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Development and Alidation of a Risk Prediction Model for Tigecycline-Induced Drug-Induced Liver Injury was Developed and Validated
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Ya SUN1, Xu WANG2, Zhi SUN1, Yubing ZHOU1
Chinese Pharmaceutical Journal | 2025, 60(10) : 1057 - 1063
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Chinese Pharmaceutical Journal | 2025, 60(10): 1057-1063
Development and Alidation of a Risk Prediction Model for Tigecycline-Induced Drug-Induced Liver Injury was Developed and Validated
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Ya SUN1, Xu WANG2, Zhi SUN1, Yubing ZHOU1
Affiliations
  • 1 Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
  • 2 Department of Medical Records Management, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
Published: 2025-05-01 doi: 10.11669/cpj.2025.10.008
Outline
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OBJECTIVE To establish a predictive model for drug-induced liver injury (DILI) of tigecycline (TGC) to enable early recognition and management of high-risk patients. METHODS A retrospective study was performed on intensive care unit inpatients receiving TGC treatment at the first affiliated hospital of Zhengzhou university between January 2023 and March 2024. Demographics, medical history, admission characteristics, and treatment data were collected. Lasso-logistic regression analysis was used to identify risk factors for TGC-induced DILI. A nomogram was constructed based on these factors, and its predictive performance was assessed. RESULTS A total of 242 patients were enrolled, including 78 in the DILI group and 164 in the non-DILI group. The DILI group had higher proportions of females, age ≥60 years, alcohol consumption, acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ) scores ≥21, TGC treatment durations ≥14 d, TGC overdosing, and concomitant use of ≥3 d compared with the non-DILI group (P<0.05). Logistic regression analysis indicated that female, age≥60 years, APACHE Ⅱ score ≥21, TGC treatment duration ≥14 d, TGC overdosing, and concomitant use of≥3 medications were independent risk factors for TGC-induced DILI (P<0.05). The area under the curve (AUC) of the nomogram was 0.870 (95%CI: 0.795-0.952). Calibration curve analysis suggested good agreement between model predictions and observations, and the decision curve showed that the patients could obtain clinical benefit within the threshold range of 10%-95%. CONCLUSION Gender, age, APACHE Ⅱ score, TGC duration, TGC overdose and concomitant medication are risk factors of TGC-induced DILI, and the nomogram based on these variables has good clinical performance.

tegacycline  /  drug-induced liver injury  /  Lasso-logistic regression  /  influencing factor  /  prediction model  /  nomogram
Ya SUN, Xu WANG, Zhi SUN, Yubing ZHOU. Development and Alidation of a Risk Prediction Model for Tigecycline-Induced Drug-Induced Liver Injury was Developed and Validated[J]. Chinese Pharmaceutical Journal, 2025 , 60 (10) : 1057 -1063 . DOI: 10.11669/cpj.2025.10.008
Year 2025 volume 60 Issue 10
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doi: 10.11669/cpj.2025.10.008
  • Receive Date:2024-10-31
  • Online Date:2025-11-09
  • Published:2025-05-01
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  • Received:2024-10-31
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    1 Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
    2 Department of Medical Records Management, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
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表12种不同金属材料的力学参数

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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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