Critical Care

BackgroundSepsis is a major public health challenge, and reliable biomarkers are essential for distinguishing sepsis from other conditions. Neutrophil Gelatinase-Associated Lipocalin (Neutrophil gelatinase-associated lipocalin (NGAL)) has shown promise as a diagnostic marker due to its role in the immune response. This study evaluates plasma NGAL as a diagnostic tool at the time of ICU admission. MethodsWe analysed plasma NGAL and C-reactive protein (CRP) levels in 4732 adult patients admitted to four ICUs between 2015 and 2018. All patients were retrospectively screened for Sepsis-3 criteria at ICU admission. The discriminative performance of NGAL and CRP for sepsis was assessed using receiver operating characteristic (ROC) analysis, with NGAL levels adjusted for Chronic kidney disease (CKD) and age. Patients were stratified by renal function. ResultsPlasma NGAL levels were significantly higher in septic patients (p<0.001). For the whole cohort, NGAL alone yielded an Area under the curve (AUC) of 0.67 (Confidence interval (CI) 0.66-0.69), CRP yielded an AUC of 0.72 (CI 0.71-0.73, p<0.001), and combining NGAL with CRP nominally improved discriminative performance (AUC 0.74 vs 0.72, p<0.001). Stratified analyses indicated that NGAL, together with CRP, significantly outperformed CRP alone in patients with no kidney injury and those with Acute Kidney Injury (AKI) only. In contrast, differences were not significant in patients with CKD only or CKD and AKI. ConclusionIn this large cohort, NGAL showed modest discrimination for sepsis, with a nominal improvement when combined with CRP. These findings do not indicate that NGAL meaningfully improves sepsis diagnosis in the ICU.

PurposeSepsis-associated immunothrombosis significantly contributes to high mortality, yet the role of N-glycosylation in this process remains poorly understood. This study aimed to comprehensively profile the plasma N-glycosylation landscape in sepsis and elucidate how its specific reprogramming in the complement and coagulation cascades influences immunothrombotic balance and patient outcomes. MethodsWe performed in-depth 4D-DIA proteomic and N-glycomic analyses on plasma from 43 sepsis patients and 9 healthy controls. Differential expression, weighted gene co-expression network analysis (WGCNA), and protein-glycosylation correlation analyses were used to characterize molecular features. Clinical relevance was assessed via correlation and survival analyses. ResultsExtensive N-glycosylation reprogramming was observed in sepsis plasma,with marked enrichment in complement and coagulation pathways(KEGG p=7.76x10- {superscript 2}{superscript 1}).Pro-coagulant proteins(eg,vWF,fibrinogen)showed increased abundance together with enhanced site-specific glycosylation,potentially amplifying their activity.In contrast,key anticoagulant proteins(eg,SERPINC1)displayed unchanged glycosylation at critical sites despite abundance changes,which may impair function.Survival analysis revealed distinct prognostic values of glycoproteins and specific glycosylation sites.For instance,high vWF protein levels predicted mortality(HR=2.83),whereas elevated glycosylation at vWF N211 was associated with improved survival(HR=0.135),suggesting a negative regulatory role.These glycosylation markers correlated closely with disease severity and prognosis,representing potential early-warning biomarkers independent of current clinical coagulation indicators. ConclusionOur study demonstrates widespread reprogramming of the plasma proteome and N-glycome in sepsis.We propose that decoupling of protein function from abundance through N-glycosylation in the complement-coagulation network contributes to immunothrombotic imbalance.Specific N-glycosylation sites may serve as novel prognostic biomarkers,offering new perspectives for early risk stratification and glycosylation-targeted therapies in sepsis. Key PointsO_LISepsis plasma exhibits specific N-glycosylation reprogramming overwhelmingly focused on the complement and coagulation cascade. C_LIO_LIA dominant "glycosylation-dominated co-upregulation" mode in procoagulant factors, coupled with a "silent" glycosylation state in key anticoagulants, drives prothrombotic imbalance. C_LIO_LISite-specific N-glycosylation levels provide prognostic information distinct from, and often superior to, their carrier protein abundance, offering novel early-risk biomarkers. C_LI

RationaleAutonomic dysfunction is a hallmark of sepsis pathophysiology, yet its quantification remains challenging. Multiscale entropy (MSE) derived from heart rate variability (HRV) offers a dynamic measure of physiological complexity and may serve as a biomarker of early deterioration associated with subsequent organ failure, vasopressor escalation, or mortality. ObjectiveTo determine whether MSE computed across multiple temporal scales during the first 24 hours of Intensive Care Unit (ICU) admission is associated with short-term mortality and longer-term organ dysfunction in patients with sepsis, and whether these relationships vary across vasopressor exposure. Unlike prior studies that focused on short-term HRV metrics, we applied MSE across multiple temporal scales and incorporated these features into machine learning models to evaluate their prognostic utility in septic shock. MethodsThis retrospective cohort study included adult ICU sepsis patients at Emory University Hospital from January 2016 to December 2019. Of 2,076 eligible patients, 958 were propensity matched into two cohorts: fluids-only and fluids-plus-vasopressor, with norepinephrine as the primary vasopressor. High-resolution electrocardiogram (ECG) waveforms were analyzed to compute MSE across 20 temporal scales. Machine learning models using (1) MSE features alone and (2) MSE combined with demographic and vital sign data (MSE-DV) were compared against traditional HRV measures based model and severity of illness scores for predicting outcomes. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC), with a primary outcome of mortality at day 7 and secondary outcome of persistent organ dysfunction at day 28. ResultsIn the fluids-plus-vasopressor cohort, MSE-based models demonstrated superior predictive performance for 7-day mortality (AUROC 0.84) compared to severity of illness scores (AUROC 0.64). MSE-DV models also predicted organ dysfunction including 28-day renal (AUROC 0.75), neurological (AUROC 0.79), and respiratory (AUROC 0.71) dysfunction. Patients receiving second-line and third-line vasopressors and corticosteroids exhibited progressively lower MSE values, particularly at mid-range and long-range scales. ConclusionMSE features in the first 24 hours of ICU stay predict mortality and organ dysfunction with higher discrimination than traditional severity of illness scores. Future work should validate these findings, assess longitudinal MSE trends, and race-specific autonomic patterns to refine predictive models.

ImportanceRecent reports have highlighted an intense influenza activity related to the circulation of the influenza A(H3N2) subclade k variant. There is no data available on the impact of the emergence of H3N2 subclade k on the severity of the 2025-2026 epidemic or on the clinical phenotype of patients requiring admission to the intensive care unit (ICU). ObjectiveTo compare the clinical presentation, hospital mortality and virological characteristics of patients with laboratory-confirmed influenza infection included in French intensive care units during the 2025-2026 epidemic season with those of patients admitted during the 2024-2025 season. We also aimed at measuring the impact of the A(H3N2) subtype on hospital mortality during the 2025-2026 season. DesignProspective, multicenter, observational SEVARVIR cohort study including patients admitted during the 2024-2025 and 2025-2025 influenza seasons. SettingForty-two French ICUs ParticipantsAdult patients with laboratory-confirmed influenza infection Interventionsnone Main Outcomes and MeasuresThe primary outcome measure was in-hospital mortality. ResultsPatients admitted in intensive care units for influenza in 2024-2025 (n=360) and 2025-2026 (n=325) were included in the French nationwide prospective multicentre SEVARVIR study. There was no significant difference in day-28 mortality between the seasons (12.7%, n=45/355 vs 16.5% n=28/170; p=0.28). In the 2025-26 season, 49% had the A(H1N1) subtype and 51% the A(H3N2) subtype (k subclade: 77%). The univariable Cox analysis revealed that patients infected with A(H3N2) viruses were at greater risk of death over time. Multivariable Cox analysis revealed that during the 2025-2026 season, age (adjusted hazard ratio, aHR=1.05 [1.00;1.11]; p=0.046) and the clinical frailty scale (aHR=1.82 [1.26;2.72]; p=0.001) were associated with an increased risk of death. The A(H3N2) subtype was not associated with an increased risk of death (aHR=1.13 [0.32;4.51]; p=0.85). Phylogenetic analyses from our ICU cohort together with 300 contextual sequences from community-acquired influenza cases collected during the same period showed no clustering according to severity. Conclusions and RelevanceThis French national prospective observational study, found that the emergence of the influenza A(H3N2) subclade K was associated with an increased risk of death in univariable but not multivariable analysis, adjusting for host-related factors. Trial RegistrationNCT051625 Key PointsQuestion: What impact did the 2025-26 influenza epidemic and the A(H3N2) variant have on the mortality of patients admitted to intensive care units? Findings: In this prospective, nationwide cohort study of 685 patients admitted to intensive care units with severe influenza during the 2024-25 or 2025-26 seasons, no difference in hospital mortality was observed between the two seasons. Patients infected with the A(H3N2) virus, 77% of which corresponded to clade k, were at higher risk of death in univariable but not in multivariable analysis after adjusting for age and clinical frailty scale. Meaning: Patients in intensive care units with severe A(H3N2) infection during the 2025/2026 season were not at higher risk of death after adjusting for confounding variables.

BackgroundPulse oximeters are typically validated on cohorts of 200-500 subjects under controlled conditions. Whether these cohorts capture the demographic heterogeneity of national clinical practice -- and whether measurement error is associated with patient outcomes -- has not been established at scale. MethodsWe analyzed paired SpO2/SaO2 readings from three independent sources spanning 209 U.S. hospitals: MIMIC-IV (1 hospital; 12,934 ICU stays), eICU-CRD (208 hospitals; 55,178 stays), and the Open Oximetry Repository (PhysioNet; 52.4 million readings with continuous melanin and perfusion indices). Bias was defined as SpO2 - SaO2. Hidden hypoxemia (SpO2 [&ge;] 94% with SaO2 < 88%) was assessed per ICU stay. Mortality was compared between hidden-hypoxemia-positive and -negative stays with multivariable logistic regression adjusting for age, sex, race, and four laboratory severity markers (cluster-robust SEs by hospital). Sensitivity analyses included landmark restriction (first 48 hours), lactate stratification, alternate thresholds, and patient-level aggregation. PPG signal quality was assessed in 125 ICU patients with demographic-linked waveform data. ResultsBias was minimal at normal perfusion but amplified under low perfusion in high-melanin patients, consistent with known optics: at very low perfusion x high melanin x severe hypoxia, mean bias reached +12.8% (n = 458,571), with 47% of readings constituting hidden severe hypoxemia. National bias in African American patients was +2.76% (n = 529,541; 208 hospitals), 62% higher than academic estimates. Across 55,178 eICU stays, hidden hypoxemia was associated with approximately doubled mortality after adjustment for age, sex, race, and illness severity (adjusted OR 1.86, 95% CI 1.69-2.04, p < 0.001), consistent across all racial groups. Hidden hypoxemia was not a pre-terminal phenomenon: 63% of events occurred >48 hours before death (median first event: 15.3 hours; mean time to death: 151 hours), and the association persisted in landmark analysis (first 48 hours only), in patients with normal lactate (adjusted OR 1.87, 95% CI 1.61-2.16), and when both restrictions were applied simultaneously (16.5% vs. 11.1%). Waveform analysis (n = 125) showed no fixed racial difference in baseline PPG AC/DC ratio (Black: 0.299, White: 0.273), suggesting the signal deficit is conditional on perfusion state. Full extraction (n = 1,545) is in progress. ConclusionsIn this multicenter retrospective analysis, national pulse oximetry variance exceeded published benchmarks and was associated with approximately doubled ICU mortality, replicated across 209 U.S. hospitals. Hidden hypoxemia was not a pre-terminal artifact: events occurred throughout the ICU stay at a constant rate, and mortality associations persisted in landmark and lactate-stratified analyses. These findings suggest that current regulatory validation standards may underestimate the real-world prevalence of demographic bias in pulse oximetry, and that perfusion-dependent mechanisms may offer a target for algorithmic correction.

Sepsis is a complex condition with a time-dependent evolution. Longitudinal biomarker dynamics could help us to better characterise sepsis. We hypothesised that the kinetics of biomarkers are associated with sepsis and with the intensity of organ dysfunction, and may have predictive capacity for patient survival. This single-centre, prospective, observational study included adult patients presenting to the Emergency Department (ED) with suspected infection. Patients were included in the study if they had a National Early Warning Score 2 (NEWS 2) of 3 or higher. Blood samples were obtained at baseline, 4hs and 24 hs. Linear mixed models were constructed to analyse the association between biomarker concentrations over time, sepsis diagnosis and organ dysfunction severity. Joint models were used to evaluate the predictive ability of individual biomarker kinetics during the first 24 hours for in-hospital mortality Of 214 screened patients, 173 patients were analysed, and 137 (79%) developed sepsis. Linear mixed models revealed time-dependent decreases in IL10 ({beta} -0.016, 95%CI -0.028 to -0.004), IL1RN ({beta} -0.014, 95%CI -0.024 to -0.004), and IL6 ({beta} -0.012, 95%CI -0.024 to 0.00). Sepsis was associated with higher IL1RN ({beta} 0.378, 95%CI 0.153-0.603), and TNFRSF1A ({beta} 0.40, 95%CI 0.21-0.58); only models evaluating IL6 showed significant interaction between sepsis and time ({beta} -0.14, 95%CI -0.028 to 0.00). SOFA correlated with elevated IL10 ({beta} 0.048, 95%CI 0.021-0.075), IL1RN ({beta} 0.044, 95%CI 0.017-0.071), CCL2 ({beta} 0.046, 95%CI 0.021-0.071), TNFRSF1A ({beta} 0.050, 95%CI 0.030-0.070), and PCT ({beta} 2.63, 95%CI 1.32-3.93); the interaction between SOFA score and time was significant only for IL6 ({beta} -0.003, 95%CI -0.005 to -0.001). Joint survival models (adjusted for age and highest SOFA) identified IL8 (HR 0.655, 95% CrI 0.582-0.728), TNFRSF1A (HR 0.505, 95% CrI 0.419-0.682), and PCT (HR 1.004, 95% CrI 1.001-1.008) as predictors. ConclusionSepsis diagnosis and severity of organ dysfunction may be associated with higher levels and kinetic values of inflammatory biomarkers such as IL1RN and TNFRSF1A. IL6 levels showed a significant association for the interaction of time with both sepsis diagnosis and SOFA score. TNFRSF1A, IL8 and PCT dynamics were found to be associated with survival and could be useful in developing prognosis tools.

BACKGROUNDDelirium is common in critically ill adults but often goes unrecognized and undertreated. Little is known about the perceptions of ICU nurse and physician leaders regarding ICU delirium detection and management and the potential role of objective continuous delirium monitoring to facilitate ICU delirium care. RESEARCH QUESTIONWhat are the perceptions of ICU leaders regarding the current challenges associated with delirium recognition and management and the potential benefits of continuous delirium monitoring? STUDY DESIGN AND METHODSWe conducted a blinded, cross-sectional, electronic survey of ICU leaders across the U.S., including physician directors and nursing managers with [&ge;]3 years of ICU leadership experience. We asked about perceptions of the effectiveness of current delirium clinical assessment tools, current delirium detection and management challenges, and how an objective, continuous delirium monitoring system might impact clinician practice and patient outcomes in their ICU. RESULTSAmong the 81 respondents (62 physicians, 19 nurses), most (76%) reported that recommended delirium assessment tools (CAM-ICU, ICDSC) are used in their ICUs, though there were mixed perceptions on how reliably they are conducted. A majority (63-90%) perceived that current bedside assessments delay and limit the recognition of ICU delirium. Nearly all (89%) agreed an objective delirium monitoring tool would be more clinically valuable than current delirium assessment tools and that it would support real-time, delirium management by clinicians. CONCLUSIONSICU leaders perceive that there are limitations to using clinical delirium assessment tools in ICU patients to effectively detect and manage ICU delirium. Most felt that an objective delirium monitor could facilitate delirium detection and potentially expedite appropriate delirium management in patients.

ObjectiveDespite substantial variability in the severity of post-anoxic encephalopathy, all comatose patients after cardiac arrest are usually treated according to the same standardized intensive care protocol, including sedation, mechanical ventilation, and targeted temperature management (TTM). We hypothesize that patients with a favourable EEG pattern (continuous EEG within 12 hours after cardiac arrest) may not benefit from prolonged sedation and TTM. We studied the feasibility and safety of early cessation of sedation and TTM in this subgroup. MethodsWe conducted a non-randomized, controlled intervention study including 40 adult patients admitted to the ICU with postanoxic encephalopathy after cardiac arrest and an early (< 12 hours) favourable EEG pattern. The control group received standard care with sedation and TTM for at least 24-48 hours, whereas the intervention group underwent early cessation of sedation and TTM as soon as possible after establishing a favourable EEG, followed by weaning from mechanical ventilation. The primary outcome was duration of mechanical ventilation. Secondary outcomes included ICU length of stay, total sedation time, number of ICU complications, and neurological outcomes at 3 and 6 months. ResultsDuration of mechanical ventilation was significantly shorter in the intervention than in the control group (median 12 vs 28 h, p < 0.001). Median ICU length of stay and median total sedation time were also reduced by more than 50% in the intervention group, from respectively 2.5 to 1.2 days (p = 0.001) and 27 to 12 h (p < 0.001). There was no increase in ICU complications in the intervention group. No statistically significant differences in neurological outcomes at 3 or 6 months were observed. ConclusionEarly withdrawal of sedation is feasible and safe in patients with an early favourable EEG following cardiac arrest. The study was underpowered to detect possible differences in long-term neurological recovery. SignificanceShortening sedation and mechanical ventilation is likely to result in direct reductions in healthcare costs and contribute to more appropriate care. Larger studies are needed to evaluate the impact on long-term neurological outcomes.

ObjectiveTo systematically identify and characterize methodological heterogeneity in sepsis case detection methods using the MIMIC-III database or the eICU-CRD, and to quantify the resulting variability in sepsis detection rates. Materials and MethodsWe conducted a PRISMA-guided systematic review of PubMed and Web of Science (2016-2024), and stratified studies by cohort definition to obtain comparable subsets. We extracted information on sepsis case detection methodology across six domains: parameter coverage, temporal windows, aggregation methods, missing data handling, SOFA calculation, and infection identification. For studies with available source code, we performed detailed code analysis extracting implementation decisions across all six domains. ResultsOf 396 screened publications using the MIMIC-III or the eICU-CRD database, 64 studies met our inclusion criteria. Reported sepsis detection rates ranged from 3.4 % to 65.2 %. Documentation of sepsis case definition methodology was provided in a minority of studies across all domains, including SOFA calculation (53.1 %), infection detection (42.2 %), temporal windows (37.5 %), aggregation methods (26.6 %), and missing data handling (17.2 %). Source code analysis revealed differences in baseline SOFA definitions, temporal alignment, and infection detection timing. DiscussionThe detection of sepsis cases is a key step in critical care research for validating sepsis prediction models. However, implementation of the current sepsis definition varies substantially, thereby undermining research reproducibility. ConclusionTo improve the reproducibility and robustness of sepsis prediction models, we recommend standardized reporting of sepsis case definition methodology and the publication of version-controlled source code.

ObjectivesTo develop and validate pediatric adaptations of the Venous Excess Ultrasound Score (P-VExUS) for noninvasive estimation of central venous pressure (CVP) in critically ill children. DesignProspective observational study. SettingPICU of a tertiary-care teaching hospital. PatientsFifty-six mechanically ventilated children (median age 7.4 months, median weight 6.0 kg) with central venous catheters. InterventionsNone. Measurements and Main ResultsVenous Doppler ultrasonography of the inferior vena cava, hepatic, portal, and intrarenal veins was performed at the bedside. Two P-VExUS models were tested: (1) a categorical grading system (0-III) and (2) a semiquantitative point-based score (0-7). Both models showed significant associations with CVP. For predicting elevated CVP (>12 mmHg), model 1 achieved an AUROC of 0.74 (95% CI 0.61-0.85) with 45% sensitivity and 98% specificity, while model 2 demonstrated superior accuracy with an AUROC of 0.94 (95% CI 0.84-0.98), sensitivity 82%, and specificity 91% (p < 0.001). For detecting low CVP (<7 mmHg), model 2 also outperformed model 1 (AUROC 0.80 vs. 0.69, p = 0.02). Among individual venous Doppler components, intrarenal veins had the highest discriminative ability (AUROC 0.92), followed by hepatic (0.89) and portal (0.80) veins. ConclusionsTwo pediatric-specific P-VExUS models were feasible and accurate for estimating CVP in critically ill children. The point-based model (model 2) demonstrated superior diagnostic performance, supporting its potential as a noninvasive tool to assess venous congestion at the bedside. Research in ContextO_LIVenous congestion, reflected by elevated central venous pressure (CVP), is associated with adverse outcomes in critically ill children, including mortality and renal dysfunction. C_LIO_LIThe Venous Excess Ultrasound Score (VExUS) is validated in adults, but pediatric-specific adaptations and cutoff values remain poorly defined. C_LIO_LIThere is a need for noninvasive, bedside tools to estimate CVP in children and guide fluid management in the PICU. C_LI What This Study MeansO_LIThis study validates pediatric-specific adaptations of the Venous Excess Ultrasound Score (P-VExUS) for estimating CVP in critically ill children. C_LIO_LIThe semiquantitative point-based model provided more consistent and accurate discrimination of venous congestion compared with categorical grading. C_LIO_LIThese findings highlight the feasibility and potential clinical utility of venous Doppler ultrasonography as a noninvasive bedside tool in the PICU. C_LI

ObjectiveTo develop and validate a predictive model incorporating behavioral telemetry signals--documentation pattern anomalies derived from routine EHR charting--alongside clinical variables for ICU mortality prediction in patients with low acute physiologic derangement. Materials and MethodsRetrospective cohort study of 46,002 adult ICU stays from MIMIC-IV v3.1 (2008-2022) with SOFA scores 0-2, excluding neurological units. We extracted 66 variables spanning demographics, acuity, behavioral telemetry, clinical enrichment, and temporal factors. Progressive logistic regression models (M1-M7) were compared using cross-validation, DeLong tests, net reclassification improvement, and calibration analysis. ResultsOverall mortality was 9.34% (4,295 deaths). The clinical model (M5) achieved cross-validated AUROC 0.691 versus 0.639 for demographics alone (M2; {Delta}AUROC = 0.052, DeLong p = 4.41x10-47). NRI was 24.3%. Discordant care patients received 30.5% more chart events than concordant patients, with the sole deficit in neurological assessments (-15.4%), refuting the neglect hypothesis. Kaplan-Meier analysis confirmed survival separation (log-rank {chi}2 = 138.6, p = 5.32x10-32). In the most conservative subgroup (SOFA 0, no sedation, no ventilation, N = 11,158), orientation omission remained associated with mortality (adjusted OR 1.52, p = 0.027). DiscussionDeep sedation and mechanical ventilation function as mediators on the causal pathway rather than traditional confounders; the discordant care signal retains significance after full sedation adjustment. ConclusionDocumentation pattern analysis adds measurable predictive value for ICU mortality risk stratification and represents a novel signal for real-time EHR-based clinical decision support.

BackgroundQuality measurement in intensive care emphasizes task completion--whether assessments were documented and protocols followed. Electronic health record (EHR) systems capture these signals in real time, yet current metrics cannot distinguish task completion from cognitive clinical engagement. A prior analysis demonstrated that omission of orientation assessment predicted a 4.29-fold increase in hospital mortality among low-acuity ICU patients [1]. Whether combining this marker with routine task-completion data yields a computable phenotype with independent prognostic value has not been studied. ObjectiveTo define, validate, and characterize "discordant care"--a computable EHR phenotype defined as completion of [&ge;]6 of 8 routine nursing assessments without orientation assessment documentation--as a predictor of hospital mortality, distinguishing patient-level confounding from care process signal. MethodsRetrospective cohort study using MIMIC-IV v3.1 (2008-2022), including 46,004 adult ICU stays with SOFA scores 0-2 and length of stay [&ge;]24 hours in non-neurological ICUs. Primary exposure: discordant care, computed from structured nursing flowsheet data within 24 hours of admission. Primary outcome: hospital mortality. Progressive covariate adjustment included mechanical ventilation, sedation, and diagnosis. ResultsDiscordant care was present in 8891 patients (19.3%), with 69.7% mechanically ventilated versus 25.3% of concordant patients. Two overlapping signals were identified: a patient-level signal driven by ventilation/sedation (full adjustment OR 1.19, 95% CI 1.09-1.30) and a care process signal in non-ventilated patients (OR 2.14, 1.87-2.44; N=30,314). Among non-ventilated SOFA 0 patients, OR was 2.60 (2.13-3.18; N=16,295). The signal was present across all 7 major diagnosis categories. Quantitative bias analysis indicated unmeasured delirium could attenuate but likely not fully explain the non-ventilated signal. ConclusionsDiscordant care identifies two phenomena: a patient-level signal from ventilation/sedation and a care process signal where assessable patients receive routine care without cognitive engagement (OR 2.14-2.60). This care process signal is invisible to existing quality metrics and detectable in real time. Prospective validation with systematic delirium screening is needed.

The red cell distribution width (RDW) is a recognized prognostic marker in sepsis, yet its dynamic changes over time and their relationship with outcomes remain unexplored. This study aimed to identify distinct RDW trajectories during the early phase of sepsis and evaluate their association with mortality. We conducted a retrospective cohort study using data from the MIMIC-IV database (n=3,813) as the derivation cohort and from the First Affiliated Hospital of Kunming Medical University (n=467) for external validation. Sepsis patients with at least seven RDW measurements within the first ten days of hospitalization were included. Group-based trajectory modeling (GBTM) was employed to identify RDW trajectories. A three-trajectory model was selected based on model fit indices and clinical interpretability: Trajectory 1 (Slow-Decrease, 32.97%), Trajectory 2 (Slow-Increase, 43.30%), and Trajectory 3 (Fluctuating-Rapid Decrease, 23.73%). In the our study, Cox models adjusted for confounders revealed that, compared to Trajectory 1, Trajectory 3 was independently associated with significantly increased 30-day (HR 1.47, 95% CI 1.17-1.84) and 90-day mortality (HR 1.54, 95% CI 1.25-1.88). Conversely, Trajectory 2 was associated with the most favorable survival rates. Kaplan-Meier analysis consistently showed the highest mortality in the Trajectory 3 group. External validation confirmed the models robustness and the consistent prognostic value of the identified trajectories. We conclude that dynamic RDW trajectories, readily identifiable from routine clinical data, provide significant prognostic information beyond single-time-point measurements and can aid in the risk stratification of sepsis patients.

ObjectiveTo compare the efficacy and safety of etomidate versus ketamine as induction agents for rapid sequence intubation in critically ill adults, focusing on 28-day mortality and post-intubation hypotension. Data SourcesPubMed, Embase, and the Cochrane Library were systematically searched from inception to January 2026. Reference lists of included studies were also manually screened. Study SelectionWe included randomized controlled trials (RCTs) comparing single-dose intravenous ketamine versus etomidate for emergency rapid sequence intubation in critically ill adults ([&ge;] 18 years) in non-operating room settings (e.g., intensive care unit or emergency department). Data ExtractionTwo investigators independently screened records, extracted data using a standardized form and assessed the risk of bias using the RoB 2 tool. The certainty of evidence was evaluated using the GRADE framework. Data SynthesisSix RCTs comprising 4,108 patients (2,046 assigned to ketamine and 2,062 to etomidate) were included. The pooled analysis showed no statistically significant difference in 28-day mortality between the ketamine and etomidate groups (39.0% vs. 40.3%; relative risk [RR] 0.96; 95% CI, 0.89-1.03; p=0.29; I{superscript 2}=11%). In a prespecified subgroup analysis of patients with sepsis (n=1,546), mortality also did not differ significantly (RR 0.94; 95% CI, 0.86-1.03). However, ketamine was associated with a statistically significant increase in the incidence of post-intubation hypotension (14.2% vs. 11.3%; RR 1.25; 95% CI, 1.01-1.53; p=0.04; I{superscript 2}=0%). No significant differences were observed regarding peri-intubation cardiac arrest, first-attempt intubation success, or ventilator- and intensive care unit-free days. ConclusionsThere is no statistical difference in 28-day mortality between etomidate and ketamine for emergency intubation in critically ill adults, including those with sepsis. The higher incidence of post-intubation hypotension with ketamine suggests etomidate presents a more favorable hemodynamic safety profile in this setting. Key pointsO_ST_ABSQuestionC_ST_ABSDoes the choice between etomidate and ketamine for emergency intubation in critically ill patients impact 28-day mortality? FindingsIn this systematic review and meta-analysis of randomized controlled trials, there was no statistically significant difference in 28-day mortality between patients induced with ketamine (39.0%) and those induced with etomidate (40.3%). MeaningThe use of etomidate versus ketamine for rapid sequence intubation does not alter 28-day mortality, indicating that the choice of induction agent should be individualized.

There is an unmet need to identify biomarkers of active thyroid eye disease (TED). scRNAseq revealed that orbital fibroblasts from orbital decompressions in people with TED express high levels of thyroid hormone receptors, growth factor receptors, including insulin-like growth factor 1 receptor (IGF1R), and extracellular matrix proteins including SPARC (osteonectin), whereas orbital fat endothelial cells expressed thyroid peroxidase (TPO). SPARC was significantly raised in the serum of people with thyroid disease compared to healthy controls. Furthermore, those with moderate, severe and sight threatening TED had higher SPARC levels than those with thyroid disease but free of TED or mild TED. Free-triiodothyronine (FT3) levels were positively correlated with SPARC in moderate-sight threatening TED. SPARC and IGF1 were positively correlated across people with thyroid disease alone, as well as TED. Thyroid stimulating hormone (TSH) levels were negatively correlated with SPARC in moderate-sight threatening TED. When participants were followed longitudinally, SPARC decreased after the active phase of TED. At the protein level, immunohistochemistry indicated that SPARC was heterogeneously expressed by fibroblasts in both control and TED orbital fat. SPARC is a key mediator of fibrosis and deposition of extracellular matrix and the correlation of SPARC serum levels to TED status and FT3 make it a promising biomarker of active TED.

BackgroundNeonatal jaundice management increasingly relies on transcutaneous bilirubinometry (TcB), yet discrepancies with serum bilirubin (TSB) have limited its clinical reliability. This study introduces Skin Residual Bilirubin Volume (SRBV) as a physiologically grounded framework to enhance TcB interpretation. ObjectiveTo evaluate SRBV as an explanation for TcB-TSB discordance and assess whether incorporating SRBV improves the interpretability and reliability of TcB measurements during diagnosis, phototherapy, and recovery. MethodsTcB readings (MBj20) were calibrated against laboratory TSB in non-jaundiced neonates (TSB <3 mg/dL). Neonates undergoing phototherapy were monitored using paired TcB measurements before and after treatment breaks (TBL-out and TBL-return). TSB was measured before treatment, at mid-treatment, and prior to discharge. Patterns of TcB-TSB disparity and an observed reproducible Recovery Value Flip (RVP) phenomenon were analysed. ResultsAcross 102 neonates, TBL consistently equalled or exceeded TSB, supporting the additive SRBV model. Early in phototherapy, TBL-return > TBL-out, indicating persistent cutaneous bilirubin. A reproducible RVP occurred mid-treatment, after which TBL-return < TBL-out coincided with sustained bilirubin decline. Fractional SRBV contribution increased with baseline bilirubin and persisted into recovery, demonstrating dynamic, patient-specific cutaneous bilirubin retention. ConclusionSRBV provides a biologically plausible explanation for TcB-TSB discordance and dynamic TcB behaviour. Incorporating SRBV into TcB interpretation enables physiologically informed monitoring, improving safety and reliability in laboratory-limited neonatal settings. Significance StatementTranscutaneous bilirubinometry is widely used but limited by disagreement with serum bilirubin. This study introduces SRBV as a physiological explanation for TcB variability and proposes an SRBV-adjusted framework that transforms TcB measurements into actionable, non-invasive clinical guidance.

Functional capacity, muscle strength, and patient-reported outcome measures are important indicators of health. In chronic obstructive pulmonary disease (COPD), these traits are often impaired beyond normal age-related decline. Substantial variability exists in both COPD and healthy populations, the biological basis of which remains poorly understood. Given the known contribution of genetics to complex traits, genetic factors may partly explain this variability. This study aimed to identify genetic variants associated with measures used to characterise extrapulmonary traits in COPD. Genome-wide association studies were conducted on the Lab3R-ESSUA cohort for the 6-minute walk test (6MWT), the 1-minute sit-to-stand test (1-min STS), the quadriceps maximal voluntary contraction (QMVC), the handgrip muscle strength, and the chronic airways assessment test (CAAT), adjusting for age, sex, body mass index, pack-years and ancestry. Variants with P<1E-05 were selected for replication in the EARLYCOPD cohort, and effects compared between COPD and healthy populations (two-way ANOVA). A total of 639 participants (364 people with COPD, 275 healthy; 75% male, median age 67 years; BMI of 27 Kg/m2; 10 pack-years) were included. Significant variants were identified for the 6MWT (rs1108983:G, {beta}=-186.5m, P=4.8E-08), the 1-min STS (rs5889103:GTT, {beta}=4.2reps, P=4.8E-08), the Handgrip (rs67352743:A, {beta}=-4.4Kg, P=2.8E-08), and for the CAAT (rs11747040:C, {beta}=4.4points, P=4.0E-09; rs11041680:A, {beta}=-2.6points, P=2.5E-08). Effects were independent of COPD diagnosis. Replication in EARLYCOPD (n=282) confirmed one SNP for 6MWT and three for CAAT. These findings highlight genetic contributions to functional capacity, muscle strength, and disease burden. COPD-related impairments appear to build on pre-existing genetic predisposition, contributing to disease heterogeneity.

BackgroundNursing documentation patterns may reflect patient acuity and clinical deterioration, yet their prognostic value remains underexplored. We developed the Intensive Documentation Index (IDI), a novel framework quantifying temporal documentation rhythms, and evaluated its ability to enhance ICU mortality prediction.58 MethodsWe analyzed 26,153 ICU admissions of heart failure patients from the MIMIC-IV database (2008-2019). Nine IDI features capturing documentation rhythm, volume, and surveillance gaps were extracted from electronic health record timestamps during the first 24 hours of ICU stay. We compared logistic regression models with and without IDI features using temporal validation and race-stratified analysis.2124 ResultsThe cohort had a mean age of 68.5 {+/-} 13.2 years and an in-hospital mortality rate of 15.99% (n=4,181). The baseline model (age, sex, ICU length of stay) achieved an AUC of 0.658 (95% CI 0.609-0.710). Addition of nine IDI features significantly improved discrimination to 0.683 (95% CI 0.631-0.732), an absolute increase of 0.025 (p<0.05, DeLong test). Leave-one-year-out cross-validation across 12 years yielded a mean AUC of 0.684 (SD 0.008). The coefficient of variation of inter-event intervals (idi_cv_interevent) was the strongest predictor (OR 1.53 per SD, 95% CI 1.38-1.70, p<0.001). Model performance was consistent across racial and ethnic groups (AUC range 0.673-0.691), with no evidence of systematic bias. ConclusionsDocumentation rhythm patterns, captured through the IDI framework, significantly enhance ICU mortality prediction beyond traditional clinical variables. The association between documentation irregularity and mortality may reflect nursing workload, patient acuity, or care processes warranting further investigation. IDI represents a novel, readily available prognostic signal that could inform future clinical decision support systems.25

ContextPolycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder associated with reproductive dysfunction and long-term cardiometabolic risk. Traditional phenotype classifications based on diagnostic criteria may not fully capture the multidimensional biological variability underlying endocrine and metabolic risk profiles, particularly in young women. ObjectiveTo identify data-driven endocrine-metabolic phenotypes in young women with PCOS and evaluate their association with established cardiometabolic risk markers. Design and SettingCross-sectional study conducted at a tertiary Gynecological Endocrinology Clinic in Poland between January 2018 and May 2025. ParticipantsA total of 1300 young women diagnosed with PCOS according to Rotterdam criteria were included. The primary analytic cohort comprised 1032 participants aged 16-25 years with complete endocrine-metabolic biomarker data. Main Outcome MeasuresEndocrine-metabolic phenotypes were derived using principal component analysis followed by Gaussian mixture model clustering. Cardiometabolic risk endpoints included impaired glucose tolerance (2-hour plasma glucose during an oral glucose tolerance test [&ge;]140 mg/dL), an atherogenic lipid profile (triglycerides (TG)/high-density lipoproteins (HDL-C) ratio >3.50), elevated non-HDL cholesterol ([&ge;]130 mg/dL), and a composite outcome of any abnormality. ResultsPrincipal component analysis retained 10 components explaining 81.9% of total variance. Unsupervised clustering identified two stable phenotypes (silhouette = 0.392; ARI = 0.842). Cluster 0 (n=954; 92.4%) represented a mixed endocrine-metabolic profile, whereas cluster 1 (n=78; 7.6%) was enriched for thyroid/autoimmune features, with higher anti-thyroid peroxidase antibody levels and higher thyroid-stimulating hormone. Cluster 1 showed a higher prevalence of an atherogenic lipid profile compared with cluster 0, while differences in glucose intolerance and non-HDL cholesterol were modest. Logistic regression analyses suggested phenotype-specific variation in cardiometabolic risk markers. ConclusionsIn a large cohort of young women with PCOS, data-driven analysis identified two reproducible endocrine-metabolic phenotypes, including a distinct thyroid/autoimmune-enriched subgroup. These findings highlight clinically relevant heterogeneity beyond traditional diagnostic phenotypes and support the potential value of integrated endocrine-metabolic profiling for early risk stratification in PCOS.

Sleep regularity is an important but under-measured dimension of sleep health. Objective indices from actigraphy or wearables are robust but resource-intensive. The Sleep Regularity Questionnaire (SRQ) offers a brief subjective tool, but its validity against objective and diary-based indices in healthy adults is unclear. In Part 1, 31 adults wore a smart ring continuously for 21 nights. Device-derived regularity metrics included the Sleep Regularity Index (SRI), interdaily stability (IS), social jetlag (SJL), composite phase deviation (CPD), and the standard deviation of sleep onset and wake time. In Part 2, 52 adults completed a one-week sleep diary, from which variability in sleep timing, total sleep time (TST), SJL and nightly perceived sleep quality were derived. All participants completed the SRQ and Brief Pittsburgh Sleep Quality Index (B-PSQI). In Part 1, associations between SRQ scores and device-derived SRI, IS, SJL, CPD and timing variability were small (absolute r [&le;] 0.36). Higher SRQ Global and Sleep Continuity scores were moderately associated with better B-PSQI global scores (r -0.37 to -0.44). In Part 2, SRQ Global and Circadian Regularity showed small-to-moderate associations with higher diary-rated sleep quality and lower bedtime variability (r {approx} 0.40 and -0.32 to -0.34), while correlations with other diary metrics and B-PSQI were weak (absolute r [&le;] 0.25). The SRQ shows modest convergent validity with diary-based timing variability and perceived sleep quality, but only weak correspondence with smart ring-based sleep regularity indices. It is likely to complement, rather than replace, objective monitoring in healthy adults with relatively regular sleep-wake patterns.