early sepsis recognition, improve antimicrobial stewardship, and support guideline-driven clinical decisions.

ImportancePhysicians routinely prognosticate to guide care delivery and shared decision making, particularly when caring for patients with critical illnesses. Yet, these physician estimates are prone to inaccuracy and uncertainty. Artificial intelligence, including large language models (LLMs), show promise in supporting or improving this prognostication. However, the performance of contemporary LLMs in prognosticating for the heterogeneous population of critically ill patients remains poorly understood. ObjectiveTo characterize and compare the performance of LLMs and physicians when predicting 6-month mortality for hospitalized adults who survived critical illness. DesignEmbedded mixed methods study with elicitation and comparison of prognostic estimates and reasoning from LLMs and practicing physicians. SettingThe publicly available, deidentified Medical Information Mart for Intensive Care (MIMIC)-IV v2.2 dataset. ParticipantsWe randomly selected 100 hospitalizations of adult survivors of critical illness. Four contemporary LLMs (Open AI GPT-4o, o3- and o4-mini, and DeepSeek-R1) and 7 physicians provided independent prognostic estimates for each case (1,100 total estimates; 400 LLM and 700 physician). Main outcomes and measuresFor each case, LLMs and physicians used the hospital discharge summary and demographics to predict 6-month mortality (yes/no) and provide their reasoning (free text). We assessed prognostic performance using accuracy, sensitivity, and specificity, and used inductive, qualitative content analysis to characterize reasonings. ResultsMean physician accuracy for predicting mortality was 70.1% (95% CI 63.7-76.4%), with sensitivity of 59.7% (95% CI 50.6-68.8%) and specificity of 80.6% (95% CI 71.7-88.2%). The top-performing LLM (OpenAI o4-mini) accuracy was 78.0% (95% CI 70.0-86.0%), with sensitivity of 80.0% (95% CI 67.4-90.2%) and specificity of 76.0% (95% CI 63.3-88.0%). The difference between mean physician and top-performing LLM accuracy was not statistically significant (p = 0.5). Qualitative analysis revealed similar patterns in LLM and physician expressed reasoning, except that physicians regularly and explicitly reported uncertainty while LLMs did not. Conclusion and RelevanceIn this study, LLMs and physicians achieved comparable, moderate performance in predicting 6-month mortality after critical illness, with similar patterns in expressed reasoning. Our findings suggest LLMs could be used to support prognostication in clinical practice but also raise safety concerns due to the lack of LLM uncertainty expression. KEY POINTSO_ST_ABSQuestionC_ST_ABSHow does large language model (LLM) prognostic accuracy and reasoning compare to physicians when predicting 6-month mortality for adult survivors of critical illness? FindingsIn this embedded mixed methods study, physicians and large language models had comparable, moderate prognostic accuracy with similar expressed reasoning patterns except that LLMs did not explicitly express uncertainty. MeaningLarge language models may be able to support physician prognostication, although the inability of LLMs to express uncertainty poses an important safety consideration.

RationaleSepsis is a life-threatening syndrome causing significant morbidity and mortality especially in the aging population. Clonal hematopoiesis of indeterminate potential (CHIP) is an age-related condition of clonal expansion of hematopoietic stem cells harboring somatic mutations associated with increased incidence of chronic illness and all-cause mortality. ObjectiveEvaluate the association of pre-illness CHIP with mortality and morbidity in patients admitted to the ICU with sepsis. MethodsWe performed a retrospective study using a de-identified electronic health record linked with a DNA biorepository. We identified adult patients with sepsis who had DNA collected prior to ICU admission. We tested the association between CHIP status, determined from whole-genome sequencing, and ICU mortality, organ support-free days, and long-term survival adjusting for age, sex, race and Sequential Organ Failure Assessment (SOFA) score on ICU admission. Measurements and Main ResultsPre-illness CHIP was associated with increased sepsis mortality (OR = 1.54, 95% CI 1.13 to 2.07, P = 0.005) and fewer days alive and free of organ support (-1.7 days, 95% CI -3.2 to -0.2, P = 0.028) after adjusting for age, sex, race, and SOFA score. In sepsis survivors, CHIP was also associated with increased long-term mortality after discharge (HR 1.40, 95% CI 1.01 to 1.93, P = 0.041). ConclusionsPre-illness CHIP was independently associated with increased mortality and morbidity in critically-ill adults with sepsis. These findings suggest that CHIP is a risk factor for sepsis severity. Elucidating the mechanism underlying this association could uncover new therapeutic interventions for sepsis.

BackgroundImmune dysfunction in sepsis and critical illness is biologically heterogeneous, yet available stratification frameworks leave many patients unclassified. We hypothesized that ex vivo cytokine-induction responses would define a continuous axis of functional immune responsiveness and identify a low-response state enriched in sepsis. MethodsIn this prospective observational study, 39 critically ill adults enrolled within 48 hours of ICU admission and 6 healthy controls underwent standardized whole-blood stimulation with lipopolysaccharide, anti-CD3/anti-CD28 antibodies, and PMA/ionomycin, with selected wells additionally supplemented with interleukin-7 or granulocyte-macrophage colony-stimulating factor. Interleukin-6, tumor necrosis factor, and interferon-gamma responses were quantified and referenced to subject-specific unstimulated baselines. A patient-anchored primary feature matrix was used to derive a continuous immune axis by principal component analysis, and a cross-validated 5-feature MiniResponder score was developed as a portable summary measure. ResultsAmong critically ill patients, induced cytokine responses organized along a dominant continuous axis of functional immune responsiveness; the first principal component explained 53.3% of between-patient variance. MiniResponder captured this axis and showed a lower-shifted distribution in sepsis. Using a control-referenced threshold defined by the 10th percentile of the healthy-control distribution, 19 of 39 patients (48.7%) were classified as low-response, including 15 of 21 patients with sepsis (71.4%) and 4 of 18 critically ill patients without sepsis (22.2%) (odds ratio 8.75, Fisher exact P=0.004). In exploratory analyses, lower MiniResponder scores were associated with greater unadjusted improvement in Sequential Organ Failure Assessment score from day 1 to days 3-9 (rho=-0.33; P=0.046), but this association attenuated after adjustment for baseline SOFA score (beta=-0.10; 95% CI-0.36 to 0.27). ConclusionsEx vivo immune profiling identified a continuous patient-anchored axis of functional immune responsiveness in critical illness that can be summarized by a compact 5-feature score. A control-referenced low-response state was enriched in sepsis. This framework may complement existing biomarker-based stratification approaches and support future enrichment strategies in sepsis trials.

Purpose: Polypharmacy is highly prevalent among critically ill patients, yet it's independent impact on intensive care unit (ICU) outcomes in sepsis remains critically unexplored. We aimed to evaluate whether pre-admission polypharmacy independently predicts ICU mortality and provides incremental prognostic value using the medication reconciliation module of the MIMIC-IV-ED linked database. Materials and Methods: We conducted a retrospective cohort study of 3,347 adults admitted to the ICU who met Sepsis-3 criteria. Pre-admission polypharmacy was categorized as none (0-4), standard (5-9), or high (>=10 medications). Multivariable logistic regression, propensity score matching, and reclassification analyses (NRI/IDI) were performed. The primary outcome was in-hospital ICU mortality. Results: High polypharmacy was present in 58.9% of patients. Crude ICU mortality increased sequentially: 18.5% (none), 26.0% (standard), and 27.5% (high; p < 0.001). After multivariable adjustment, high polypharmacy independently predicted in-hospital ICU mortality (aOR 1.45, 95% CI (1.10-1.91)), and 28-day mortality (aOR 1.47). Drug-class analysis identified statins as significantly protective (aOR 0.56), whereas RAS blockers combined with diuretics increased acute kidney injury risk (aOR 1.49). Propensity matching confirmed the primary mortality association (matched aOR 1.28). Conclusions: By utilizing the ED medication reconciliation table, this study proves high polypharmacy represents a distinct 'pharmacologic frailty', independent of acute severity. Available instantly at triage, this zero-latency metric provides significant early prognostic value (SOFA NRI = 0.24) and identifies actionable high-risk interactions (e.g., RAS blockers plus diuretics) for immediate, targeted pharmacist-led intervention upon ICU admission.

ABSTRACT Background: Corticosteroids reduce mortality in severe COVID-19 requiring oxygen or invasive mechanical ventilation, yet emerging data suggest that SARS-CoV-2-associated acute lung injury is biologically heterogeneous and that treatment response may vary across molecularly defined disease states. Lung-derived molecular endotypes of severe COVID-19-associated acute lung injury have been described, but direct molecular profiling is not routinely available at the bedside. We evaluated whether a clinical predictor of previously defined lung molecular endotype identifies heterogeneity in corticosteroid treatment effect among mechanically ventilated patients with COVID-19. Methods: We utilized a single-center cohort of 5,000 patients with COVID-19 treated at the University of North Carolina Hospital between January 1, 2020, and December 31, 2022, to emulate a target trial assessing the effect of corticosteroid receipt on mortality, length of stay, and incident organ support. Confounding was addressed through inverse probability of treatment weighting (IPTW). Outcomes for severely ill patients requiring mechanical ventilation were compared to the RECOVERY trial results, with subsequent moderation analysis and stratified analysis by clinically predicted lung molecular endotype and vaccination status. The primary outcome was 28-day mortality. Secondary Outcomes were time to discharge alive and progression to additional organ support. Results: This emulated target trial showed a directionally favorable but non-statistically significant association between corticosteroid treatment and reduced 28-day mortality in patients requiring mechanical ventilation for SARS-CoV-2 infection. A clinical predictor of lung molecular endotype moderated the effect of corticosteroids on 28-day mortality (p-value for interaction 0.038) and identified distinct predicted endotype-specific treatment effect. Corticosteroid treatment was associated with lower 28-day mortality in the predicted Hyper-Inflammatory endotype (OR 0.62, 95% CI 0.39, 0.99) but not in the predicted Metabolic Dysregulation endotype (OR 1.15, 95% CI 0.82, 1.61). We did not detect significant effect modification by vaccination status (p-value for interaction 0.65), although inference was limited by the small, vaccinated subgroup (28-mortality OR 0.78, 95% CI 0.37, 1.65 in vaccinated vs 0.94, 95% CI 0.70, 1.26 in unvaccinated). Conclusions: In this target trial emulation of mechanically ventilated patients with severe COVID-19, corticosteroid treatment showed a directionally favorable but non-statistically significant association with reduced 28-day mortality in the overall cohort. However, a clinical predictor of lung molecular endotype identified significant heterogeneity in treatment effect, with benefit concentrated in the predicted Hyper-Inflammatory endotype and no apparent benefit in the predicted Metabolic Dysregulation endotype. These findings support prospective validation of clinically deployable endotype-guided corticosteroid treatment strategies in acute lung injury and ARDS.

Septic shock caused by fungal organisms is characterized by high mortality and diagnostic complexity. We used the Premier Healthcare Database to characterize antifungal use and fungal diagnoses among adults with septic shock requiring vasopressors admitted between October 2022 through July 2024. Among 12.8 million admission at 886 hospitals, 554,948 met septic shock criteria and were included for analysis. A fungal diagnosis was established in 11,405 (2.1%) of encounters; of these, 3,565 (31.3%) received intravenous antifungal therapy within one day of vasopressor initiation. In the overall cohort, antifungal therapy was initiated in 29,824 (5.5%) within one day of vasopressor initiation; of these, 3,656 (12.2%) were ultimately diagnosed with a fungal infection. In the 116 hospitals reporting microbiological data, a subgroup of 489 encounters with septic shock and culture-confirmed candidemia was identified. In this subgroup, intravenous antifungal therapy was initiated in 43.8% within one day, 63.8% within three days, and 78.9% within seven days. These findings highlight a profound decoupling between fungal diagnosis and treatment--few patients receiving antifungals were diagnosed with an infection that would be treated by these agents, while less than half of patients with septic shock and candidemia received timely treatment. Strategies for greater precision in empiric antifungal use in septic shock are needed to improve safety, stewardship, and outcomes.

Background Ventilator-associated pneumonia (VAP) is the most frequent nosocomial infection in critical care, affecting 20-36% of mechanically ventilated patients. Early prediction is hampered by the absence of a reliable, objective diagnostic standard. We developed ADVISE (Automated Dudley Ventilation Infection Series Evaluation), a machine learning model to predict physiological deterioration consistent with developing VAP using routinely collected electronic health record data from a UK NHS intensive care unit. Methods Retrospective observational study of admissions at Russell's Hall Hospital ICU (2008-2026). Following National Data Opt-Out exclusion (158 admissions, 4.2%), 3,566 admissions generated 33,208 candidate 48-hour observation blocks. Six temporal variables - FiO2, ventilator mode, P:F ratio, procalcitonin (PCT), secretion amount, and secretion description - were extracted across the baseline window (hours 1-24). A composite VAP-surrogate outcome required concurrent P:F ratio decline (>=5%) and PCT rise (>=0.5 ng/mL) across the outcome window (hours 25-48). After sequential quality filters, 2,134 blocks (18 positive, 0.84% prevalence) were retained. An XGBoost classifier was trained using nested 5-fold cross-validation with scale_pos_weight=114.0 and ROC-based hyperparameter optimisation on 1,495 training blocks, evaluated on 639 held-out test blocks. Performance was assessed via AUROC, AUPRC, and calibration (Brier score). Bootstrap resampling (1,000 iterations) generated 95% confidence intervals. Results On the held-out test set (n=639, 5 positive outcomes), ADVISE achieved AUROC 0.874 [95% CI: 0.771-0.939] and AUPRC 0.031 [0.008-0.069], representing a 4.0-fold improvement over the no-skill baseline. Nested cross-validation mean AUROC was 0.844 +/- 0.078 (range 0.716-0.915). At the Youden-optimal threshold, sensitivity was 0% with specificity 97.8%, reflecting extreme class imbalance (0.78% test prevalence). A threshold targeting 80% sensitivity achieved sensitivity 80.0% [33.3-100.0%], specificity 87.4% [84.8-89.9%], positive predictive value 4.8% [1.1-9.9%], and negative predictive value 99.8% [99.4-100.0%], detecting 4 of 5 VAP cases with approximately 80 false alarms (12.6% false positive rate). Brier score was 0.0078. Feature importance identified baseline P:F ratio as the dominant predictor (41.3% total gain), followed by ventilator mode (26.1%), secretion amount (13.2%), secretion description (9.1%), procalcitonin (5.9%), and FiO2; (4.5%). Conclusions ADVISE demonstrates that baseline oxygenation trajectory and ventilatory support patterns - derived exclusively from routinely charted ICCA variables - can identify admissions at risk of VAP-related physiological deterioration with meaningful discrimination (AUROC 0.874) despite severe class imbalance. The 80% sensitivity operating point offers a clinically actionable alert rate (12.6% FPR), supporting integration into existing ICU workflows. This proof-of-concept study establishes feasibility; multi-site prospective validation is required before clinical deployment.

ABSTRACT OBJECTIVES To examine whether psychological safety and power distance are associated with medical researchers' well-being, and whether these associations operate through team inclusiveness and conflict. DESIGN Cross-sectional survey study. SETTING A biomedical research institute at a major UK university. PARTICIPANTS 133 medical researchers from 17 teams, including 20 principal investigators and 113 team members. MAIN OUTCOME MEASURES Job satisfaction, life satisfaction, intrinsic motivation, and psychological detachment. Mediators were dimensions of team inclusiveness and team conflict. RESULTS Psychological safety had no significant direct associations with job satisfaction, life satisfaction, intrinsic motivation, or psychological detachment, but showed several indirect associations through researchers' team experiences. It was indirectly associated with higher job satisfaction, life satisfaction, and intrinsic motivation primarily through greater integration of differences, inclusion in decision making, or more constructive forms of conflict (bs=.23-.38, ps=.032-<.001).For psychological detachment, psychological safety showed conflicting indirect associations: it had the potential to support detachment through greater integration of differences and lower avoidant conflict (bs=.21-.56, ps=.054-.002), but to undermine detachment through greater inclusion in decision-making (b=-.26, p=.082). Power distance showed a different pattern. Most notably, it was positively associated with psychological detachment (b=.54, p=.062). However, power distance was indirectly associated with lower job satisfaction, life satisfaction, and intrinsic motivation, primarily through reduced integration of differences and greater dominating conflict (bs=-.14 to -.19, ps=.068-.020). CONCLUSIONS Common assumptions about psychological safety and power distance should be revisited. Psychological safety did not show strong direct benefits for researcher well-being, whereas power distance was not uniformly harmful and was positively associated with psychological detachment. A more nuanced understanding of both cultural dimensions is needed in medical research teams.

Background: The Glasgow Coma Scale (GCS) is a universal neurologic severity score in the intensive care unit and is incorporated into APACHE, SOFA, mortality prediction models, ICU benchmarking, and quality metrics. In mechanically ventilated patients, however, the verbal component cannot be assessed. Common conventions, including assigning a normal total GCS of 15 or excluding patients with missing verbal scores, may misclassify the sickest patients as neurologically normal or remove them from analysis. Objective: To quantify non-assessable verbal GCS examinations after acute brain injury and determine how different handling conventions affect severity scoring and mortality-model performance across two independent critical care databases. Materials and Methods: We conducted a retrospective cohort study of adults with acute brain injury during their first ICU stay in MIMIC-IV, with replication in eICU-CRD. A verbal examination was considered non-assessable when documented as No Response-ETT. We measured the burden and determinants of non-assessability, compared the MIMIC-IV derived GCS convention with a component-aware GCS, and evaluated mortality-model handling strategies. Results: Among 14,230 patients, 45.2% had a non-assessable verbal examination, and 47.5% of ventilated patients had no assessable verbal score in the first 24 hours. Non-assessability was strongly associated with mechanical ventilation and mortality. The MIMIC-IV derived GCS assigned a score of 15 to 42.9% of patients and placed 11.6% in the lowest severity category despite eye and motor findings consistent with GCS [&le;]9. Complete-case handling excluded 28.5% of patients, who accounted for 50.2% of deaths. Similar distortions were observed in eICU-CRD/APACHE across 171 hospitals. Discussion: Default-to-normal scoring can make severely ill intubated patients appear neurologically normal, while complete-case analysis removes the highest-risk patients. Conclusion: Non-assessable verbal GCS in mechanically ventilated patients should be explicitly flagged and reported in ICU severity scores, risk-adjusted mortality models, and benchmarking systems.

BackgroundOnline professional learning offers a scalable alternative to traditional face-to-face learning, but there are doubts regarding how well it works and when it works best. This review assessed the effectiveness of online professional learning interventions on healthcare professionals knowledge and skill acquisition. MethodsWe conducted a systematic review and meta-analysis of randomised controlled trials that compared online professional learning against static controls or face-to-face controls. We searched MEDLINE Complete, Scopus, Embase, CENTRAL, and PsycINFO from inception to January 31, 2025. Eligible studies included practising healthcare professionals in any clinical setting that measured knowledge or skill acquisition related to patient care. Data was extracted in duplicate, with disagreements resolved through discussion or by a third reviewer. We used multilevel meta-analyses to estimate the overall effect size and conducted moderation analyses for pre-specified factors. The study protocol was pre-registered on the Open Science Framework (OSF; https://osf.io/46zav). FindingsOf 55,376 records; 171 studies (391 effects, 25,412 participants) met the inclusion criteria. Online learning significantly improved knowledge and skill acquisition compared to static controls (g = 0.93, 95% CI [0.78,1.07], p < 0.001; I{superscript 2} = 89.8%), with larger effects in lower-middle income countries (g = 1.30, 95% CI [0.88, 1.72]) than in high income (g = 0.75, 95% CI [0.63, 0.86]). Online learning also significantly improves outcomes compared to face-to-face instruction (g = 0.45, 95% CI [0.31,0.59], p < 0.001; I{superscript 2} = 85.92%), with larger effects for knowledge outcomes (g = 0.46, 95% CI [0.33, 0.59]) than skills outcomes (g = 0.20, 95% CI [0.04, 0.36]). Effects did not differ significantly by profession, clinician experience, clinical setting, intervention characteristics or the learning design features (all p > 0.05). No studies had low overall risk of bias, and some evidence of publication bias was found. InterpretationFrom this body of evidence, we identified that online learning appears to improve healthcare professionals knowledge and skill acquisition, exceeding traditional teaching methods. Healthcare organisations can be confident implementing or expanding online professional learning to improve knowledge and skill acquisition. FundingNo funding

BACKGROUND: Critical care pharmacists (CCPs) reduce adverse drug events (ADEs) and mortality in the intensive care unit (ICU). Board certification is the established professional standard for CCPs but its impact on ICU patient outcomes, including its relationship between CCP characteristics and workload, remain unclear. The purpose of this study was to evaluate the association between pharmacist board certification, CCP workload characteristics, and patient outcomes. METHODS: This was a pre-planned analysis of the multicenter, observational Optimizing Pharmacist Team Integration for ICU Patient Management (OPTIM) study, including adult ICU patients cared for by CCPs. Patients cared for exclusively by board certified pharmacists on every ICU day were categorized as the BCP group; those with at least one day of care from a non board certified pharmacist comprised the non BCP group. The primary outcome was hospital mortality; secondary outcomes included the hazard of discharge alive (HDA) from the ICU and hospital. Multivariable logistic regression was used to evaluate the association between BCP and mortality; Fine-Gray competing risk models were used to assess the relationship between BCP and ICU and hospital HDA. RESULTS: A total of 201 pharmacists (184 BCPs; 17 non BCPs) from 63 institutions caring for 20,537 ICU patients were included. Care provided exclusively by a BCP (vs. >/= 1 day by a non-BCP) was associated with lower mortality (OR 0.80, 95% CI 0.69 to 0.92, p=0.002) and both a higher ICU HDA (HR 1.08, 95% CI 1.03 to 1.13, p<0.001) and hospital HDA (HR 1.19, 95% CI 1.13 to 1.26, p<0.001). CONCLUSION: Daily ICU care delivered by pharmacists with board certification was independently associated with reduced mortality and improved hazard of discharge alive from the ICU. Board-certified pharmacists may enhance the quality and/or efficiency of critical care pharmacy services. These findings support the role of board certification as a modifiable factor to improve patient outcomes and optimize workload in the ICU.