A simple diagnostic scoring system for COVID-19 screening | [Anaesthesia, Pain and Intensive Care • 2022]

Author(s):

1. Yunita Widyastuti: Public Health, and Nursing, Universitas Gadjah Mada/Dr Sardjito General Hospital,Yogyakarta,Indonesia−55284

2. Djayanti Sari: Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada/Dr Sardjito General Hospital,Yogyakarta,Indonesia

3. Juni Kurniawaty: Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada/Dr Sardjito General Hospital,Yogyakarta,Indonesia

4. Untung Widodo: Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada/Dr Sardjito General Hospital,Yogyakarta,Indonesia

5. Calcarina Fitriani R.W: Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada/Dr Sardjito General Hospital,Yogyakarta,Indonesia

6. Akhmad Yun Jufan: Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada/Dr Sardjito General Hospital,Yogyakarta,Indonesia

7. Ketut Sutaendy: Air Force Central Hospital Dr Suhardi Hardjolukito,Bantul,Indonesia

8. Purnama Jaya: Air Force Central Hospital Dr Suhardi Hardjolukito, Bantul, Indonesia

9. 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.

Page(s): 785-793

DOI: 10.35975/apic.v26i6.2076

Published: Journal: Anaesthesia, Pain and Intensive Care, Volume: 26, Issue: 6, Year: 2022

Keywords:

COVID19 , Clinical symptoms , Laboratory Indicators , Screening System

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