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

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

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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 obje...

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Main Authors: Takaya Namiki, Yuta Yokoyama, Motonori Kimura, Shogo Fukuda, Shoji Seyama, Osamu Iketani, Masaru Samura, Haruki Ishikawa, Aya Jibiki, Hitoshi Kawazoe, Hisakazu Ohtani, Naoki Hasegawa, Kazuaki Matsumoto, Hideki Hashi, Sayo Suzuki, Tomonori Nakamura
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0322909
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Summary: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.
ISSN:1932-6203

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