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Ankara City Hospital COVID-19 Severity Score (ACCSES):A Calculation Tool in the Prediction of Severe Illness Requiring Intensive Care Follow-up
- Publication Year :
- 2020
- Publisher :
- Research Square Platform LLC, 2020.
-
Abstract
- Aim: The aim of this study is to develop and explain an easy-to-use severity score calculation tool to predict severe COVID-19 cases that would need intensive care unit (ICU) follow-up.Material method: The study was carried out in patients with laboratory-confirmed COVID-19 hospitalized in Ankara City Hospital between March 15, 2020, and June 15, 2020. The outcome was severe illness that required ICU follow-up. Univariate and binary logistic regression were used to create a prediction model by using potential predictive parameters obtained on the day of hospitalization. Youden’s J index was calculated with receiver-operator characteristic curves analysis in order to evaluate cut-off points, and predicted probability was calculated. The accuracy of the prediction model was tested by calculating the area under curve (AUC). Results: Of the total of 1022 patients, 152 had a severe illness and required ICU follow-up. Among 68 variables, 20 parameters met the potential predictive factor condition for severe illness and were included in the development process for ANKARA CITY HOSPITAL COVID-19 SEVERITY SCORE (ACCSES). The ACCSES calculation tool was created by the final 9 parameters (sex, oxygen saturation, hemoglobin, platelet count, glomerular filtration rate, aspartate transaminase, procalcitonin, ferritin, and D-dimer). AUC was 0.96 (95% CI, 0.95-0.98).Conclusion: We developed a simple, accessible, easy to use calculation tool, ACCSES, with good distinctive power for a severe illness that required ICU follow-up. The clinician can easily predict the course of COVID-19 and decide the procedure and facility of further follow-up simply using available clinical and laboratory values of patients upon admission.
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi...........1ccb8a4b2129459fa863c5157c3686f6
- Full Text :
- https://doi.org/10.21203/rs.3.rs-63960/v1