Trends and clinico-epidemiological profile of COVID-19 patients at a designated COVID-19 hospital in Delhi, North India
Mona Bargotya, BankeLal Sherwal, Namrata Makkar, Ajeet Jain, Vikas Dogra, S. Durga Prasad, Ashish Sachan, Ragi Jain, Aarti Gupta, Smita Gulati, Sonali Bhattar
Abstract
Background: The coronavirus disease (COVID-19) presents across a spectrum of signs and symptoms and shows clinico-epidemiological predilections (elderly, those with comorbidities). Delhi is among the highest burden states in India. Objectives: To report the case detection trends and clinico-epidemiological profile of patients tested positive at a designated COVID-19 hospital in Delhi in Northern India. Methods: Using an observational (descriptive design) we analyzed data from the electronic medical records of the hospital. All individuals testing positive for SARS-CoV-2 RNA using reverse transcription polymerase chain reaction (RT-PCR) between 17th March and 07th May 2020 (both dates inclusive) were included. Case detection trend (7-day moving averages) was plotted. Clinico-epidemiological profile of patients was summarized statistically. Results: Total 308 positive cases were enrolled in this study. The median age of participants was 48 years (09–95 years) men (47.9 ± 16.4 years) and women (43.5 ± 14.0 years). Men to women ratio was 3.4:1 with a statistically significant difference (P < 0.001). During the study timeframe, 166 (54.0%) patients had an outcome: 11 (6.6%; 95% CI: 3.4–11.6) expired and 155 recovered (recovery rate: 93.4%; 95% CI: 88.5–96.7). Chance of death was significantly associated with the higher age group (P = 0.005). The commonest clinical symptoms noted were fever (38.9%) and cough (38.6%). Majority (56.6%) had mild to moderate symptoms, 12.6% had severe symptoms and the remaining were asymptomatic (30.8%). 31 patients (26.05%) needed ICU care. Total 119 patients (38.6%) had various preexisting comorbidities, most commonly diabetes mellitus (35.0%) and hypertension (34.0%). However, the comorbidities were not associated with age (P = 1.000). Conclusion: Triangulation of data and careful analysis of trends in designated COVID-19 hospitals and other institutional settings may help inform surge preparedness and care provisioning. Stringent containment strategies must continue as the pandemic is intensifying.