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

IF 2 4区医学 Q2 HEALTH CARE SCIENCES & SERVICES

Risk Management and Healthcare Policy Pub Date : 2025-06-25 eCollection Date: 2025-01-01 DOI:10.2147/RMHP.S529488

Xiuyan Li, Wanlin Lei, Maofeng Wang, Lili Xu

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引用次数: 0

Abstract

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.

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头孢菌素诱导的血小板减少症的风险分层：老年人多维预测模型的开发和验证。

目的：第三代头孢菌素虽然被广泛使用，但在老年人中存在量化不足的血小板减少风险。本研究旨在建立并验证65岁以上住院患者头孢菌素相关血小板减少症的临床预测模型。方法：回顾性队列研究（2019~2023年）最初纳入45,779例头孢菌素治疗患者。应用排除标准后，对12917例患者进行分析。通过LASSO回归选择预测因子，并采用反向消除多元逻辑回归构建正态图。使用AUC、校准曲线和决策曲线分析（DCA）对训练集和测试集的模型性能进行评估。结果：最终模型确定了8个预测因素：基线血小板计数（PLT）、红细胞计数（RBC）、肿瘤的存在、肾功能不全（RI）、肝硬化（LC）、美罗培南的使用、抗真菌药物（AD）的使用和每日使用频率（DUF）。它显示出强烈的歧视(训练AUC 0.82 [95% CI 0.79-0.85]；检测AUC 0.80[0.76-0.84])和校准（Brier评分0.057）。DCA证实了广泛风险阈值的临床应用。结论：这种形态图工具可以快速评估接受头孢菌素治疗的老年患者的血小板减少风险。在临床上，它通过量化合并症-药物相互作用来指导抗生素的选择，并提高对复杂老年病例的毒性监测准确性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Risk Management and Healthcare Policy Medicine-Public Health, Environmental and Occupational Health

CiteScore

6.20

自引率

2.90%

发文量

242

审稿时长

16 weeks

期刊介绍： Risk Management and Healthcare Policy is an international, peer-reviewed, open access journal focusing on all aspects of public health, policy and preventative measures to promote good health and improve morbidity and mortality in the population. Specific topics covered in the journal include: Public and community health Policy and law Preventative and predictive healthcare Risk and hazard management Epidemiology, detection and screening Lifestyle and diet modification Vaccination and disease transmission/modification programs Health and safety and occupational health Healthcare services provision Health literacy and education Advertising and promotion of health issues Health economic evaluations and resource management Risk Management and Healthcare Policy focuses on human interventional and observational research. The journal welcomes submitted papers covering original research, clinical and epidemiological studies, reviews and evaluations, guidelines, expert opinion and commentary, and extended reports. Case reports will only be considered if they make a valuable and original contribution to the literature. The journal does not accept study protocols, animal-based or cell line-based studies.