Predictors for mortality of inpatients of COVID-19 in Mumbai

INTRODUCTION

The pandemic of coronavirus disease 2019 (COVID-19) has spread rapidly across the world causing increased mortality and hardships. On 19 April 2021 India has 10.7% of worlds cases and mortality rate of 1.19%.¹ To ensure optimal utilization of available resources and appropriate care to all the COVID-19 patients the COVID dedicated facilities were divided into three types namely COVID care center (CCC), dedicated COVID health centre (DCHC), dedicated COVID hospital (DCH).² COVID-19 has a broad spectrum of clinical manifestations ranging from asymptomatic cases to death. The accurate prediction of mortality in COVID-19 and the identification of contributing factors would allow for targeted strategies in patients with the highest risk of death. It can help in modifying the screening, treatment strategy and saving valuable lives. The published studies regarding the association of comorbidities to mortality from India are scarce.

Objectives of the study were to explore the risk factors of in-hospital deaths for COVID-19 patients.

METHODS

Study setting

This study was done in a large dedicated COVID hospital in Mumbai.

Study design and population

This was a hospital-based cross-sectional study. All COVID-19 patients positive on reverse transcriptase–polymerase chain reaction (RTPCR) test of nasopharyngeal or/and oropharyngeal samples who were admitted in this DCH from April to July 2020 and with definite outcome (death or discharge) till end of September 2020 were included in this study. Suspected cases of COVID-19 whose RTPCR never came positive were excluded. The information was collected in a predesigned proforma which included socio-demographic data, duration of stay, comorbidities, outcome, etc. by trained staff. Permission of institute ethics committee (IEC) was taken. Full confidentiality of respondent’s information was maintained and information was used only for research purpose.

Statistical analysis

Data entry was done by using Microsoft excel version 2010 and statistical analysis was done by using IBM statistical package for the social sciences (SPSS) statistics for windows, version 22. To explore the risk factors associated with in-hospital death univariate and multivariate logistic regression models (backward LR method) were used. As age category (0-20) years was having only one event it was excluded from final model. The multiple coefficients of determination (R²) was used as the goodness-of-fit statistic for the model. The level of significance was fixed at 0.05.

RESULTS

The 6195 COVID-19 patients who were admitted in this DCH from April to July 2020 and with definite outcome (death or discharge) till end of September 2020 were included in this study. This paper describes the socio-demographic and clinical profile of these 6195 patients. The age (mean±SD) of the patients was 46.44±17.1 years (range: 0.1-98 years) and majority 4147 (66.9%) were males. Of 6195 patients, 450 (7.26%) died. The duration of stay (mean±SD) was 12.74±8.22 days (range: 0-84 days). The duration from admission to death (mean±SD) was 10.4±10.42 days and for survivors the duration of hospital stay (mean±SD) was 12.93±7.99 days and the difference was statistically significant (p<0.001). Total 2303 (37.17%) patients had one or more morbidities. Total 952 (15.36%) patients required intensive care unit (ICU) support.

As seen in the Table 1, in univariate analysis more patients in the deceased group had diabetes (52.4% versus 18.9%; p<0.001), hypertension (54.9% versus 21.4%; p<0.001) and cerebrovascular or cardiovascular (CVD) diseases (14.9% versus 3.7%; p<0.001), chronic kidney diseases (CKD) (15.6% versus 4.2%; p<0.001), chronic obstructive pulmonary diseases (COPD) (1.3% versus 0.1%, p<0.001), hypothyroidism (4.4% versus 2.6%; p=0.03) and were middle aged (40-60 years) (38.9% versus 34.73%, p<0.001), elderly (>60 years) (60.9% versus 18.2%, p<0.001). All above differences were found to be statistically significant.There was no significant difference in the prevalence of asthma, cancer and history of tuberculosis between the two groups (p>0.05).

Multivariate regression analysis (Table 1) showed that age group of 41–60 years and ≥60 years, CVD, CKD, hypertension, diabetes mellitus were independent predictors of mortality. The Nagelkerke pseudo-R² value for the final model was 23.5%. The patients >60 years of age were at 17.42 times (CI: 10.55-28.75) higher risk, patients (41-60 years) of age were at 4.53 times (CI: 2.71-7.58) higher risk of death as compared to the age group 21-40 years.

*Statistically significant (p≤0.05), @column percentage, OR: odds ratio, CI: confidence interval

Also suffering from CKD [AOR (CI)=2.78(2.02-3.82)], diabetes mellitus [AOR (CI)=2.08(1.66-2.6)], CVD [AOR (CI)=1.57 (1.14-2.17)], Hypertension [AOR (CI)=1.43 (1.14-1.8)] were found to be the significant predictors of death after adjusting for potential confounders.

DISCUSSION

The case fatality rate (CFR) in our study was 7.26% which is more than CFR of India (1.19%), Maharashtra (1.58%), and Mumbai (2.13%) because many severe cases were admitted in this DCH.¹ Also we have included only those patients with definite outcomes while there are many active patients for India, Maharashtra and Mumbai’s CFR.¹ Variations in CFR can be due to time lags, differing quality of care or interventions being introduced at different stages of the illness, profile of patients (for example their age, sex, ethnicity and underlying comorbidities), case definitions, testing strategies.⁴ In a hospital based study in Jaipur CFR was 2.87% as 75.7% of their cases were asymptomatic.⁵ Many hospitals treating COVID-19 patients had much higher case fatality rate like DCH in Pune 29%, in hospitals in United States of America (USA) 8.2% and in China 28.3%.^6-8 The mean age of patients in Pune DCH was similar to our study and comorbidity percentage differed for some diseases.⁶ In another study in Pune DCH the CFR was 11.9%.⁹ In the study in USA and China the mean age was more and comorbidity percentage differed from our study.^7,8 Coordinated teamwork from the clinicians, administration and support staff of Seven Hills DCH along with proper diet and psychiatric counselling for COVID-19 patients can be the reasons for low CFR at Seven Hills DCH.³

In our study the mortality rate was more in age >40 years. Early Indian data suggested age >50-60 is showing mortality from states like Maharashtra unlike global 65 years of age.⁹ Many studies conclude morality is more in elderly.^6-16 There was some male preponderance in the number of inpatients, but there was no significant difference between the mortality rate of males and females. There were similar findings in some studies.^5,7,8,10,12 In our study diabetics had higher risk of dying than non-diabetics, some other studies had similar findings.^6-8,15-22 A study in China did not find such association. It can be due to smaller sample size.¹²

In our study patients suffering from hypertension and cardiovascular diseases had significantly increased mortality. Some studies had similar findings.^{6,7,15,16,20,22-26} In our study patients with CKD had higher risk of dying than patients not having CKD. There were similar findings in the studies in Pune and China.^6,27

In our study there was no significant difference in mortality rate in COVID-19 patients with reference to suffering from asthma, cancer or history of tuberculosis. A large mortality model prediction study in USA had similar findings.⁷ The proportion of patients suffering from COPD was much higher in deceased group than in survivors but the difference was not statistically significant in multivariable analysis.

A study by Du et al had similar findings but a large case series of patients from China showed higher case fatality rate in patients suffering from chronic respiratory disease and cancers.^12,14 The difference can be due to different types of cancers and chronic respiratory diseases.

The population groups at high-risk of mortality i.e. age >40 years, diabetes mellitus, cardiovascular diseases, hypertension, chronic kidney diseases should be considered as priority groups for receiving the COVID 19 vaccines. The clinical management protocol: COVID-19 guidelines by Government of India includes above predictors in their risk-factors for sever diseases along with chronic lung disease and cancer but in our study we did not find significant association between mortality due to COVID-19 and chronic lung disease or cancer.²⁸ The high risk groups should be given special attention during screening and treatment so as to prevent mortality.

This is a hospital based study and will differ from the situation in community. Obesity, history of alcohol, tobacco, duration of diabetes and hypertension was not assessed in our study.

CONCLUSION

Age >40 years, diabetes mellitus, cardiovascular diseases, hypertension, chronic kidney diseases are the independent predictors for mortality in COVID-19. These high risk groups should be given special attention during screening and treatment so as to prevent mortality.

ACKNOWLEDGEMENTS

Authors would like to thank the contributions made by all members of administrative team, the data handling team and all others functioning behind the curtains at this dedicated COVID-19 hospital in these tough and testing times of the COVID-19 pandemic.

Funding: No funding sources

Conflict of interest: None declared

Ethical approval: The study was approved by the Institutional Ethics Committee

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