In-Hospital Mortality Predictors and a Bayesian Weighted-Incidence Antibiogram in Infective Endocarditis: A Seven-Year Cohort Study from a Mexican Tertiary 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. Calibration was assessed with bootstrap calibration plots and the Hosmer–Lemeshow test. 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% in a young cohort (median 37 years) characterized by high hemodialysis prevalence (47.4%), substantial right-sided IE (46.4%), and Staphylococcus aureus predominance (32%) with no methicillin-resistant isolates. Vasopressor-requiring 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 predictors; the final model achieved an AUC of 0.922 (optimism-corrected 0.908), significantly outperforming RiskE (0.598) and ICE (0.632). The Bayesian WISCA identified multiple carbapenem-sparing and anti-MRSA–sparing regimens with adequate coverage (≥80%), particularly for community-acquired IE, supporting stewardship-oriented empirical selection. Coverage was consistently lower in healthcare-associated IE. Conclusions: A parsimonious three-variable model provided strong, locally valid mortality prediction in this hemodialysis-predominant, MRSA-free cohort, substantially outperforming European-derived scores. External validation in independent cohorts is required before clinical adoption. The Bayesian WISCA demonstrated that adequate empirical coverage is achievable without routine broad-spectrum agents, offering institution-specific guidance for stewardship-compatible regimen selection; multicenter validation is warranted.