Critical Care Explorations

Purpose To estimate the per-protocol effect of red blood cell (RBC) transfusion strategies on ICU-acquired infection in critically ill adults with sepsis using a target trial emulation framework. We evaluated whether restrictive strategy and liberal strategy, defined by hemoglobin (Hgb) thresholds, differ in their effect on ICU-acquired infection during ICU stay. Methods We conducted a target trial emulation using the MIMIC-IV database and included adults who met Sepsis criteria at ICU admission. Clones were assigned to restrictive or liberal transfusion strategies. Under the restrictive strategy, RBC transfusion was permitted only when Hgb was [≤]7.0 g/dL, whereas under the liberal strategy, transfusion was permitted when Hgb was >7.0 g/dL. The primary outcome was the first ICU-acquired infection occurring at least 72 hours after ICU admission. Per-protocol effects were estimated using a clone-censor-weight approach with a marginal structural model. A parametric g-formula was used as a complementary analysis that jointly modeled ICU discharge and ICU mortality as competing events to derive strategy-specific 28-day cumulative incidences and risk differences. Results 8 Among 4,013 eligible ICU stays, the liberal-versus-restrictive comparison provided little evidence of a difference in the risk of ICU-acquired infection (adjusted conditional OR, 0.954; 95% CI, 0.797 to 1.142). In the complementary g-formula analysis, the 28-day risk difference for the liberal versus restrictive comparison was -0.02 percentage points (95% CI, -0.15 to 0.11), consistent with the primary analysis. Findings were generally robust across prespecified subgroup and sensitivity analyses. Conclusion In this target trial emulation of adults with sepsis, we observed no clinically meaningful difference in ICU-acquired infection between RBC transfusion strategies defined by hemoglobin thresholds.

Objective: This study aims to identify which markers of tissue hypoperfusion - specifically lactate levels, central venous oxygen saturation (ScvO2), and venous arterial carbon dioxide gradient (CO2 gradient) - have the highest sensitivity and specificity in predicting the discharge of postoperative cardiac surgical patients from the ICU within 48 hours. This is an exploratory, hypothesis-generating investigation. Methods: Prospective observational study involving 100 patients in the Surgical ICU at InCor-HCFMUSP undergoing cardiac surgery with cardiopulmonary bypass. Perfusion markers were assessed at ICU admission and 24 hours post-admission. Results: ScvO2 at 24 hours was the only marker significantly associated with ICU discharge (OR=1.096; 95% CI=1.020-1.180; p=0.012). Formal DeLong's test confirmed ScvO2 had significantly superior discriminatory performance compared to lactate (AUC 0.661 vs. 0.428; p=0.004). Lactato and CO2 gap showed no significant associations. Conclusions: In this exploratory cohort, ScvO2 at 24 hours post-admission showed a statistically significant association with early ICU discharge and superior discriminatory performance compared to lactate. These findings are hypothesis-generating and require prospective validation before clinical recommendations can be made.

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: Molecular markers and mediators of adverse post-hospital outcomes following critical illness remain incompletely characterized. Anemia and red blood cell (RBC) indices integrate inflammation, nutritional status, and hematopoietic function, and may represent biological processes that influence long-term outcomes. We therefore examined whether pre-discharge anemia and hematologic clusters derived from correlated RBC indices were associated with one-year mortality among critical illness survivors. Methods: We conducted an exploratory, retrospective cohort study of adult ICU patients discharged alive using MIMICIV. Pre-hospital discharge RBC indices (hemoglobin, red cell distribution width (RDW), mean corpuscular volume (MCV), mean cell hemoglobin (MCH), mean cell hemoglobin concentration (MCHC), and RBC count) were analyzed. Hemoglobin and anemia were first evaluated, followed by Gaussian mixture modeling of standardized RBC indices to identify patient clusters in a derivation cohort (70%) and validated findings in a held-out cohort (30%). Associations with one-year mortality were assessed using multivariable-adjusted Cox models. Results: Among 20,233 ICU survivors with available pre-discharge hemoglobin (median age, 67 years), based on the WHO definition of anemia, 17,247 (85.2%) critical illness survivors were anemic at hospital discharge. Anemia was associated with higher one-year mortality (adjusted HR 1.42, p<0.001). Mortality was 20% overall and decreased across increasing hemoglobin quartiles, from 28.8% to 12.5% (log-rank P<0.005); lower hemoglobin was associated with progressively higher adjusted one-year mortality risk. Six hematologic clusters derived from RBC indices were identified with one-year mortality ranging from 10.1% to 31.4% (log-rank p<0.005). Compared with the lowest-risk group, the cluster characterized by elevated RDW and MCV had a twofold higher adjusted mortality risk (HR 2.14; 95% CI, 1.81-2.53). Conclusion: Both anemia and hematologic clusters derived from standard RBC indices at hospital discharge are associated with one-year mortality following critical illness. These hypothesis-generating findings support further investigation of RBC indices as potential biomarkers for post-discharge risk stratification and of the underlying biological pathways as possible therapeutic targets.

Background: Risk adjustment for disease severity in pediatric intensive care research commonly relies on clinical organ dysfunction scores requiring detailed clinical and laboratory information, which is often unavailable in administrative healthcare datasets. We therefore evaluated the feasibility of a coding-based Pediatric Organ Dysfunction Index (PODI) derived from International Classification of Diseases (ICD-10) and Operation and Procedure System (OPS) codes, for approximating sepsis-related organ dysfunction and adjusting for disease severity, using the pediatric Sequential Organ Failure Assessment (pSOFA) score as a reference standard. Methods: In this retrospective single-center cohort study, pediatric sepsis episodes treated between November 2011 and November 2021 were identified. Discrimination for in-hospital mortality and calibration were assessed. Agreement between PODI and pSOFA was quantified using Spearman's rank correlation, and organ-specific agreement using sensitivity, specificity, and predictive values. An expanded PODI incorporating additional ICD-10 and OPS codes was evaluated in sensitivity analyses. Results: A total of 488 pediatric sepsis episodes were included, with an in-hospital mortality of 14.1%. The PODI showed good discrimination for in-hospital mortality (AUC 0.85, 95% CI 0.80-0.89), comparable to the maximum pSOFA (pSOFAmax) (AUC 0.78, 95% CI 0.72-0.83) and superior to pSOFA at sepsis onset (pSOFAonset) (AUC 0.73, 95% CI 0.67-0.80). Agreement between PODI and pSOFA organ-specific components varied considerably across organ systems, with the highest sensitivity to detect pulmonary dysfunction. Correlation between both scores was moderate (0.54 for pSOFAonset and 0.60 for pSOFAmax), indicating that comparable predictive performance does not render the scores interchangeable. The expanded PODI improved organ-level sensitivity for selected components but did not meaningfully improve mortality discrimination. Conclusions: The standard PODI may represent a practical approach to adjust for organ dysfunction and therapy intensity in administrative datasets with ICD-10 coding where clinical and laboratory information is unavailable. Given only moderate agreement with the pSOFA, the PODI should be understood as a covariate for risk adjustment at the group level rather than as a substitute for clinical organ dysfunction scores in individual patients. Further validation and refinement in non-sepsis cohorts are required before broader implementation in large-scale administrative research can be recommended.

Background Despite numerous randomized controlled trials (RCTs) and systematic reviews (SRs), current sepsis guidelines continue to issue only weak recommendations for corticosteroids. We examined the clinical scope, underlying study pools, and mortality conclusions of SRs evaluating corticosteroids for sepsis. Methods We conducted a meta-research study of SRs on corticosteroids in sepsis (2015 to 2025), extracting SR characteristics, mortality results, and included RCTs. Study-pool overlap was assessed using an SRxRCT inclusion matrix, Jaccard similarity (J), and hierarchical clustering. SRs and RCTs were classified according to standardized Population, Intervention, Comparison, Outcome (PICO) profiles. We explored discordance in short-term mortality conclusions among clinically comparable SRs and potential associations with study-pool composition, target populations, and methodological characteristics. Results Forty-two SRs including 121 unique RCTs were identified. More than half of pairwise SR comparisons shared no RCTs, and only three pairs showed high overlap (J>0.8). SRs addressing similar intervention and target population profiles frequently relied on different study pools. Among 38 SRs with short-term mortality meta-analyses, 15 (39%) reported benefit and 23 (61%) no evidence of effect. Discordance occurred exclusively among SRs evaluating broad, non-specific corticosteroid strategies; conclusions were consistent for hydrocortisone plus fludrocortisone (benefit) and hydrocortisone, ascorbic acid, and thiamine (no evidence of effect). SRs including sepsis +/- shock populations more frequently reported benefit than those restricted to septic shock (62% vs 22%), although estimates were imprecise. No single methodological or clinical factor consistently explained discordance. Conclusions SRs addressing apparently similar clinical questions frequently synthesized different underlying evidence bases and reported discordant conclusions. Guideline developers should therefore consider not only methodological quality and reported PICO, but also whether the RCTs included in an SR adequately represent the intended clinical question. Clinically coherent evidence syntheses may improve the interpretability of pooled treatment effects and support more targeted corticosteroid therapy in sepsis.

Abdominal aortic aneurysm (AAA) patients in the ICU represent a heterogeneous, high-risk population with mortality risk evolving across distinct clinical phases. Existing prognostic tools rely largely on Cox proportional hazards (Cox PH) nomograms with narrow predictor sets and single time horizons, leaving the value of modern machine learning, extended features, and external generalizability uncharacterized. We extracted an ICD-coded AAA ICU cohort from MIMIC-IV v2.2 (858 patients with complete six-predictor admission data: age, BUN, sepsis, antihypertensive use, anion gap, mean SpO2) using a 24-hour admission window. An extended feature set added hemodynamic, laboratory, and comorbidity variables, with feature selection via LASSO and SVM-RFE intersection. Six models (Cox PH, logistic regression, random forest, gradient boosting, XGBoost, MLP) were trained on a 70% split and evaluated at 7-, 14-, and 28-day horizons using ROC-AUC, C-index, Brier score, calibration, and SHAP. External validation used a harmonized eICU-CRD cohort. In-hospital mortality was [~]11.8%. On the six-predictor set, logistic regression led at 7 days (AUC 0.866) and 14 days (AUC 0.872), with XGBoost competitive. Extended features yielded modest gains; random forest achieved the best 28-day AUC (0.892). The MLP consistently underperformed. Discrimination declined monotonically with longer horizons. External validation showed expected attenuation (best 7-day AUC 0.771). SHAP consistently identified anion gap, BUN, and age as top contributors. We conclude that regularized linear models excel under data scarcity, while tree ensembles gain advantage as features and horizons expand. External results motivate local recalibration before deployment.

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.

Background. Capillary refill time is a resuscitation target in septic shock,1-4 but bedside measurement is examiner-dependent. An ICU monitor co-records a photoplethysmogram on the pulse oximeter and intermittent noninvasive blood pressure cuff cycles; if the probe and the cuff share a limb, each cycle is an unplanned vascular occlusion test on the distal microvascular bed. Standard practice places the two on opposite limbs. Objective. To measure how often, in MIMIC-IV-WDB v0.1.0, charted cuff cycles show the photoplethysmographic morphology expected of a same-limb cuff and probe, and to characterize the candidate capillary refill-like signal when that morphology is present. Methods. MIMIC-IV-WDB v0.1.05 was linked to the MIMIC-IV clinical database.6 A pre-registered rule-based detector identified candidate occlusion-reperfusion signatures on the 1-Hz perfusion-index envelope around each charted cuff timestamp. The primary endpoint was the proportion of cuff cycles suitable for analysis that were detector-positive at a 15-second reperfusion threshold, with 95% confidence intervals estimated by resampling patients at a fixed seed. A secondary analysis used a locally hosted multimodal language model (a Gemma-3 derivative on a non-device server) to adjudicate the same signature on perfusion-index plots; no MIMIC-IV-WDB content left the workstation. Results. Of 9,224 charted cuff cycles, 8,909 had a usable pulse-oximeter waveform, and 268 cycles in 15 patients (4.30% of the 6,236 cuff cycles suitable for analysis, 95% CI 2.60 to 6.03) met the primary 15-second threshold. The language model adjudicated the same cycles and called 1,367 of the 8,909 cycles with a usable waveform (15.34%) signature-present, roughly five times the detectors count. Because no laterality ground truth exists, agreement with a single blinded reader served as the comparator rather than accuracy. The two methods were about equally concordant with the reader: precision was 0.25 (95% CI 0.14 to 0.39) for the detector and 0.24 (95% CI 0.10 to 0.35) for the language model, although reweighting to the full population of cycles with a usable waveform lowered the language model to 0.030 (95% CI 0.009 to 0.053). These estimates are reference-limited: a blinded re-read of a 150-card subsample showed only moderate intra-rater reliability (Cohen {kappa} 0.46 to 0.59) with systematic undercalling on the first pass, and rescoring against the corrected re-read roughly doubled precision for both methods. Conclusions. Opportunistic extraction of capillary refill-like signals from archived ICU pulse oximetry is limited in two distinct ways. First, sensor geometry limits how often the signal is recordable: cuff cycles rarely show the morphology expected of a same-limb cuff and probe pair, consistent with opposite-limb placement, so the bottleneck is geometry rather than signal processing. Second, the modest reliability of morphology adjudication limits how well any single flagged cycle can be confirmed: against a blinded reader the detector is a usable screen but a noisy confirmer, the reference is itself only moderately reliable, and the language model is no more concordant despite flagging many more cycles. The minority of cycles in which the morphology appears contain a candidate signal that may merit prospective study under controlled placement with laterality recorded.

Purpose: Continuous intracranial pressure (ICP) monitoring requires invasive instrumentation, reaching only a narrow subset of critically ill patients. We tested whether deep learning models trained on routinely acquired extracranial signals can reconstruct continuous ICP waveforms at clinically relevant accuracy in an independent external cohort. Methods: In adults admitted to the ICU at a single quaternary health system, five deep learning architectures were trained on high-frequency arterial blood pressure (ABP), photoplethysmography (PPG), and electrocardiography (ECG) waveforms, using invasive (intraparenchymal) ICP as ground truth. Two fusion strategies (early and late) and three training objectives (waveform-morphology, baseline robust regression, and weighted robust regression) were evaluated. Models were externally validated on the held-out MIMIC-III Waveform Database. Performance was assessed by mean absolute error (MAE) and waveform similarity by Pearson correlation (r). Results: We analyzed data from 158 critically ill adults (~5,322 hours) across two quaternary health systems (Johns Hopkins Hospital, Baltimore; Beth Israel Deaconess Medical Center, Boston). Validation MAE ranged from 4.276 mmHg [95% CI 4.269, 4.283] (gated recurrent, late fusion) to 4.946 mmHg [95% CI 4.938, 4.956] (attention-based, early fusion), with Pearson r ranging from 0.599 [95% CI 0.599, 0.600] to 0.722 [95% CI 0.722, 0.723]. The multiscale encoder-decoder model demonstrated the most favorable MAE-correlation tradeoff. Conclusion: This is the first demonstration that continuous ICP waveform reconstruction from bedside signals generalizes across institutions at clinically relevant accuracy, establishing a foundation for non-invasive ICP monitoring and motivating validation across broader populations and ICP ranges.

Objective We aimed to evaluate the performance of the recently updated Sequential Organ Failure Assessment Score-2 (SOFA-2) on organ dysfunction classification and prognostication compared to SOFA-1 in critically injured trauma patients. Methods Adult trauma patients admitted to critical care at four urban Major Trauma Centres between 2011 and 2024 were included. Daily organ dysfunction scoring was performed using SOFA-1 and SOFA-2 until death or discharge. The primary outcome was MODS, defined as SOFA score [&ge;]6. Results In 2162 severely injured patients (median Injury Severity Score 25 [IQR, 17-34]), SOFA-2 reduced the proportion of patients classified as having MODS compared with SOFA-1 (61.6% vs 68.5%, p<0.001). SOFA-2 scores on the first day after admission were lower than SOFA-1 (median 6 [IQR, 3-8] vs 7 [IQR, 4-10], p<0.001), driven predominantly by lower respiratory and cardiovascular scoring. Critical care mortality in trauma patients was increased in respiratory, cardiovascular and renal components of SOFA-2 at the higher ends of the scores, consistent with the aims of the SOFA-2 reclassification. A group of 159 severely injured patients (7.3%) classified as MODS by SOFA-1 were reclassified to no-MODS by SOFA-2. Despite this reclassification, these patients had substantially higher ICU mortality (7.5% vs 0.7%, p<0.01), greater ventilator and vasopressor requirements, and longer hospital stays than patients classified as no-MODS by both systems. Conclusions SOFA-2 reduces MODS prevalence in severely injured patients and changes organ dysfunction classification, with lower rates of severe respiratory and cardiovascular dysfunction. This represents an important update in trauma MODS measurement and has implications for future trauma trial design. However SOFA-2 reclassification generates a small cohort a small but clinically significant group with occult MODS that warrants further evaluation in severely injured trauma patients.

BACKGROUND: Liberation from invasive mechanical ventilation (IMV) is a central therapeutic objective in acute respiratory failure (ARF). While lung-protective ventilation strategies and diaphragm function have received considerable attention as determinants of liberation success, the prognostic role of extrapulmonary thoracic tissue composition remains poorly defined. We examined whether chest computed tomography (CT)-derived thoracic skeletal muscle mass (TMM), subcutaneous fat mass (SFM), and their ratio (muscle-fat ratio: MFR) are associated with IMV outcomes in ARF. METHODS: This secondary analysis of a prospective observational ARF cohort includes patients with a chest CT obtained within 7 days before or 3 days after intubation. TMM, SFM and MFR were derived using validated three-dimensional convolutional neural network-based volumetric segmentation spanning the lung apices to bases. Co-primary outcomes were time to successful ventilator liberation within 60 days and 60-day all-cause mortality. Multivariable Cox and logistic regression models with restricted cubic splines assessed linear and non-linear associations, adjusted for age, sex, and key comorbidities. We performed prespecified BMI-stratified and ARDS subgroup analyses. RESULTS: Among 826 patients with ARF requiring IMV, 238 patients with CT imaging were included for analysis (median age 59.5 years, median BMI 28.7 kg/m^2). A higher MFR was independently associated with faster ventilator liberation (hazard ratio 1.16, 95% confidence interval [CI] 1.02 to 1.32, p=0.023). TMM demonstrated a significant J-shaped non-linear relationship with time to liberation (p for non-linearity=0.019), with delayed liberation at both low and high extremes of TMM. Higher SFM was independently associated with increased 60-day mortality (odds ratio 1.09, 95% CI 1.00 to 1.18, p=0.049). In 81 patients with ARDS, TMM also demonstrated a significant J-shaped non-linear relationship with 60-day mortality (p for non-linearity=0.037). BMI was not significantly associated with either outcome. CONCLUSIONS: Volumetric CT-derived thoracic body composition metrics, particularly MFR and TMM, are independently associated with ventilator liberation and 60-day mortality in ARF, capturing prognostic information not reflected by BMI alone. These findings support the incorporation of automated thoracic body composition analysis into early risk stratification frameworks for mechanically ventilated patients and highlight extrapulmonary tissue composition as an underexplored determinant of IMV outcomes.

Background: Optimal arterial oxygen targets after return of spontaneous circulation (ROSC) in pediatric out-of-hospital cardiac arrest (OHCA) remain uncertain. We examined whether arterial oxygen tension on the first arterial blood gas after ROSC is associated with neurological or survival outcomes. Methods: Using the Japanese Association for Acute Medicine OHCA Registry, we retrospectively studied pediatric patients (<18 years) with OHCA in whom ROSC was confirmed at or after hospital arrival. Patients were categorized by PaO? on the first arterial blood gas after ROSC as normoxemia (60?200 mmHg) or hyperoxemia (>200 mmHg). Missing covariate data were handled using multiple imputation, and associations were estimated using inverse probability-weighted logistic regression. Outcomes were favorable neurological status at 30 days, defined as a Pediatric Cerebral Performance Category score of 1?3, and 30-day survival. Multiple sensitivity analyses were performed, including analyses using an alternative PaO? threshold, restricting the timing of PaO? measurement, and excluding extracorporeal cardiopulmonary resuscitation cases. Results: A total of 189 patients were included (95 normoxemia, 94 hyperoxemia). A favorable neurological outcome occurred in 21 of 95 (22.1%) normoxemia and 13 of 94 (13.8%) hyperoxemia patients, and 30-day survival in 40 of 95 (42.1%) and 42 of 94 (44.7%), respectively. After weighting, covariate balance was achieved with standardized mean differences below 0.1. Hyperoxemia was not significantly associated with favorable neurological outcome (adjusted odds ratio [aOR] 0.94, 95% confidence interval [CI] 0.49?1.77) or 30-day survival (aOR 1.49, 95% CI 0.88?2.54). Sensitivity analyses yielded consistent results. Conclusions: Early hyperoxemia after ROSC was not significantly associated with neurological or survival outcomes in pediatric out-of-hospital cardiac arrest. These findings suggest that a single early PaO? measurement may be insufficient to characterize the clinical impact of oxygen exposure after resuscitation. Future research should focus on phase-specific and individualized oxygen management incorporating serial physiological assessment.

Background: The 2026 American Heart Association/American College of Cardiology (AHA/ACC) guidelines replaced the 2019 European Society of Cardiology (ESC) four-tier pulmonary embolism (PE) risk scheme with five clinical categories (A-E) and subcategories. These categories were set by expert consensus and have not been validated against outcomes. How patients are reclassified relative to ESC, or how the two systems compare prognostically, is unknown. Methods: We utilized three cohorts of patients with confirmed PE using structured electronic health record data, laboratory biomarkers, and large-language-model abstraction of radiology reports: Duke University Health System (n=12,992, drawn from 95,760 consecutive inpatient CT pulmonary angiography studies, 2014-2025, with no referral or registry enrollment step between imaging and cohort entry), INSPECT (Stanford; n=3,870), and MIMIC-IV (Beth Israel Deaconess; n=361). Patients were assigned AHA/ACC categories B through E, subcategorized where data allowed, and mapped to 2019 ESC risk strata. The primary outcome was 30-day mortality; discrimination was assessed with Harrell C-index. Results: Among 17,223 patients with confirmed PE, pooled 30-day mortality rose monotonically across categories: 1.5% (B), 8.9% (C), 15.5% (D), and 31.9% (E), with the ordering preserved in all three cohorts despite differing baseline mortality. Subcategory-level discrimination was reliable only at the high-acuity extreme (D2-E2); across subcategories C1 through D1, mortality did not order monotonically (9.2%, 10.8%, 8.1%, 10.9%), and adding subcategories to category C did not improve discrimination at Duke (C-index 0.699 vs 0.699). Category C patients lacking both echocardiography and biomarker testing (12.7% of category C) had mortality (10.4%) equal to or exceeding classified peers. Relative to ESC, the frameworks were concordant at the extremes, but 5.7%of ESC intermediate-risk patients were reclassified to category D, with modestly higher but non-significant 30-day mortality than those remaining in category C (10.8% versus 8.9%). Conclusions: Across a three-health-system cohort, the 2026 AHA/ACC framework produced a reproducible mortality gradient at the category level, with added subcategory granularity refining risk chiefly at the highest-acuity tiers. Discrimination across the broad intermediate band was limited, and reclassification from ESC fell almost entirely within this range.

Background: The condition of a patient with acute stroke often changes within hours of ICU admission. Prognostic work here targets fixed endpoints predicted from admission data, and trajectory phenotyping assigns one label per patient. We used longitudinal ICU data to identify interpretable dynamic clinical states, characterize transitions between them, and relate the current state to later events. Methods: Retrospective cohort study of 6368 adults with acute stroke in MIMIC IV v3.1. The first 72 h were divided into twelve 6-hour windows, and a hidden Markov model was fitted to 21 neurological, physiological and organ support variables. State number was chosen against criteria fixed before fitting: statistical fit, restart stability, state occupancy and clinical interpretability. Generalized estimating equations related the current state to new mechanical ventilation and vasopressor use within 12 h, and to ICU death within 72 h. Eleven sensitivity analyses assessed the robustness of the state solution. Results: Four states were selected: neurologically preserved-low support, neurological impairment low support, impairment renal dysfunction and impairment-respiratory support (63.3%, 7.8%, 11.8% and 17.1% of windows). Within 72 h, 40.3% of patients changed state at least once, and transitions ran in both directions rather than along a single severity gradient. States were identified without outcome data, yet ICU mortality by last state ranged from 2.9% to 43.9%. Adjusted for age, sex, subtype and Charlson index, the current state remained associated with organ-support escalation and death. State prevalence differed by at most 1.1 percentage points between training and test sets, and 10 of 11 sensitivity analyses gave a stable four-state solution (ARI 0.754 0.955). Conclusions: The early ICU course of acute stroke can be represented as movement among a small number of clinically interpretable states. The representation was reproducible in a held out set and across admission eras, but requires validation in an independent database before any clinical use.

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.

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.

Background: Intraoperative hypotension is associated with cardiovascular complications and mortality, making accurate blood pressure monitoring essential. However, the accuracy of noninvasive oscillometric cuff blood pressure (Cuff BP) during hypotension is uncertain. We examined the association between intraoperative hypotension and Cuff BP inaccuracy. Methods: A single-center retrospective cohort included 22,812 adults undergoing noncardiac surgery from April 2013 through November 2023, with 159,782 simultaneous Cuff BP and invasive arterial blood pressure (Arterial BP) pairs. Pairs with arterial systolic BP >120 mmHg or diastolic BP >80 mm Hg were excluded to focus on hypotensive range. Hypotension was defined as arterial mean arterial pressure (MAP) <65 mmHg and categorized as mild (55 to <65), moderate (45 to <55), or severe (35 to <45 mmHg). Cuff BP inaccuracy was defined as an absolute MAP difference >10 mmHg from Arterial BP. Multivariable logistic regression estimated adjusted odds ratios (ORs) and 95% CIs. Results: Compared with normal MAP (?65 mmHg), hypotension was associated with greater odds of Cuff BP inaccuracy (adjusted OR, 1.45 [95% CI, 1.41?1.49]). Adjusted ORs increased with severity (P for trend <0.001): 1.23 (95% CI, 1.19?1.27) for mild, 2.36 (95% CI, 2.24?2.50) for moderate, and 7.39 (95% CI, 6.34?8.62) for severe hypotension. Sensitivity for correct MAP classification decreased from 87.1% for normal MAP to 32.0%, 19.6%, and 10.2% for mild, moderate, and severe hypotension. Conclusions: We found a significantly higher risk of Cuff BP inaccuracy in patients with intraoperative hypotension, supporting cautious interpretation of Cuff BP during intraoperative hypotension.

Background Spontaneous intracerebral hemorrhage (ICH) is the most devastating type of stroke but lacks the established time-critical treatment guidelines available for acute ischemic stroke. This study investigated the impact of Code Stroke activation and warfarin use on anticoagulation reversal times to identify opportunities for quality improvement. Methods We retrospectively assessed patients with anticoagulation-associated ICH admitted to our medical center between January 1, 2020, and December 31, 2025. Patients with warfarin- or direct oral anticoagulant (DOAC)-associated ICH were identified from our ICH clinical trial screening log, Vizient, and AHA's Get With The Guidelines-Stroke registry. Code Stroke activation, warfarin or DOAC use, anticoagulation reversal times, causes of delay, and clinical outcomes at hospital discharge were analyzed. Results Of 892 ICH admissions, 50 patients had confirmed anticoagulation-associated ICH. Among those who underwent reversed at our center (n=34), Code Stroke activation (n=24) significantly reduced door-to-CT time (16.5 [12.8-22.0] vs 172.5 [49.0-261.5] minutes, p <0.001), reversal agent order-to-needle time (37.5 [24.7-56.9] vs 57.0 [39.0-85.0] minutes, p <0.001), and door-to-treatment (DTT) time (64 [48-98] vs 277 [159-305] minutes, p <0.001) compared to non-activation (n=10). Conversely, warfarin use was associated with higher international normalized ratios (INR) (2.7 [2.2-3.6] vs 1.3 [1.2-1.9], p =0.003) and significantly longer DTT time (95 [51-108] vs 64 [48-77] minutes, p =0.007). Primary DTT delays stemmed from the absence of a time-critical treatment protocol, weight-based dosing for 4F-PCC, waiting for INR results, and a lack of Code Stroke activation for patients with mild symptoms, trauma or unexplained unresponsiveness. Conclusions Our findings suggest that Code Stroke activation for all suspected cases of ICH, a time-critical emergency department algorithm targeting a DTT time of less than 60 minutes, and immediate anticoagulation reversal with fixed-dose 4F-PCC without waiting for INR results may optimize the acute management of anticoagulation-associated ICH.

BACKGROUND Children receiving extracorporeal membrane oxygenation (ECMO) are at high risk for focal cerebral injury (FCI). There is emerging evidence that electroencephalography (EEG) may aid FCI detection. The EEG Correlate of Injury to the Nervous System (COIN) index quantifies and displays focal background asymmetries. We evaluated whether COIN is associated with FCI in pediatric ECMO. METHODS Retrospective, cross-sectional study of patients age 28 days to 21 years, on venoarterial ECMO at a tertiary children's hospital, who received EEG monitoring and neuroimaging during ECMO. COIN was calculated from all available EEG data. COIN of 0 implies a symmetric EEG and negative COIN values are observed with FCI. Median COIN values near FCI recognition time were compared to median COIN values from randomly selected control EEG batches using logistic regression. A receiver operator characteristic curve was used to identify multilevel FCI test ranges. Likelihood ratios were calculated to estimate the posttest FCI probability for each COIN range. RESULTS During the 8-year study period (2015-2023), 33 of 142 ECMO runs met study criteria for COIN analysis. Twelve patients (36%) had FCI. The COIN cutoff of -13.3 had 92% sensitivity and 67% specificity for FCI. The COIN cutoff of -27.7 had 67% sensitivity and 90% specificity. Likelihood ratios were 0.13 for COIN (0 to -13.3), 1.1 for COIN (-13.3 to -27.7), and 7.0 for COIN (< -27.7). Posttest probability was 0.02, 0.13, 0.49 in each respective range. CONCLUSION FCI on ECMO is associated with COIN-measured EEG asymmetry. COIN may support FCI risk-stratification during ECMO.