Abstract
<title>Abstract</title> <p>Background Bloodstream infection (BSI) is associated with substantial morbidity and mortality among older adults. Existing prognostic tools primarily focus on acute illness severity and comorbidity burden but often fail to capture age-related physiological vulnerability.We evaluated the incremental prognostic value of a laboratory frailty index (FIlab) for predicting adverse outcomes in older patients with BSI. Methods This retrospective cohort study included 775 hospitalized patients aged ≥ 60 years with confirmed BSI at a single tertiary center. Missing data were handled using multiple imputation by chained equations (20 imputations). Logistic regression coefficients were pooled across all imputed datasets using Rubin's rules. A baseline model including age, sex, lactate, and creatinine (Model 0) was compared with models incorporating the Sequential Organ Failure Assessment (SOFA) score, Charlson Comorbidity Index (CCI), and FIlab. Model performance was assessed using discrimination (area under the receiver operating characteristic curve [AUC]), calibration, decision curve analysis (DCA), and bootstrap internal validation based on a representative imputed dataset. Incremental predictive value was quantified using category-free net reclassification improvement (cfNRI) and integrated discrimination improvement (IDI). Results Among 775 patients (median age 72 years; 64.8% male), 365 (47.1%) experienced adverse outcomes (death 91 [11.7%]; discharge without improvement 274 [35.4%]). In pooled multivariable analysis, FIlab remained independently associated with adverse outcomes (odds ratio [OR] 1.53 per 0.1-unit increase; 95% confidence interval [CI] 1.34–1.75; P < 0.001). The full model (Model 5) achieved an AUC of 0.679 (95% CI 0.642–0.717), representing a significant improvement over the base model (ΔAUC = 0.098; 95% CI 0.058–0.137; P < 0.001), with an optimism-corrected AUC of 0.667 (95% CI 0.661–0.679). A simplified model containing FIlab without SOFA or CCI (Model 4) demonstrated equivalent discrimination (AUC 0.679; DeLong P = 0.890). Adding FIlab to the base model yielded a cfNRI of 0.510 and an IDI of 0.071, suggested improved risk reclassification. DCA showed consistent net benefit across clinically relevant threshold probabilities (20%–50%). Sensitivity analysis using in-hospital mortality alone as the outcome confirmed the robustness of FIlab (OR 1.26 per 0.1-unit increase; 95% CI 1.04–1.53; P = 0.018). Conclusions FIlab is an independent predictor of adverse outcomes in older patients with BSI and improved risk stratification with moderate discrimination beyond conventional clinical variables. A simplified model incorporating FIlab may provide a practical tool for individualized prognostic assessment, pending external validation. Trial registration Clinical trial number: not applicable.</p>