key: cord-0699720-vybs1p56 authors: Bobdey, Saurabh; Chawla, Naveen; Behera, Vineet; Ray, Sougat; Ilankumaran, M.; Koshy, George; Kaushik, S.K. title: An analysis of mortality and survival of COVID 19 patients admitted to a tertiary care hospital in Maharashtra, India date: 2021-07-26 journal: Med J Armed Forces India DOI: 10.1016/j.mjafi.2021.02.004 sha: a768511f68c17c9a08ec252587c427ccf4de6b81 doc_id: 699720 cord_uid: vybs1p56 BACKGROUND: After nine months of responding to the coronavirus disease-19 (COVID-19) pandemic, the scientific fraternity is yet to unravel the mystery of those who are at most risk from mortality. Despite resistance to wear masks, the global public health response has beaten the grimmer projections of millions of deaths. The present study seeks to analyze the survival of COVID-19 patients at a tertiary care hospital and identify the risk factors of mortality. METHODS: Medical records of 1233 RT PCR confirmed COVID-19 patients admitted in a tertiary care hospital between 01 April and 30 September 2020 were retrospectively analyzed for calculating overall survival and to investigate the independent predictors of survival of COVID-19 patients. RESULTS: There were 72 (5.8%) deaths; which occurred in 24.9% of the elderly (age > 60yrs) people (P < 0.001), 76.0% in people with multiple comorbidities (having more than one comorbidity) (P < 0.001), 75.6% in people with diabetes (P < 0.001), and 75.5% in people with hypertension (P < 0.001). A significantly higher risk of mortality was observed in elderly patients, patients with comorbidities, and patients requiring oxygen while admitted in the hospital. CONCLUSION: Survival reflects the cure rates and is used by health professionals and policymakers to plan and implement disease control measures. The insights provided by the study would help facilitate the identification of patients at risk and timely provision of specialized care for the prevention of adverse outcomes in the hospital setting. The novel coronavirus disease has caused unprecedented stress on the health care system across the globe. Efforts to stratify clinical outcomes and predict survival are paramount for allocating resources and targeting interventions. 1 In India, from 30 January to 31 October 2020, there have been 82,67,623 confirmed cases of COVID-19, and more than one lac people have succumbed to the illness. 2 Health agencies across the globe have been closely monitoring the mortality of the COVID-19. China reported an overall 2.3% mortality rate among COVID-19 patients with a significantly higher mortality rate (14.8%) reported among the elderly patients (80 years or older). 3 In Italy, where more than 23% of residents were 65 or older, 4 the overall mortality rate was 5%, with 20% being elderly patients. 5, 6 Overall the mortality rates so far have ranged from 0.9% in Russia to 18.3% in France. 7 As per the recent reports, India is one of the worst affected countries in terms of the number of cases; however, in terms of case fatality, India does not figure in the list of top ten countries. In India, the survival rates vary widely between different states with Gujarat (6.2%), Madhya Pradesh (4.25), and Maharashtra (3.7%) reporting the highest mortality rates. 7 The disease continues to pose new challenges, and little is known with regard to the progression of the disease and its outcome. The exact reasons for the difference in mortality between and within the countries is still unknown, but as per the existing scientific knowledge, the difference has been postulated to be due to multiple reasons such as demographic profile, presence of comorbidities, genetic variation of the virus, etc. It is only time and research that will provide answers to this conundrum. However, as the disease continues to cause global mayhem, to face the pandemic and reduce death, it is essential to study factors that influence the risk of death from COVID-19. Survival reflects the cure rates and is a positive measure that can be used by health professionals and decision-makers to plan and implement measures for containing and combating the COVID-19 pandemic. The literature on the survival of COVID-19 patients and its prognostic factors is sparse. Hence, the present study was conducted to study survival and identify risk factors of mortality in RT PCReconfirmed COVID-19 patients admitted in a tertiary care hospital in western Maharashtra. Medical records of 1233 RT PCReconfirmed COVID-19 patients admitted in a tertiary care hospital between 01 April to 30 September 2020 were retrospectively analyzed. Data on the details of demography and clinical parameters were retrieved from the medical records section of the health department. Patients' overall survival (OS) duration was defined as the time interval between the date of diagnosis (positive test) and date of death or the date of discharge (patients were discharged after at least one negative RT PCR test), whichever was earlier. The entry point of each patient was different, and the event of interest was taken as death in the hospital. If the event had not occurred then the survival time was taken to be censored beyond the time of discharge. KaplaneMeier methods were used to estimate the OS by patient groups, and the log-rank test was used to compare survival curves. Factors that were found to be significantly related to survival, on univariate analysis, were considered in multivariate modelling. The Cox regression method was used to investigate the independent predictors of survival (estimating the survival function in presence of various covariates). All statistical analyses were performed using the Statistical Package for Social Science program (SPSS for Windows, version 20, SPSS, Chicago, IL, USA). P < 0.05 was considered to be statistically significant. The mean age of the patients was 41.63 (±17.63) years, 16.6% of cases were above the age of 60 years; 79.8% being male and 5.7% having comorbidity while on admission ( onset of symptoms until death/discharge was considered to be the study time variable. Using KaplaneMeier survival function, the 28-day OS was found to be 91.5%. Death occurred in 24.9% of the elderly people (patients of age more than 60 years) (P < 0.001), 76.0% in people with multiple comorbidities (having more than one comorbidity) (P < 0.001), 75.6% in people with diabetes (P < 0.001), 75.5% in people with hypertension (P < 0.001). Patients requiring oxygen support irrespective of the modality of O 2 delivery had higher mortality (11.9% expired) and patients requiring mechanical ventilation had the highest mortality (91.7%, P < 0.001). To study whether the duration of symptoms and provision of institutional care influenced survival, the time from onset of symptom to admission in the hospital was calculated and was analyzed with reference to the survival of the COVID patients. However, no difference in outcome was observed between patients who were admitted in hospital within 05 days of onset of symptoms and those beyond 05 days (p > 0.05) ( (Table 3 ). The state of Maharashtra had the highest number of COVID-19 cases and deaths in India till 31 October 2020. 7 Our study found that the survival of the COVID-19 patients in the hospital decreased with increasing age and patients of age more than 60 years were at higher risk of dying (HR 23.85, p < 0.01, 95% CI 3.09e183.89) than those in lower age groups. A study of 2070 COVID-19 patients from the northeast state of Brazil has also found that the elderly (more than 60 years) had a higher risk of dying in both the Poisson and Cox models. 8 In accordance with the Chinese Center for Disease Control, the mortality rate is largely influenced by the age of patients (>60 years), reaching 14.8% in those with >80 years. 9 Similarly, a higher risk of mortality due to COVID-19 in the elderly population has been reported by many national and international authors; 10 our study thus confirms the current epidemiology of the disease. In our study, women were found to be at a higher risk of death than men in univariate analysis; however, after adjustment (multivariate analysis), the difference was not found to be significant. A study from Mexico had reported that men were at higher risk of dying than women (HR 1.21, p < 0.01, 95% C.I. 1.09e1.35); however, this study had not adjusted for other factors. 11 Similar to our study, many researchers from various countries including India have reported no significant difference in survival between men and women. 8e10 The presence of comorbidities was found to adversely affect survival. The 28-day survival for individuals with comorbidities was found to 31.3% as compared with 95% for patients without comorbidities. Patients with single comorbidity such as diabetes or hypertension as well as with multiple comorbidities were found to have significantly lower survival than individuals with no comorbidities. Studies have reported higher circulating levels of cytokines such as interleukin-6 were found in COVID-19 patients with DM indicating the presence of an underlying proinflammatory milieu and it has been postulated as one mechanism linking DM to worse severity outcomes in COVID-19 patients. 12, 13 In multivariate analysis, the presence of comorbidity (HR 14.71, p < 0.01, 95% CI 8.24e26.27) was found to significantly affect the survival of COIVD-19 patients. This was in line with many studies which have reported that patients with COVID-19 disease who have comorbidities are more likely to experience more severe diseases and a higher risk of mortality. 8, 10, 14, 15 Oxygen desaturation and requirement of oxygen support in COVID-19 patients have been reported to be an indicator of disease progression and poor outcome. 16 In our study, patients requiring oxygen support were found to have higher mortality. The present study, despite having the distinction of being one of its kind in the Indian population, is not devoid of limitations. One of the major limitations of the study is that it is based on secondary data and only factors that were available in the database have been taken into consideration for survival analysis. Hence, certain important factors such as classification of the patients as per mild, moderate, and severe at the time of admission, presence of obesity, or clinical progression of the diseases including laboratory parameters could not be studied. However, even with limitations, the results presented by the article are similar to available scientific literature and provides an insight into the epidemiology of the disease, specifically in the Indian population. It has been more than a year since the first case of COVID-19 was reported in the world, but still, the disease continues to be a mystery posing new challenges to the practicing clinician and public health professionals in controlling the disease. Survival and mortality data from our study were similar to other studies conducted elsewhere. The available scientific literature indicates that the elderly and people with comorbidities have a higher risk of death and shorter survival. The present study is one of its kind in India to present mortality of COVID-19 and the survival of the patients affected by the disease. The insights provided by the study would help facilitate the identification of patients at risk and timely provision of specialized care for the prevention of adverse outcomes in a hospital setting. The authors have none to declare. r e f e r e n c e s Risk factors for hospitalization, mechanical ventilation, or death among 10 131 US Veterans with SARS-CoV-2 infection Government of India. PIB daily bulletin on COVID19 matters Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention Demographic science aids in understanding the spread and fatality rates of COVID Coronavirus disease 2019 (COVID-19) in Italy Case-Fatality Ratio and Recovery Rate of COVID-19: Scenario of Most Affected Countries and Indian States. Project: IIPS Research on COVID-19 Mortality and survival of COVID-19 Za Zhi Xue. Epidemiology working group for NCIP epidemic response, Chinese center for disease control and prevention Factors associated with COVID-19-related death using OpenSAFELY A survival analysis of COVID-19 in the Mexican population COVID-19: consider cytokine storm syndromes and immunosuppression Diabetes mellitus association with coronavirus disease 2019 (COVID-19) severity and mortality: a pooled analysis Comorbidities in COVID-19: outcomes in hypertensive cohort and controversies with renin angiotensin system blockers Comorbidity and its impact on patients with COVID-19 Factors affecting mortality in 1022 COVID-19 patients referred to an emergency department in Bergamo during the peak of the pandemic