Research Paper | Medicine | India | Volume 10 Issue 11, November 2021
Clinico-Demographic Characteristics and Laboratory Parameters Correlation with Severity Spectrum in COVID-19 Patients at a Peripheral Hospital of Indian Armed Forces
Abstract: Background: This study was conducted to describe the clinico-demographic characteristics and the laboratory parameters in symptomatic patients of COVID-19 from a peripheral hospital of Indian Armed Forces and to identify predictors of severity in COVID-19. Methodology: The study included consecutive 161 lab confirmed symptomatic cases between 05 Jul and 10 Oct 2020. Bivariate and multivariate logistic regression analysis of demographic, clinical and laboratory data was done to find predictors of severity in COVID-19. Results: The age of our patients ranged from 01 to 69 with male to female ratio of 8.47%. The clinical spectrum of 161 symptomatic patients included in the study showed mild, moderate, and severe disease in 81.37%, 15.53% and 3.11% respectively. There were two (CFR=1.18%) deaths. Diabetes Mellitus was the most commonly observed comorbidity. Fever was the most common presenting symptom. Baseline N/L ratio > 3 and CRP positivity was seen in 13 (8.07%) patients with specificity and PPV of 100% for progression in severity spectrum. Conclusion: In our study, we recommend that age > 40 years, any comorbidity, and baseline raised ESR, renal functions, random blood sugar, and N/L ratio > 3 with positive CRP be used as the predictors for higher severity in COVID-19 patients.
Keywords: COVID-19; Severity Spectrum; Predictors; Clinico-Demographic; Laboratory Parameters; Peripheral Hospital
Edition: Volume 10 Issue 11, November 2021,
Pages: 1283 - 1290
How to Cite this Article?
Amit Sharma, "Clinico-Demographic Characteristics and Laboratory Parameters Correlation with Severity Spectrum in COVID-19 Patients at a Peripheral Hospital of Indian Armed Forces", International Journal of Science and Research (IJSR), https://www.ijsr.net/get_abstract.php?paper_id=SR211126140137, Volume 10 Issue 11, November 2021, 1283 - 1290, #ijsrnet
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