Background New-onset atrial fibrillation (NOAF) is the most common arrhythmia in critically ill patients admitted to intensive care and is associated with poor prognosis and disease burden. Identifying high-risk individuals early is crucial. This study aims to create and validate a NOAF prediction model for critically ill patients using machine learning (ML). Methods The data came from two non-overlapping datasets from the Medical Information Mart for Intensive Care (MIMIC), with MIMIC-IV used for training and subset of MIMIC-III used as external validation. LASSO regression was used for feature selection. Eight ML algorithms were employed to construct the prediction model. Model performance was evaluated based on identification, calibration, and clinical application. The SHapley Additive exPlanations (SHAP) method was used for visualizing model characteristics and individual case predictions. Results Among 16,528 MIMIC-IV patients, 1520 (9.2%) developed AF post-ICU admission. A model

Background Rezafungin is an echinocandin approved in the US and EU to treat candidaemia and/or invasive candidiasis. This post-hoc, pooled analysis of the Phase 2 STRIVE and Phase 3 ReSTORE trials assessed rezafungin versus caspofungin in patients with candidaemia and/or invasive candidiasis (IC) in the intensive care unit (ICU) at randomisation. Methods STRIVE and ReSTORE were randomised double-blind trials in adults with systemic signs and mycological confirmation of candidaemia and/or IC in blood or a normally sterile site ≤ 96 h before randomisation. Data were pooled for patients in the ICU at randomisation who received intravenous rezafungin (400 mg loading dose then 200 mg once weekly) or caspofungin (70 mg loading dose then 50 mg once daily) for ≤ 4 weeks. Outcomes were Day 30 all-cause mortality (primary outcome), Day 5 and 14 mycological eradication, time to negative blood culture, mortality attributable to candidaemia/invasive candidiasis, safety, and pharmacokinetics. Result

Background The aim of this study was to assess whether hypothermia increased survival and improved functional outcome when compared with normothermia in out-of-hospital cardiac arrest (OHCA) patients with similar characteristics than in previous randomized studies showing benefits for hypothermia. Methods Post hoc analysis of a pragmatic, multicenter, randomized clinical trial (TTM-2, NCT02908308). In this analysis, the subset of patients included in the trial who had similar characteristics to patients included in one previous randomized trial and randomized to hypothermia at 33 °C or normothermia (i.e. target < 37.8 °C) were considered. The primary outcome was survival at 6 months; secondary outcomes included favorable functional outcome at 6 months, defined as a modified Rankin scale of 0–3. Time-to-death and the occurrence of adverse events were also reported. Results From a total of 1891 included in the TTM-2 study, 600 (31.7%) were included in the analysis, 294 in the hypothermia

Objective To report the outcomes of patients with severe tuberculosis (TB)-related acute respiratory distress syndrome (ARDS) on extracorporeal membrane oxygenation (ECMO), including predictors of 90-day mortality and associated complications. Methods An international multicenter retrospective study was conducted in 20 ECMO centers across 13 countries between 2002 and 2022. Results We collected demographic data, clinical details, ECMO-related complications, and 90-day survival status for 79 patients (median APACHE II score of 20 [25th to 75th percentile, 16 to 28], median age 39 [28 to 48] years, PaO2/FiO2 ratio of 69 [55 to 82] mmHg before ECMO) who met the inclusion criteria. Thoracic computed tomography showed that 61 patients (77%) had cavitary TB, while 18 patients (23%) had miliary TB. ECMO-related complications included major bleeding (23%), ventilator-associated pneumonia (41%), and bloodstream infections (32%). The overall 90-day survival rate was 51%, with a median ECMO durat

Background Sleep deprivation is common in intensive care units (ICUs) and may alter respiratory performance. Few studies have assessed the role of sleep disturbances on outcomes in critically ill patients. Objectives We hypothesized that sleep disturbances may be associated with poor outcomes in ICUs. Methods Post-hoc analysis pooling three observational studies assessing sleep by complete polysomnography in 131 conscious and non-sedated patients included at different times of their ICU stay. Sleep was assessed early in a group of patients admitted for acute respiratory failure while breathing spontaneously (n = 34), or under mechanical ventilation in patients with weaning difficulties (n = 45), or immediately after extubation (n = 52). Patients admitted for acute respiratory failure who required intubation, those under mechanical ventilation who had prolonged weaning, and those who required reintubation after extubation were considered as having poor clinical outcomes. Durations of de

Background Veno-venous extracorporeal membrane oxygenation (VV ECMO) has become standard of care in patients with the most severe forms of acute respiratory distress syndrome. However, hemolysis and bleeding are one of the most frequent side effects, affecting mortality. Despite the widespread use of VV ECMO, current protocols lack detailed, in-vivo data-based recommendations for safe ECMO pump operating conditions. This study aims to comprehensively analyze the impact of VV ECMO pump operating conditions on hemolysis by combining in-silico modeling and clinical data analysis. Methods We combined data from 580 patients treated with VV ECMO in conjunction with numerical predictions of hemolysis using computational fluid dynamics and reduced order modeling of the Rotaflow (Getinge) and DP3 (Xenios) pumps. Blood trauma parameters across 94,779 pump operating points were associated with numerical predictions of shear induced hemolysis. Results Minimal hemolysis was observed at low pump pre