Background One-fifth of COVID-19 patients are seriously and critically ill cases and have a worse prognosis than non-severe cases. Although there is no specific treatment available for COVID-19, early recognition and supportive treatment may reduce the mortality. The aim of this study is to develop a functional nomogram that can be used by clinicians to estimate the risk of in-hospital mortality in patients hospitalized and treated for COVID-19 disease, and to compare the accuracy of model predictions with previous nomograms. Methods This retrospective study enrolled 709 patients who were over 18 years old and received inpatient treatment for COVID-19 disease. Multivariable Logistic Regression analysis was performed to assess the possible predictors of a fatal outcome. A nomogram was developed with the possible predictors and total point were calculated. Results Of the 709 patients treated for COVID-19, 75 (11%) died and 634 survived. The elder age, certain comorbidities (cancer, heart failure, chronic renal failure), dyspnea, lower levels of oxygen saturation and hematocrit, higher levels of C-reactive protein, aspartate aminotransferase and ferritin were independent risk factors for mortality. The prediction ability of total points was excellent (Area Under Curve = 0.922). Conclusions The nomogram developed in this study can be used by clinicians as a practical and effective tool in mortality risk estimation. So that with early diagnosis and intervention mortality in COVID-19 patients may be reduced.
【저자키워드】 COVID-19, Mortality, nomogram, risk factor, Fatal outcome, 【초록키워드】 Cancer, Comorbidity, C-reactive protein, nomogram, risk, ferritin, oxygen, Intervention, outcome, COVID-19 disease, heart failure, Retrospective study, early diagnosis, oxygen saturation, Critically ill, Accuracy, Dyspnea, Patient, Aspartate aminotransferase, age, predictor, disease, in-hospital mortality, hematocrit, renal failure, mortality risk, Analysis, chronic renal failure, Regression, COVID-19 patient, chronic renal failure), Supportive treatment, clinician, independent risk factors, aspartate, worse prognosis, independent risk factor, specific treatment, Multivariable logistic regression analysis, renal, non-severe cases, effective, Result, enrolled, develop, died, was performed, reduced, treated, can be used, calculated, functional, reduce, survived, Area, patients hospitalized, patients treated, treatment for COVID-19, 【제목키워드】 risk, in-hospital mortality, retrospective cohort study, university hospital,