Propacetamol-related postoperative liver enzyme abnormalities: insights from a clinical prediction nomogram study

doi:10.5246/jcps.2025.04.025

Abstract

Abstract:

To investigate the correlation between propacetamol and postoperative liver enzyme abnormalities among patients, a retrospective analysis was conducted on inpatients in the thoracic surgery department spanning from January 1 to June 30, 2023. Causality assessment regarding propacetamol and postoperative liver enzyme abnormalities was performed using the updated Roussel Uclaf Causality Assessment Method (RUCAM). Furthermore, independent risk factors for liver enzyme abnormalities were identified through both univariate and multivariate analyses, followed by the construction and validation of a clinical nomogram. A total of 247 patients who received propacetamol were ultimately included in the study. Liver enzyme abnormalities post-surgery were more accurately predicted by considering the daily dose of propacetamol and the number of medications (OR (95% CI), 4.831 (2.797, 8.344), P < 0.001; 10.007 (3.878, 25.823), P < 0.001). A clinical predictive nomogram model was developed, incorporating these two independent risk factors, which exhibited favorable discrimination (AUC (95% CI), 0.811 (0.750, 0.872)), calibration, and decision curve analysis (DCA) demonstrating the highest net benefits across a broad spectrum of threshold probabilities (10% to 90%). The daily dose of propacetamol and the number of medications were found to be independently associated with postoperative liver enzyme abnormalities. This user-friendly nomogram, comprising these two factors, might assist clinicians in assessing the risks of propacetamol-related liver dysfunction following surgery.

Key words: Propacetamol, Nomogram, Liver enzyme abnormalities, Postoperative period, Drug-induced liver injury

Supporting:

Shuhong Liang, Haiyang Meng, Kai Kong, Chaoying Kang, Ning Liu, Qianqian Yuan, Jie Yang. Propacetamol-related postoperative liver enzyme abnormalities: insights from a clinical prediction nomogram study[J]. Journal of Chinese Pharmaceutical Sciences, 2025, 34(4): 334-344.

Figures/Tables 7

Table 1. Characteristics of the 247 patients enrolled in the study.

Table 2. Multivariate logistic regression analysis of the predictors.

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