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使用头孢美唑导致国际标准化比值升高的患者中危险因素的识别及预测模型的建立

Identification of risk factors and development of a predictive model in patients using cefmetazole for international normalized ratio elevation.

作者信息

Namiki Takaya, Yokoyama Yuta, Kimura Motonori, Fukuda Shogo, Seyama Shoji, Iketani Osamu, Samura Masaru, Ishikawa Haruki, Jibiki Aya, Kawazoe Hitoshi, Ohtani Hisakazu, Hasegawa Naoki, Matsumoto Kazuaki, Hashi Hideki, Suzuki Sayo, Nakamura Tomonori

机构信息

Division of Pharmaceutical Care Sciences, Keio University Graduate School of Pharmaceutical Sciences, Tokyo, Japan.

Department of Pharmacy, Tokyo Bay Urayasu Ichikawa Medical Center, Chiba, Japan.

出版信息

PLoS One. 2025 Jul 28;20(7):e0322909. doi: 10.1371/journal.pone.0322909. eCollection 2025.

Abstract

Patient risk factors related to coagulopathy and bleeding when using cefmetazole (CMZ) have not yet been identified, and no models exist to predict side effects during CMZ treatment. Moreover, reports that examine which patients should be careful when using CMZ to ensure safety are lacking. Our objective was to understand risk factors for elevated international normalized ratio (INR) in patients using CMZ and to develop a predictive model for INR elevation using a risk score to enable safe administration of CMZ. This multicenter, retrospective, and observational study was conducted in Tokyo Bay Urayasu Ichikawa Medical Center and Keio University Hospital using data from patients being treated with CMZ. Patients were classified into INR-elevated or non-INR-elevated groups. Univariate and multivariate analyses were performed to calculate the adjusted odds ratios (aOR) and 95% confidence intervals (CI). The actual probability of an elevated INR and probability of an elevated INR predicted by the regression β coefficients were calculated and classified into four categories according to the risk score. Binomial logistic regression analysis revealed that liver disorder (aOR, 5.65; 95% CI, 1.69-18.91; risk scores, 2), nutritional risk (aOR, 6.32; 95% CI, 3.14-12.74; risk scores, 2), no-diabetes mellitus (aOR, 4.53; 95% CI, 1.34-15.26; risk scores, 2), and warfarin use (aOR, 98.44; 95% CI, 7.05-1375.50; risk scores, 5) were significantly associated with INR elevation. The predicted incidence probabilities of INR elevation were < 5% (low risk), 5- < 30% (medium risk), 30- < 90% (high risk), and ≥ 90% (very high risk). The model validity showed a good fit (AUC, 0.79; 95% CI, 0.73-0.85, P < 0.001). We identified risk factors that contribute to INR elevation and constructed a model to predict INR elevation using the risk score. Using this predictive model enables the appropriate use of CMZ in a safe manner.

摘要

使用头孢美唑(CMZ)时与凝血病和出血相关的患者风险因素尚未明确,目前也没有模型可用于预测CMZ治疗期间的副作用。此外,缺乏关于哪些患者在使用CMZ时应格外小心以确保安全的报告。我们的目标是了解使用CMZ的患者国际标准化比值(INR)升高的风险因素,并使用风险评分开发一个预测INR升高的模型,以实现CMZ的安全给药。这项多中心、回顾性观察研究在东京湾浦安市市川医疗中心和庆应义塾大学医院进行,使用了接受CMZ治疗患者的数据。患者被分为INR升高组和非INR升高组。进行单因素和多因素分析以计算调整后的比值比(aOR)和95%置信区间(CI)。根据风险评分计算INR升高的实际概率以及回归β系数预测的INR升高概率,并将其分为四类。二项式逻辑回归分析显示,肝脏疾病(aOR,5.65;95%CI,1.69 - 18.91;风险评分,2)、营养风险(aOR,6.32;95%CI,3.14 - 12.74;风险评分,2)、非糖尿病(aOR,4.53;95%CI,1.34 - 15.26;风险评分,2)和使用华法林(aOR,98.44;95%CI,7.05 - 1375.50;风险评分,5)与INR升高显著相关。INR升高的预测发病概率为<5%(低风险)、5 - <30%(中等风险)、30 - <90%(高风险)和≥90%(非常高风险)。模型有效性显示拟合良好(AUC,0.79;95%CI,0.73 - 0.85,P < 0.001)。我们确定了导致INR升高的风险因素,并构建了一个使用风险评分预测INR升高的模型。使用这个预测模型能够以安全的方式合理使用CMZ。

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