Clinical subphenotypes in septic patients with new-onset atrial fibrillation: validation and parsimonious classifier model development.

Abstract

Background: The substantial heterogeneity among septic patients with new‑onset atrial fibrillation (NOAF) complicates intensive care unit (ICU) management, and the absence of a parsimonious subphenotype classifier has impeded the implementation of personalized therapeutic strategies. In this study, we aim to identify the subphenotype of septic patients with NOAF, develop a concise classifier model, and reveal the differential efficacy of heart-rate control therapies across these subphenotypes.

Methods: This retrospective study utilized data from the Medical Information Mart in Intensive Care (MIMIC)-IV and MIMIC-III database. Consensus clustering based on hierarchical clustering was employed for subphenotype derivation. Nine supervised classifiers were employed to construct the subphenotype classifier, including random forest (RF), extreme gradient boosting (XGBoost), support vector machine (SVM), partial least squares (PLS), neural network (NN), naïve Bayes (NB), linear discriminant analysis (LDA), least absolute shrinkage and selection operator (LASSO), and adaptive boosting (AdaBoost.M1). Subphenotype-specific propensity score-derived stabilized inverse probability of treatment weights was used to weight comparisons of intensive care unit and hospital lengths of stay and discharge dispositions across subphenotypes.

Results: Among 1535 septic patients with NOAF, three distinct subphenotypes emerged: Phenotype A was the mildest subgroup; Phenotype B exhibited pronounced metabolic acidosis, highest anion gap, severe renal impairment, and elevated severity scores; Phenotype C showed intermediate laboratory values and score profiles with notable hyperchloremia and inflammatory markers. A parsimonious model established by SVM showed the best effectiveness. HR-control therapy was associated with subphenotype-specific reductions in hospital and ICU lengths of stay and more favorable discharge dispositions in Phenotype A, while more favorable survival outcomes were observed across all three subphenotypes in IPTW-weighted analyses.

Conclusion: Cluster analysis revealed three clinically relevant subphenotypes among septic patients with NOAF, each demonstrating distinct clinical outcomes and heterogeneous responses to heart rate control therapy.