Print Get Citation Citation Disclaimer: These citations have been automatically generated based on the information we have and it may not be 100% accurate. Please consult the latest official manual style if you have any questions regarding the format accuracy. AMA Citation Shah R. Shah R Shah, Ravi. New scoring system proves effective in predicting COVID-19-related deaths and complications. 2 Minute Medicine, 22 July 2020. McGraw-Hill, 2020. AccessMedicine. https://accessmedicine.mhmedical.com/updatesContent.aspx?gbosid=551545§ionid=248705028APA Citation Shah R. Shah R Shah, Ravi. (2020). New scoring system proves effective in predicting covid-19-related deaths and complications. (2020). 2 minute medicine. McGraw-Hill. https://accessmedicine.mhmedical.com/updatesContent.aspx?gbosid=551545§ionid=248705028.MLA Citation Shah R. Shah R Shah, Ravi. "New scoring system proves effective in predicting COVID-19-related deaths and complications." 2 Minute Medicine McGraw-Hill, 2020, https://accessmedicine.mhmedical.com/updatesContent.aspx?gbosid=551545§ionid=248705028. Download citation file: RIS (Zotero) EndNote BibTex Medlars ProCite RefWorks Reference Manager Mendeley © Copyright Clip Full Chapter Figures Only Tables Only Videos Only Supplementary Content Top New scoring system proves effective in predicting COVID-19-related deaths and complications by Ravi Shah, MD MBA Listen +Originally published by 2 Minute Medicine® (view original article). Reused on AccessMedicine with permission. +1. Old age, coronary heart disease, percentage of lymphocytes, procalcitonin and D-dimer were independent factors predictive of in-hospital COVID-19-related mortality; a predictive model combining these variables performed well in predicting poor prognosis among high-risk patients +2. Use of systemic corticosteroids for patients deemed low risk as per the COVID-19 Scoring System predictive model was associated with longer hospitalization durations and durations of illness; there was no survival benefit in high-risk patients with the same. +Evidence Rating Level: 2 (Good) Study Rundown: + +Despite the novel coronvirus emerging as a global pandemic, identification and management remain challenging, in part due to a broad spectrum of disease presentations between severe and non-severe COVID-19 cases. +This retrospective cohort study sought to develop a risk model to predict mortality in patients with severe COVID-19 by identifying risk factors in three hospitals in Wuhan, China. After identifying 1830 COVID-19 patients, 452 (26.7%) were classified as severe. After calculating the weight associated with all available data, the COVID-19 Scoring System was (CSS) was developed, with the following factors identified as independently related to COVID-19 mortality: age 60-75 (1 point), age > 75 (2 points), coronary heart disease (1 point), lymphocyte count < 8% (1 point), procalcitonin > 0.15ng/mL (2 points) and D-dimer > 0.5 μg/mL (1 point). A score of 2 or less was considered low-risk, and 3 or more high-risk. The model demonstrated good prognostic accuracy, with mortality rates between low-risk and high-risk groups being 10.0% and 81.1%, respectively. For patients in the low-risk group, administration of systemic corticosteroids was associated with a significantly longer mean hospital duration and duration of disease. Corticosteroids also failed to improve survival in the high-risk group. Limitations of this study included the retrospective nature of the study, need for a larger validation cohort to more comprehensively validate the CSS, several missing lab values , and having only included the presence of lung lesions, and not the severity, in the scoring system. +Click to read the study in EClinicalMedicine +Relevant Reading: Prognostic factors associated with mortality risk and disease progression in 639 critically ill patients with COVID-19 in Europe: Initial report of the international RISC-19-ICU prospective observational cohort In-Depth [retrospective cohort]: + +This multi-center, retrospective cohort study of 452 patients with severe COVID-19 in Wuhan, China aimed to develop a COVID-19 Scoring System (CSS) to predict mortality using various health parameters. Of the 452 patients classified as severe (as per the Chinese management guidelines for COVID-9, version 7.0), 113 patients were included in the CSS training cohort. The average age at admission was 66.0 years, and 40 (35.4%) were female. Of the 52 parameters analyzed, old age, coronary heart disease, percentage of lymphocytes, procalcitonin and D-dimer were significantly associated with in-patient mortality. Combining these five variables, the CSS was developed and showed an independent relationship to mortality. The validation cohort was then stratified into low-risk (n= 60) and high-risk (n=54) groups based on their CSS score. The low-risk group had significantly lower mortality rates than the high-risk group (10.0% vs. 81.1%, p < 0.01), as well as longer median time from illness to death (34.5 days vs. 21.0 days, p=0.039). There was also a significantly higher rate of complications in the high-risk groups (including respiratory failure, sepsis, acute myocardial infarction, acute kidney injury, acute liver injury, acidosis, secondary infection and coagulopathy), except for sepsis. While the use of systemic corticosteroids in the low-risk group lengthened hospital stay (23.0 days average with steroids vs. 18.5 without, p=0.036) and lengthened disease length (34.5 days average with steroids vs. 27.0 without, p= 0.012), it did not affect survival for the high-risk group (21.0 days average with steroids vs. 15.0 without, p = 0.475). +©2020 2 Minute Medicine, Inc. All rights reserved. No works may be reproduced without expressed written consent from 2 Minute Medicine, Inc. Inquire about licensing here. No article should be construed as medical advice and is not intended as such by the authors or by 2 Minute Medicine, Inc.