Correction: Voriconazole-associated liver injury: clinical risk factor identification and predictive nomogram construction

Dongge Feng; Yiyi Ma; Xiaoyi Liu; Sheng Tang; Shijian Xiang; Yì Wáng; Shasha Li

doi:10.3389/fphar.2026.1834410

March 27, 2026SHILAP Revista de lepidopterologíaOpen Access

Correction: Voriconazole-associated liver injury: clinical risk factor identification and predictive nomogram construction

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Key Points

Identify key predictors of voriconazole-associated liver injury and develop a nomogram for risk prediction.
Retrospective analysis of electronic health records from patients using voriconazole.
Utilization of logistic regression and LASSO regression to identify independent risk factors.
Development of a nomogram for visual risk prediction and analysis using AUC for model performance.
Identified independent risk factors include glucocorticoids, ezetimibe, caspofungin, and elevated total cholesterol levels.
The nomogram achieved an AUC of 0.728 in the training set and 0.773 in the testing set.
The model demonstrated good calibration and clinical utility for guiding decision-making in high-risk patients.

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Implication

Retrospective analysis identifies risk factors and constructs a predictive model for liver injury in invasive fungal infections, suggesting enhanced clinical risk assessment.

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Cite This Study

Feng et al. (2026) studied this question.

synapsesocial.com/papers/69cb645fe6a8c024954b88fe https://doi.org/10.3389/fphar.2026.1834410

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Correction: Voriconazole-associated liver injury: clinical risk factor identification and predictive nomogram construction

Key Points

No abstract yet

Implication

Discussion

Cite This Study

Correction: Voriconazole-associated liver injury: clinical risk factor identification and predictive nomogram construction

Key Points

No abstract yet

Implication

Discussion

Cite This Study

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