Articles: intensive-care-units.
-
High lactate to albumin ratio (LAR) has been reported to be associated to with poor prognosis in patients admitted to the intensive care unit (ICU). However, its role in predicting in-hospital mortality in AF patients admitted to ICU has not been explored. ⋯ LAR, as a readily available biomarker, can predict in-hospital mortality in AF patients admitted to the ICU. The nomogram that combined LAR with other relevant variables performed exceptionally well in terms of predicting in-hospital mortality.
-
A real-time model for predicting short-term mortality in critically ill patients is needed to identify patients at imminent risk. However, the performance of the model needs to be validated in various clinical settings and ethnicities before its clinical application. In this study, we aim to develop an ensemble machine learning model using routinely measured clinical variables at a single academic institution in South Korea. ⋯ Our real-time machine learning model to predict short-term mortality in critically ill patients showed excellent performance in both internal and external validations. This model could be a useful decision-support tool in the intensive care units to assist clinicians.
-
Comparative Study Observational Study
Impact of COVID-19 on posttraumatic stress disorder in ICU survivors: a prospective observational comparative cohort study.
Posttraumatic stress disorder (PTSD) after a stay in the intensive care unit (ICU) can affect one in five ICU survivors. At the beginning of the coronavirus disease 2019 (COVID-19) pandemic, admission to the ICU for COVID-19 was stressful due to the severity of this disease. This study assessed whether admission to the ICU for COVID-19 was associated with a higher prevalence of PTSD compared with other causes of ICU admission after adjustment for pre-ICU psychological factors. ⋯ Admission to the ICU for COVID-19 was not associated with a higher prevalence of PTSD compared with admission for another cause during the first wave of the COVID-19 pandemic in France. However, intrusion and avoidance symptoms were more frequent in COVID-19 patients than in non-COVID-19 patients.
-
Meta Analysis
Accuracy of respiratory muscle assessments to predict weaning outcomes: a systematic review and comparative meta-analysis.
Several bedside assessments are used to evaluate respiratory muscle function and to predict weaning from mechanical ventilation in patients on the intensive care unit. It remains unclear which assessments perform best in predicting weaning success. The primary aim of this systematic review and meta-analysis was to summarize and compare the accuracy of the following assessments to predict weaning success: maximal inspiratory (PImax) and expiratory pressures, diaphragm thickening fraction and excursion (DTF and DE), end-expiratory (Tdiee) and end-inspiratory (Tdiei) diaphragm thickness, airway occlusion pressure (P0.1), electrical activity of respiratory muscles, and volitional and non-volitional assessments of transdiaphragmatic and airway opening pressures. ⋯ DTF and DE are superior to PImax and DTF seems to have the highest accuracy among all included respiratory muscle assessments for predicting weaning success. Further studies aiming at identifying the optimal threshold of DTF to predict weaning success are warranted.