Articles: critical-illness.
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J Clin Monit Comput · Apr 2024
Early prediction of mortality at sepsis diagnosis time in critically ill patients by using interpretable machine learning.
This study applied machine learning for the early prediction of 30-day mortality at sepsis diagnosis time in critically ill patients. Retrospective study using data collected from the Medical Information Mart for Intensive Care IV database. The data of the patient cohort was divided on the basis of the year of hospitalization, into training (2008-2013), validation (2014-2016), and testing (2017-2019) datasets. 24,377 patients with the sepsis diagnosis time < 24 h after intensive care unit (ICU) admission were included. ⋯ The calibration plot for the model revealed a slope of 1.03 (95% CI 0.94-1.12) and intercept of 0.14 (95% CI 0.04-0.25). The SHAP revealed the top three most significant features, namely age, increased red blood cell distribution width, and respiratory rate. Our study demonstrated the feasibility of using the interpretable machine learning model to predict mortality at sepsis diagnosis time.
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Acta Anaesthesiol Scand · Apr 2024
Observational StudyMeropenem pharmacokinetic/pharmacodynamic target attainment and clinical response in ICU patients: A prospective observational study.
Several studies report lack of meropenem pharmacokinetic/pharmacodynamic (PK/PD) target attainment (TA) and risk of therapeutic failure with intermittent bolus infusions in intensive care unit (ICU) patients. The aim of this study was to describe meropenem TA in an ICU population and the clinical response in the first 72 h after therapy initiation. ⋯ Intermittent meropenem bolus infusion q6h gives satisfactory TA in an ICU population with variable renal function and CRRT modality, except for ARC patients. No consistent relationship between TA and clinical endpoints were observed.
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Critical care medicine · Apr 2024
Randomized Controlled Trial Multicenter StudyA Comparison of High and Usual Protein Dosing in Critically Ill Patients With Obesity: A Post Hoc Analysis of an International, Pragmatic, Single-Blinded, Randomized, Clinical Trial.
Across guidelines, protein dosing for critically ill patients with obesity varies considerably. The objective of this analysis was to evaluate whether this population would benefit from higher doses of protein. ⋯ In critically ill patients with obesity, higher protein doses did not improve clinical outcomes, including those with higher nutritional and frailty risk.
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Pediatr Crit Care Me · Apr 2024
ReviewThe Pediatric Data Science and Analytics Subgroup of the Pediatric Acute Lung Injury and Sepsis Investigators Network: Use of Supervised Machine Learning Applications in Pediatric Critical Care Medicine Research.
Perform a scoping review of supervised machine learning in pediatric critical care to identify published applications, methodologies, and implementation frequency to inform best practices for the development, validation, and reporting of predictive models in pediatric critical care. ⋯ Publication of supervised machine learning models to address clinical challenges in pediatric critical care medicine has increased dramatically in the last 5 years. While these approaches have the potential to benefit children with critical illness, the literature demonstrates incomplete reporting, absence of external validation, and infrequent clinical implementation.
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Since the 1990s, time-limited trials have been described as an approach to navigate uncertain benefits and limits of life-sustaining therapies in patients with critical illness. In this review, we aim to synthesize the evidence on time-limited trials in critical care, establish what is known, and highlight important knowledge gaps. ⋯ Time-limited trials are endorsed by physicians, align with the priorities of some older adults, and are part of current practice. Substantial efforts are needed to test their impact on patient-centered outcomes, improve their implementation, and maximize their potential benefit.