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Development and validation of a nomogram to assess the occurrence of liver dysfunction in patients with COVID-19 pneumonia in the ICU

Wang et al., BMC Infectious Diseases, doi:10.1186/s12879-025-10684-1
Mar 2025  
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Liver dysfunction -27% Improvement Relative Risk Paxlovid for COVID-19  Wang et al.  LATE TREATMENT Is late treatment with paxlovid beneficial for COVID-19? Retrospective 286 patients in China (November 2022 - February 2023) c19early.org Wang et al., BMC Infectious Diseases, Mar 2025 Favorspaxlovid Favorscontrol 0 0.5 1 1.5 2+
Retrospective 286 critically ill COVID-19 ICU patients developing a predictive model for liver dysfunction, showing significantly higher risk with azvudine and paxlovid use.
Resistance. Variants may be resistant to paxlovid1-6. Use may promote the emergence of variants that weaken host immunity and potentially contribute to long COVID7.
Confounding by contraindication. Hoertel et al. find that over 50% of patients that died had a contraindication for the use of Paxlovid8. Retrospective studies that do not exclude contraindicated patients may significantly overestimate efficacy.
Black box warning. The FDA notes that "severe, life-threatening, and/or fatal adverse reactions due to drug interactions have been reported in patients treated with paxlovid"9.
Kidney and liver injury. Studies show significantly increased risk of acute kidney injury10 and liver injury11.
Standard of Care (SOC) for COVID-19 in the study country, China, is poor with low average efficacy for approved treatments12.
Study covers azvudine and paxlovid.
liver dysfunction, 27.0% higher, OR 1.27, p < 0.001, treatment 51, control 235, adjusted per study, multivariable, RR approximated with OR.
Effect extraction follows pre-specified rules prioritizing more serious outcomes. Submit updates
Wang et al., 10 Mar 2025, retrospective, China, peer-reviewed, 3 authors, study period November 2022 - February 2023. Contact: xiekeliang2009@hotmail.com.
This PaperPaxlovidAll
Development and validation of a nomogram to assess the occurrence of liver dysfunction in patients with COVID-19 pneumonia in the ICU
Zhiwei Wang, Lina Zhao, Keliang Xie
BMC Infectious Diseases, doi:10.1186/s12879-025-10684-1
The global pandemic of novel coronavirus pneumonia (COVID-19) has resulted in millions of deaths over the past three years. As one of the most commonly affected extra-pulmonary organs, numerous studies have reported varying degrees of liver injury in a significant proportion of patients with COVID-19, particularly in severe and critically ill patients. Early prediction of liver dysfunction in hospitalized patients would facilitate the clinical management of COVID-19 and improve clinical prognosis, but reliable and valid predictive models are still lacking. Methods We collected data from 286 patients with RT-PCR confirmed COVID-19 admitted to various ICUs from the case system. These patients were randomly divided into a training cohort (50%) and a validation cohort (50%). In the training cohort, we first used ROC curves to measure the predictive efficiency of each of the variables for the development of liver damage during hospitalization in patients with COVID-19, followed by LASSO regression analysis to screen the variables for predictive models and logistic regression analysis to identify relevant risk factors. A nomogram based on these variables was created following the above model. Finally, the efficiency of the prediction models in the training and validation cohorts was assessed using AUC, consistency index (C index), calibration curves and Decision Curve Analysis. Results Out of a total of 80 parameters for COVID-19 patients admitted to the ICUs, 10 were determined to be significantly associated with the occurrence of liver dysfunction during hospitalization. Based on these predictors, further prediction models were used to construct and develop a nomogram that was offered for practical clinical application. The C-index of the column line graphs for the training and validation cohorts was 0.956 and 0.844 respectively. in addition, the calibration curves for the model showed a high degree of agreement between the predicted and actual incidence of liver dysfunction in patients with COVID-19. Conclusion By developing a predictive model and associated nomogram, we predicted the incidence of liver dysfunction during hospitalization in patients with COVID-19 in the ICU. The model's predictive performance was determined in both the training and validation cohorts, contributing to the clinical management of COVID-19.
Abbreviations Declarations Ethics approval and consent to participate This study was conducted in accordance with the principles of the Declaration of Helsinki and was approved by the Medical Ethics Committee of Tianjin Medical University General Hospital (Approval Number: IRB2022-YX-268-01) on December 29, 2022. All procedures involving human participants adhered to the ethical standards of the institutional and/or national research committee and the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Given the retrospective nature of this study and the use of anonymized medical records, the Medical Ethics Committee approved a waiver of written informed consent for patients with COVID-19. The waiver was granted as the research involved no more than minimal risk to the participants, and the data were anonymized to ensure privacy and confidentiality. Consent for publication Written informed consent for publication was obtained from all participants. Competing interests The authors declare no competing interests. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Late treatment
is less effective
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