Analysis of risk factors for piracetam-associated thrombocytopenia and the establishment of risk prediction model

HUANG Tianmin; LU Xingming; ZHENG Mei; GUO Guizong; LU Xin; LUO Yilin; YANG Yingxia

doi:10.6039/j.issn.1001-0408.2025.10.13

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Analysis of risk factors for piracetam-associated thrombocytopenia and the establishment of risk prediction model

更新时间：2025-09-23

- Analysis of risk factors for piracetam-associated thrombocytopenia and the establishment of risk prediction model
- ZHONGGUO YAOFANG Vol. 36, Issue 10, Pages: 1226-1231(2025)
- 作者机构：
  
  1.广西医科大学第一附属医院药学部，南宁　530021
  2.广西壮族自治区宾阳县人民医院药学部，南宁　530400
  3.广西医科大学教务处，南宁　530021
  4.百色市食品药品认证审评中心，广西百色　533000
- 作者简介：
- 基金信息：
- DOI：10.6039/j.issn.1001-0408.2025.10.13
  CLC： R969.3;R979.9
- Received：31 October 2024，
  
  Revised：2025-03-19，
  
  Accepted：01 April 2025，
  
  Published：30 May 2025
- 稿件说明：
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黄天敏,陆星名,郑媚,等.吡拉西坦相关血小板减少症的危险因素分析及其风险预测模型建立 [J].中国药房,2025,36(10):1226-1231.

HUANG Tianmin,LU Xingming,ZHENG Mei,et al.Analysis of risk factors for piracetam-associated thrombocytopenia and the establishment of risk prediction model[J].ZHONGGUO YAOFANG,2025,36(10):1226-1231.
黄天敏,陆星名,郑媚,等.吡拉西坦相关血小板减少症的危险因素分析及其风险预测模型建立 [J].中国药房,2025,36(10):1226-1231. DOI： 10.6039/j.issn.1001-0408.2025.10.13.

HUANG Tianmin,LU Xingming,ZHENG Mei,et al.Analysis of risk factors for piracetam-associated thrombocytopenia and the establishment of risk prediction model[J].ZHONGGUO YAOFANG,2025,36(10):1226-1231. DOI： 10.6039/j.issn.1001-0408.2025.10.13.

摘要

目的

分析吡拉西坦相关血小板减少症的危险因素，并建立其风险预测模型。

方法

回顾性收集广西医科大学第一附属医院2021年1月－2023年12月使用吡拉西坦治疗住院患者的电子病历信息，汇总性别、年龄、基础疾病、联合用药、实验室数据等临床资料。根据是否发生血小板减少症将患者分为发生组和未发生组，比较两组患者临床资料的差异。通过单因素/多因素Logistic回归分析确定独立危险因素，以列线图可视化展示，并构建风险预测模型；采用受试者工作特征（ROC）曲线、Bootstrap内部验证、校准曲线评估模型的预测效能。

结果

共纳入224例患者，其中未发生组196例、发生组28例，血小板减少症发生率为12.50%。单因素Logistic回归分析结果显示，发生组联用三联及以上抗菌药物的患者比例和血肌酐水平均显著高于未发生组，血红蛋白水平显著低于未发生组（

＜0.05）。多因素Logistic回归分析结果显示，联用三联及以上抗菌药物、低血红蛋白水平、高血肌酐水平是吡拉西坦相关血小板减少症的独立危险因素（

＜0.05）。所构建的风险预测模型为Logit

＝－1.114+1.256×联用三联及以上抗菌药物－0.017×血红蛋白水平+0.009×血肌酐水平。该模型ROC曲线的曲线下面积（AUC）为0.757，最佳截断值为0.474；Bootstrap内部验证的ROC曲线的AUC为0.733；未校准曲线、偏倚校准曲线均与参考曲线接近。

结论

联用三联及以上抗菌药物、低血红蛋白水平、高血肌酐水平是吡拉西坦相关血小板减少症的独立危险因素；所建风险预测模型具有良好的预测效能。

Abstract

OBJECTIVE

To analyze the risk factors contributing to piracetam-associated thrombocytopenia and develop a predictive model for risk prediction.

METHODS

The electronic medical record information of inpatients treated with piracetam was collected retrospectively from the First Affiliated Hospital of Guangxi Medical University from January 2021 to December 2023， including gender， age， underlying diseases， combined medication， and laboratory data， etc. Patients were divided into the occurrence group and the non-occurrence group according to whether thrombocytopenia occurred， and the differences in clinical data between the two groups were compared. The independent risk factors were determined through univariate/multivariate Logistic regression analysis. A nomogram was drawn to visually present the independent risk factors， and a risk prediction model was constructed. The predictive efficacy of the model was evaluated using the receiver operating characteristic （ROC） curve， Bootstrap internal validation and calibration curve.

RESULTS

A total of 224 patients were included， among which 196 cases were in the non-occurrence group and 28 cases in the occurrence group. The incidence of thrombocytopenia was 12.50%. The results of the univariate Logistic regression analysis showed that the proportion of patients using three or more combined antibiotics and the level of serum creatinine in the occurrence group were significantly higher than those in the non-occurrence group， while the level of hemoglobin was significantly lower （

＜0.05）. The results of the multivariate Logistic regression analysis revealed that the use of three or more combined antibiotics， low hemoglobin level and high serum creatinine level were independent risk factors for piracetam-associated thrombocytopenia （

＜0.05）. The constructed risk prediction model was Logit

＝－1.114+1.256×three or more combined antibiotics－0.017×hemoglobin level+0.009×serum creatinine level. The AUC of the ROC curve of this model was 0.757， and the optimal cut-off value was 0.474； the AUC of the ROC curve of the Bootstrap internal validation was 0.733； the apparent curve and the bias-corrected curve were close to the ideal curve.

CONCLUSIONS

The use of three or more antibiotics， along with low hemoglobin level and high serum creatinine level， are identified as independent risk factors for piracetam-associated thrombocytopenia. The developed risk prediction model demonstrates good predictive value.

关键词

Keywords

references

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