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Background Limited prior data suggest that preexisting liver disease is associated with adverse outcomes among patients with coronavirus disease 2019 (COVID-19). Fibrosis-4 (FIB-4) is a noninvasive index of readily available laboratory measurements that represents hepatic fibrosis. We evaluated the association between FIB-4 at the early stage of infection and COVID-19 outcomes. Methods FIB-4 was evaluated at admission in a cohort of 267 patients admitted with early-stage COVID-19 confirmed through reverse-transcription polymerase chain reaction assay. Hazard of ventilator use and of high-flow oxygen was estimated using Cox regression models controlled for covariates. Risks of progression to severe disease and of death/prolonged hospitalization were estimated using multivariable logistic regression models. Results Forty-one (15%) patients progressed to severe disease, 36 (14%) required high-flow oxygen support, 10 (4%) required mechanical ventilator support, and 1 died. FIB-4 between 1.45 and 3.25 was associated with a greater than 5-fold (95% confidence interval [CI], 1.2–28) increased hazard of high-flow oxygen use, a greater than 4-fold (95% CI, 1.5–14.6) increased odds of progression to severe disease, and an over 3-fold (95% CI, 1.4–7.7) increased odds of death or prolonged hospitalization. FIB-4 >3.25 was associated with a greater than 12-fold (95% CI, 2.3–68. 7) increased hazard of high-flow oxygen use and an over 11-fold (95% CI, 3.1–45) increased risk of progression to severe disease. All associations were independent of sex, number of comorbidities, and inflammatory markers (D-dimer, C-reactive protein). Conclusions FIB-4 at the early-stage of COVID-19 had an independent and dose-dependent association with adverse outcomes during hospitalization. FIB-4 provided significant prognostic value for estimating adverse outcomes among COVID-19 patients.

Approximately 15–20% of COVID-19 patients will develop severe pneumonia, and about 10% of these will die if not properly managed. Earlier discrimination of potentially severe patients basing on routine clinical and laboratory changes and commencement of prophylactical management will not only save lives but also mitigate the otherwise overwhelming healthcare burden. In this retrospective investigation, the clinical and laboratory features were collected from 125 COVID-19 patients who were classified into mild (93 cases) or severe (32 cases) groups according to their clinical outcomes after 3–7 days post-admission. The subsequent analysis with single-factor and multivariate logistic regression methods indicated that 17 factors on admission differed significantly between mild and severe groups but that only comorbidity with underlying diseases, increased respiratory rate (>24/min), elevated C-reactive protein (CRP >10 mg/L), and lactate dehydrogenase (LDH >250 U/L) were independently associated with the later disease development. Finally, we evaluated their prognostic values with receiver operating characteristic curve (ROC) analysis and found that the above four factors could not confidently predict the occurrence of severe pneumonia individually, though a combination of fast respiratory rate and elevated LDH significantly increased the predictive confidence (AUC = 0.944, sensitivity = 0.941, and specificity = 0.902). A combination consisting of three or four factors could further increase the prognostic value. Additionally, measurable serum viral RNA post-admission independently predicted the severe illness occurrence. In conclusion, a combination of general clinical characteristics and laboratory tests could provide a highly confident prognostic value for identifying potentially severe COVID-19 pneumonia patients.

Approximately 15-20% of COVID-19 patients will develop severe pneumonia, about 10 % of which will die if not properly managed. Earlier discrimination of the potential severe patients basing on routine clinical and laboratory changes and commencement of prophylactical management will not only save their lives but also mitigate the otherwise overwhelmed health care burden. In this retrospective investigation, the clinical and laboratory features were collected from 125 COVID-19 patients, who were classified into mild (93 cases) or severe (32 cases) groups according to their clinical outcomes after 3 to 7-days post-admission. The subsequent analysis with single-factor and multivariate logistic regression methods indicated that 17 factors on admission differed significantly between mild and severe groups, but that only comorbid with underlying diseases, increased respiratory rate (>24/min), elevated C-reactive protein (CRP >10mg/liter), and lactate dehydrogenase (LDH >250U/liter), were independently associated with the later disease development. Finally, we evaluated their prognostic values with the receiver operating characteristic curve (ROC) analysis and found that the above four factors could not confidently predict the occurrence of severe pneumonia individually, but that a combination of fast respiratory rate and elevated LDH significantly increased the predictive confidence (AUC= 0.944, sensitivity= 0.941, and specificity= 0.902). A combination consisting of 3- or 4-factors could further increase the prognostic value. Additionally, measurable serum viral RNA post-admission independently predicted the severe illness occurrence. In conclusion, a combination of general clinical characteristics and laboratory tests could provide high confident prognostic value for identifying potential severe COVID-19 pneumonia patients.SummaryWith our successful experience of treating COVID-19 patients, we retrospectively found that routine clinical features could reliably predict severe pneumonia development, thus provide quick and affordable references for physicians to save the otherwise fatal patients with the limited medical resource.