Identifying and preliminary validating patient clusters in coronary artery bypass grafting: integrating autonomic function with clinical and demographic data for personalized care.

Abstract

Aims: This study aims to identify distinct clusters of patients undergoing coronary artery bypass grafting (CABG) based on demographic, clinical, and autonomic function characteristics and to validate these clusters.

Methods and results: Our cohort study included 154 subjects aged 18 years and older undergoing CABG, enrolled in Italy, from April 2017 to January 2020. Data were prospectively collected from pre-anesthesia induction to hospital discharge. Clustering was performed using t-distributed stochastic neighbor embedding (t-SNE) on 23 variables and hierarchical clustering, including pre-and post-anesthesia autonomic function indices and demographic and clinical data. Two distinct clusters were identified: "Higher Risk-Responsive Group" and "Lower Risk-Responsive Group." The Higher Risk-Responsive Group cluster consisted of older patients with higher comorbidity rates and worse autonomic function. Validation of clusters through multiple correspondence analysis and Poisson regression demonstrated significant differences in postoperative outcomes. Patients in the Lower Risk-Responsive Group cluster had fewer complications (IRR = 0.441, p=0.004). The analysis indicated that intensive care unit (ICU) stay duration and the power of systolic arterial pressure series in low-frequency band derived in the post-anesthesia phase were significant predictors of complications above and beyond the expected contributions of age and comorbidities, with longer ICU stays and lower low-frequency power of systolic arterial pressure post-anesthesia induction being associated with higher complication rates.

Conclusion: Integrating autonomic function measures and demographic and clinical data could enhance patient monitoring and intervention, improving outcomes if included in future risk stratification tools and early warning score systems.

Registration: ClinicalTrials.gov: NCT03169608.