In-Hospital Mortality Predictors and a Bayesian Weighted-Incidence Antibiogram in Infective Endocarditis: A Seven-Year Cohort Study from a Referral University Hospital

Background/Objectives: Infective endocarditis (IE) carries substantial mortality, particularly in middle-income settings where patient profiles and microbial ecology differ from those of cohorts used to derive international prognostic scores. Syndrome-specific, locally grounded decision aids for empirical therapy are also scarce. We aimed to identify predictors of in-hospital mortality, externally evaluate the RiskE and ICE scores, and construct a Bayesian weighted-incidence syndromic combination antibiogram (WISCA) for IE. Methods: We conducted a retrospective cohort study of consecutive adults with definite or possible IE admitted between January 2019 and January 2026. Candidate predictors were screened in two phases and a clinically specified model was estimated with maximum-likelihood and Firth penalization, with 1000-replicate bootstrap optimism correction. Discrimination was compared against RiskE and ICE using DeLong’s test and reclassification metrics. For empirical coverage, we built a WISCA using identified pathogens, reporting both non-Bayesian bootstrap estimates and Bayesian hierarchical partial-pooling estimates with species- and antibiotic-level random intercepts; analyses were also stratified by IE type. Results: In-hospital mortality was 22.9%. Septic shock (Firth OR 9.23, 95% CI 2.40–40.61) and acute heart failure (OR 10.01, 95% CI 2.78–41.07) were the strongest independent predictors; the final model achieved an AUC of 0.922 (optimism-corrected 0.908) and outperformed RiskE (AUC 0.598) and ICE (AUC 0.632). Bayesian WISCA ranked vancomycin + gentamicin and meropenem + gentamicin highest (both 87.0%); several β-lactam–based combinations provided comparably high coverage without requiring routine carbapenems. Coverage was consistently higher for community-acquired than healthcare-associated IE. Conclusions: A simple variable model provided strong, locally valid mortality prediction and substantially outperformed international scores in this hemodialysis-predominant cohort. Bayesian WISCA offers stable, institution-specific empirical coverage estimates that can support stewardship-oriented regimen selection; multicenter validation is warranted.