Predicting responsiveness to fixed-dose methylene blue in adult patients with septic shock using interpretable machine learning: a retrospective study.

ABSTRACT: This study aimed to develop an interpretable machine learning model to predict methylene blue (MB) responsiveness in adult patients with refractory septic shock and to identify key factors influencing MB responsiveness using the SHapley Additive exPlanations (SHAP) approach. We retrospectively analyzed data from 416 adult patients with refractory septic shock who received MB treatment at Xiangya Hospital of Central South University between June 2018 and October 2022. MB responders were defined as patients who, within 6 hours after MB administration, exhibited either a reduction in average norepinephrine equivalence (NEE) of ≥ 10% or an increase in mean arterial pressure of ≥ 10 mmHg without an associated increase in NEE. The incidence of MB responders was 38.2%(n=159). Statistical and mach

SUBMITTER: Xue S 

PROVIDER: S-EPMC11871053 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature