ArticleBMC pharmacology & toxicology2024
Development and internal validation of a model for predicting cefoperazone/sulbactam-associated coagulation disorders in Chinese inpatients.
Article in BMC pharmacology & toxicology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Construction and temporal external validation of interpretable machine-learning models for predicting tigecycline-associated hypofibrinogenemia.European journal of clinical pharmacology · 2026Article
- Analytical approaches for medication management for patient safety: a scoping review.npj health systems · 2025Article
- Severe delayed coagulopathy caused by cefoperazone/sulbactam: A case report.The Journal of international medical research · 2025Article
- Towards a prescribing monitoring system for medication safety evaluation within electronic health records: a scoping review.BMC medical informatics and decision making · 2025Article
- Characteristics, risk factors and a risk prediction model of tocilizumab-induced hypofibrinogenemia: a retrospective real-world study of inpatients.BMC pharmacology & toxicology · 2025Article
- Risk Stratification for Cephalosporin-Induced Thrombocytopenia: Development and Validation of a Multidimensional Predictive Model in Older Adults.Risk management and healthcare policy · 2025Article
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Authors and funding
10 authors.
Funding
Abstract
BACKGROUND AND
aimThe use of cefoperazone/sulbactam (CPZ/SAM) could commonly cause vitamin K-dependent coagulation disorders and even hemorrhage sometimes. However, there is a lack of prediction tools estimating the risk for this. This study aimed at developing and internally validating a model for predicting CPZ/SAM-associated coagulation disorders in Chinese inpatients.
methodsA case-control study was conducted in 11,092 adult inpatients admitted to a Chinese general hospital between 2020 and 2021 and treated with CPZ/SAM. Patients with CPZ/SAM-associated coagulation disorders were identified through the Adverse Drug Events Active Surveillance and Assessment System-II and subsequent manual evaluation. Controls were selected from eligible patients who didn't develop coagulation disorders after CPZ/SAM therapy, with a 1:1 propensity score matching. The final predictors were obtained by univariable and multivariable logistic regression analyses. Internal validation and calibration for the model were performed using 1000 bootstrap resamplings.
results258 patients were identified as CPZ/SAM-associated coagulation disorders in 2184 patients eligible for inclusions and exclusions and the incidence was 11.8%. A final population of 252 cases and 252 controls was included for model development and validation. Malnutrition (OR = 2.41 (1.56-3.77)), history of recent bleeding (OR = 1.95 (1.32-2.90)), treatment duration (OR = 1.10 (1.07-1.14)), combination with carbapenems (OR = 4.43 (1.85-11.88)), and serum creatinine (OR = 1.01 (1.00-1.01)) were identified as final predictors. The model showed good discrimination, calibration, and clinical practicality, with the validated area under the receiver operating characteristic curve being 0.723 (0.683-0.770).
conclusionsThe model with good performance quantifies the risk for CPZ/SAM-associated coagulation disorders, and may support individual assessment and interventions to mitigate the risk after external validation.
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