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A simple diagnostic scoring system for COVID-19 screening

Author(s)
Yunita Widyastuti Public Health, and Nursing, Universitas Gadjah Mada/Dr Sardjito General Hospital,Yogyakarta,Indonesia−55284
Djayanti Sari Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada/Dr Sardjito General Hospital,Yogyakarta,Indonesia
Juni Kurniawaty Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada/Dr Sardjito General Hospital,Yogyakarta,Indonesia
Untung Widodo Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada/Dr Sardjito General Hospital,Yogyakarta,Indonesia
Calcarina Fitriani R.W Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada/Dr Sardjito General Hospital,Yogyakarta,Indonesia
Akhmad Yun Jufan Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada/Dr Sardjito General Hospital,Yogyakarta,Indonesia
Ketut Sutaendy Air Force Central Hospital Dr Suhardi Hardjolukito,Bantul,Indonesia
Purnama Jaya Air Force Central Hospital Dr Suhardi Hardjolukito, Bantul, Indonesia
Dinda Ulfa Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada/Dr Sardjito General Hospital,Yogyakarta,Indonesia
Abstract
Background: The COVID-19 pandemic has prompted the world to make various efforts to control its spread by finding ways to diagnose COVID-19 quickly and accurately. Early identification of COVID-19 infection is essential, especially in hospitals with limited resources. We aimed to generate two scores based upon clinical and laboratory findings in patients screen for COVID-19 infection. Methodology: This study used a retrospective cohort design that involved 705 adults (= 18 y old) admitted in Dr. Sardjito Hospital and Dr. S. Hardjolukito Hospital. The patients' data collected included demographic characteristics, anamnesis on signs and symptoms, history of contact with COVID-19 patients, history of staying or visiting an endemic area, comorbidities, and laboratory and radiologic indicators. All variables with a P < 0.25 on the bivariate test were included in a univariable logistic regression. If the P < 0.05, the variable was included in the multivariable logistic regression with a P < 0.05 considered significant. Receiver Operating Characteristic (ROC) producing an area under the curve (AUC) with 95% confidence intervals (CIs) was used to assess discrimination power. Results: Two scores were generated; score in Model 1 consisted of clinical signs, basic laboratory indicators, and chest X-ray, and in Model 2 consisted of clinical signs, chest X-ray, basic and advanced laboratory indicators, including C-reactive protein (CRP), lactate dehydrogenase (LDH), albumin, and D-dimer. The ROC score of Model 1 was 0.801 (0.764-0. 838), which is considered good discrimination, and of Model 2 had excellent discrimination with a ROC of 0.858 (0.826-0. 891); the differences in the ROC of the two models was statistically significant (P = 0.03). The score of Model 1 more than 5 had 85% sensitivity and 61% specificity of positive COVID-19. A score of Model 2 more than 4 had 83% sensitivity and 72% specificity for diagnosing positive COVID-19. Conclusions: A simple score consisting of clinical symptoms and signs, and simple laboratory indicators can be used to screen for COVID-19 infection.
Publication Details
Page(s) 785-793
Published Journal: Anaesthesia, Pain and Intensive Care, Volume: 26, Issue: 6, Year: 2022

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Keywords
COVID-19, Clinical symptoms, Laboratory Indicators, Screening System
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