Risk Stratification for Cephalosporin-Induced Thrombocytopenia: Development and Validation of a Multidimensional Predictive Model in Older Adults.

OBJECTIVE

Third-generation cephalosporins, while widely prescribed, carry underquantified thrombocytopenia risks in older adults. This study aimed to develop and validate a clinical prediction model for cephalosporin-associated thrombocytopenia in hospitalized patients aged over 65 years.

METHODS

A retrospective cohort (2019~2023) initially included 45,779 cephalosporin treated patients. After applying exclusion criteria, 12,917 patients were analyzed. Predictors were selected via LASSO regression, with backward elimination multivariate logistic regression constructing a nomogram. Model performance was assessed using AUC, calibration curves, and decision curve analysis (DCA) in training and testing sets.

RESULTS

The final model identified eight predictors: baseline platelet count (PLT), red blood cell count (RBC), presence of tumor, renal insufficiency (RI), liver cirrhosis (LC), meropenem use, use of antifungal drugs (AD), and daily usage frequency (DUF). It demonstrated strong discrimination (training AUC 0.82 [95% CI 0.79-0.85]; testing AUC 0.80 [0.76-0.84]) and calibration (Brier score 0.057). DCA confirmed clinical utility across wide risk thresholds.

CONCLUSION

This nomogram tool enables rapid thrombocytopenia risk assessment in elderly patients receiving cephalosporins. Clinically, it guides antibiotic selection by quantifying comorbidity-drug interactions, and improves toxicity monitoring accuracy in complex geriatric cases with polypharmacy.