Reply to: Comments on “Association of liver abnormalities with in-hospital mortality in patients with COVID-19”
Authors: Ze-yang Ding, Gan-xun Li, Chang Shu, Ping Yin, Bixiang Zhang
Journal: Journal of Hepatology (2021)

Risk stratification in hospitalized COVID-19 patientsJournal of HepatologyVol. 75Issue 3PreviewDing et al. recently published a retrospective analysis of potential predictors for mortality in 2,073 Chinese patients hospitalized with COVID-19.1 As their main findings, they reported that increased liver parameters as well as liver injury were predictive for 28-day mortality, and proposed a nomogram that estimates the mortality risk of hospitalized patients with COVID-19 disease. However, as the understanding of COVID-19 disease improves, it becomes evident that the disease may present differently in different regions. Full-Text PDF Association of liver abnormalities with in-hospital mortality in patients with COVID-19Journal of HepatologyVol. 74Issue 6PreviewThe evolution and clinical significance of abnormal liver chemistries and the impact of hepatitis B infection on outcome in patients with COVID-19 is not well characterized. This study aimed to explore these issues. Full-Text PDF Liver injury in COVID-19 – The culprit may not be COVID-19!Journal of HepatologyVol. 75Issue 3PreviewWe read the study by Ding et al1 with great interest. We congratulate the authors on conducting this large, multicentric study. They have demonstrated that raised levels of aspartate aminotransaminase and direct bilirubin at admission can be used as independent predictors of mortality in patients with coronavirus disease 2019 (COVID-19). They developed a prognostic model with a nomogram that can be used to predict the overall survival probability in patients with COVID-19. Importantly, they have reported that chronic HBV infection is not associated with an increased risk of lethal outcomes in patients with COVID-19. Full-Text PDF Letter regarding "Association of liver abnormalities with in-hospital mortality in patients with COVID-19"Journal of HepatologyVol. 75Issue 3PreviewWith great enthusiasm, we read a breakthrough study demonstrating the association of liver abnormalities with in-hospital mortality in patients with COVID-19.1 Integrating 10 candidate predictor parameters determined by multivariate regression analyses, Ding and colleagues formulated a novel prognostic nomogram to predict the survival of patients with COVID-19. However, several crucial pitfalls should be taken into account. Full-Text PDF We thank Singh et al., Horvath et al., and Luo et al. for their comments on our recent study.[1]Ding Z.Y. Li G.X. Chen L. Shu C. Song J. Wang W. et al.Association of liver abnormalities with in-hospital mortality in patients with COVID-19.J Hepatol. 2021; 74: 1295-1302Abstract Full Text Full Text PDF PubMed Scopus (68) Google Scholar In this study, we focused on investigating the association between abnormal liver chemistries at admission and in-hospital death, rather than the etiology of liver injury in COVID-19. We agree with comments from Singh et al. that liver injury in COVID-19 may not be attributable to COVID-19 infection alone, and associations of hypoxia, systemic inflammation, and hepatotoxic drugs with liver injury were explored in another study from our institute.[2]Fu Y. Zhu R. Bai T. Han P. He Q. Jing M. et al.Clinical features of patients infected with coronavirus disease 2019 with elevated liver biochemistries: a multicenter, retrospective study.Hepatology. 2021; 73: 1509-1520Crossref PubMed Scopus (42) Google Scholar In our study, parameters of hypoxic injury (severity of COVID-19) and systemic inflammation (abnormal C-reactive protein or interleukin-6 levels) are listed in the predictive model for COVID-19-related fatal outcome, and we did not find the use of traditional Chinese medicine drugs (univariate OR 0.895; 95% CI 0.738–1.085; p = 0.26, logistic regression analysis) or antiviral drugs (univariate OR 0.922; 95% CI 0.775–1.096; p = 0.357) before admission are associated with liver injury at admission. High flow oxygen or invasive ventilation was not used before admission, thus these parameters were not included in the predict model of our study. In addition, only 41 patients had oral use of lopinavir/ritonavir before admission, and 13 patients had history of alcohol abuse in the cohort. We performed sensitivity analyses by excluding these patients; the associations of (at admission) liver injury (adjusted HR 1.88; 95% CI 1.22–2.89; p = 0.004), abnormal aspartate aminotransferase (adjusted HR 1.37; 95% CI 1.01–1.83; p = 0.041) and abnormal direct bilirubin (adjusted HR 1.61; 95% CI 1.18–2.21; p = 0.003) with in-hospital death of COVID-19 patients were similar. Singh et al. mentioned that severity scoring systems of liver function were not described in our study. We and others have reported that serum levels of albumin, bilirubin, creatinine, prothrombin time, and international normalized ratio might be influenced by COVID-19 and result in deterioration of Child-Pugh, model for end-stage liver disease and Maddrey's discriminant function scores.[3]Iavarone M. D'Ambrosio R. Soria A. Triolo M. Pugliese N. Del Poggio P. et al.High rates of 30-day mortality in patients with cirrhosis and COVID-19.J Hepatol. 2020; 73: 1063-1071Abstract Full Text Full Text PDF PubMed Scopus (209) Google Scholar However, we were not able to retrieve pre-hospital status of liver function tests in these patients, thus we did not evaluate the baseline liver function of patients by using severity scores. Singh et al. also mention that the limited sample size of patients with chronic liver disease (CLD) in the cohort may account for the association of CLD and COVID-19-related mortality in our study. Notably, CLD constitutes a spectrum of diseases such as hepatitis B, MAFLD, cirrhosis, etc., and the prognosis of COVID-19 varies in patients with different CLD,[4]Marjot T. Webb G.J. Barritt ASt Moon A.M. Stamataki Z. Wong V.W. et al.COVID-19 and liver disease: mechanistic and clinical perspectives.Nat Rev Gastroenterol Hepatol. 2021; 18: 348-364Crossref PubMed Scopus (168) Google Scholar thus the association of CLD with COVID-19 mortality is always determined by the constitution of CLD in the investigated cohort, thus we suggested that the characteristics and outcome of COVID-19 patients with different CLD should be analyzed independently. We appreciate the work done by Horvath et al. They validated the robustness of our predictive model for COVID-19 mortality and simplified it in an Austrian cohort of COVID-19 patients. We tested the robustness of the simplified model in our cohort and found that this simplified predictive model can still predict 28-day mortality (HR 1.31; 95% CI 1.26–1.37; p <0.001). However, the simplified model showed reduced predictive accuracy in our cohort (AUC-difference -0.07; 95% CI -0.075 to -0.064; p <0.001) (Fig. 1A) and provided less net benefit across the range of fatal risk compared with the full model in decision curve analysis (Fig. 1B). We are expecting these predictive models to be validated in more cohorts in the future. Luo et al. raised concerns regarding the statistical analyses and suggested that it is better to use disease-specific survival instead of overall survival to build the nomogram. This suggestion lacks feasibility, as COVID-19 is an emerging infectious disease whose pathophysiology is still being explored, and there is still no consensus on disease-specific death of COVID-19.[5]Asselah T. Durantel D. Pasmant E. Lau G. Schinazi R.F. COVID-19: discovery, diagnostics and drug development.J Hepatol. 2021; 74: 168-184Abstract Full Text Full Text PDF PubMed Scopus (220) Google Scholar In addition, Luo et al. comments that based on the Riley's minimum sample size criteria,[6]Riley R.D. Ensor J. Snell K.I.E. Harrell Jr., F.E. Martin G.P. Reitsma J.B. et al.Calculating the sample size required for developing a clinical prediction model.BMJ. 2020; 368m441Crossref PubMed Scopus (455) Google Scholar a much larger sample size of 11,200 is required to establish a robust predictive model in our study. The predictive model in our study was used with an events per predictor parameter (EPP) of 20 (200 outcome events/10 parameters), which is compliant with the rule of thumb that a minimum of 10 EPPs is necessary for Cox models.[7]Gao F. Huang Z.M. The impact of COVID-19 on the clinical outcome of patients with cirrhosis deserves more attention and research.J Hepatol. 2020; 73: 1568-1569Abstract Full Text Full Text PDF PubMed Scopus (3) Google Scholar We noticed that when calculating sample size based on Riley's criteria, the short-term clinical course of COVID-19 leads to a very short anticipated mean follow-up (0.104 year), and results in the need for an impractically large sample size. Riley et al. only provide examples of investigating chronic diseases with anticipated mean follow-up of at least 2.07 years when introducing their methods of calculating sample size in prediction models for a time-to-event outcome.[6]Riley R.D. Ensor J. Snell K.I.E. Harrell Jr., F.E. Martin G.P. Reitsma J.B. et al.Calculating the sample size required for developing a clinical prediction model.BMJ. 2020; 368m441Crossref PubMed Scopus (455) Google Scholar Whether Riley's minimum sample size criteria are suitable for establishing predictive models of acute diseases needs to be confirmed and validated. In addition, the aim of the large sample size is to ensure the robustness of the predictive model, whereas this robustness has been internally validated by setting the bootstrap resampling cohort in our study and externally validated by Horvath et al. in an Austrian cohort. This work was funded by the research project for diagnosis and treatment of COVID-19 in Wuhan Tongji Hospital, China (XXGZBDYJ007 and XXGZBDYJ008), and the State Key Project on Infectious Diseases of China (2018ZX10723204-003). ZD and BZ: writing, critical revision and obtain funding; GL, CS and PY: statistical analysis and writing reply to comments involving statistical analysis. The data that support the findings of this study are available from the corresponding author upon reasonable request. All authors declare no conflict of interest. Please refer to the accompanying ICMJE disclosure forms for further details. The following is the supplementary data to this article: Download .pdf (.11 MB) Help with pdf files Multimedia component 1