Background: Patients with sepsis-induced hypotension are generally treated with a combination of intravenous fluids and vasopressors. The attributes of patients receiving a liberal compared to a restrictive fluid strategy have not been fully characterized. We use machine learning (ML) techniques to identify key predictors of restrictive versus liberal fluids strategy, and the likelihood of receiving each strategy in distinct patient phenotypes.
View Article and Find Full Text PDFInjury Severity Score (ISS) as a prospective predictive variable is limited, as it is scored post-discharge by registrars. We followed a phase 1 pilot investigation of the feasibility of prospective ISS estimation (eISS) by trauma surgeons within 1 day of admission with an investigation of the impact of a simple educational aid on the accuracy of these estimations. Eleven surgeons evaluated 178 patients in phase 2.
View Article and Find Full Text PDFBackground: Septic patients who develop acute respiratory failure (ARF) requiring mechanical ventilation represent a heterogenous subgroup of critically ill patients with widely variable clinical characteristics. Identifying distinct phenotypes of these patients may reveal insights about the broader heterogeneity in the clinical course of sepsis. We aimed to derive novel phenotypes of sepsis-induced ARF using observational clinical data and investigate their generalizability across multi-ICU specialties, considering multi-organ dynamics.
View Article and Find Full Text PDFInjury Severity Score (ISS) has limited utility as a prospective predictor of trauma outcomes as it is currently scored by abstractors post-discharge. This study aimed to determine accuracy of ISS estimation at time of admission. Attending trauma surgeons assessed the Abbreviated Injury Scale of each body region for patients admitted during their call, from which estimated ISS (eISS) was calculated.
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