A Retrospective Observational Study to Determine the Early Predictors of In-hospital Mortality at Admission with COVID-19

Jain, Aakanksha Chawla; Kansal, Sudha; Sardana, Raman; Bali, Roseleen Kaur; Kar, Sujoy Kumar; Chawla, Rajesh

doi:10.5005/jp-journals-10071-23683

Cited by 18 publications

(7 citation statements)

References 22 publications

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“…Overall, it is observed from a retrospective observational study that age >47 years, associated with comorbidities like hypertension and diabetes, hypoxia, tachycardia, lymphopenia, and raised inflammatory markers, are predictors of in-hospital mortality [26]. A similar thing was observed in the present study in both waves.…”

Section: Figure 3: Trend Of Covid-19 Cases In India (Authors Prepared...supporting

confidence: 89%

Comparative Study Between the First and Second Wave of COVID-19 Deaths in India: A Single Center Study

Tendulkar¹,

Pandey²,

Panda³

et al. 2023

Cureus

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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is continuously evolving, and many mutant variants of the virus are circulating in the world. Recurrent waves of COVID-19 have caused enormous mortality all across the globe. Considering the novelty of the virus, it becomes crucial for healthcare experts and policymakers to understand the demographic and clinical attributes of inpatient deaths in the first and second waves of COVID-19. MethodsThis hospital record-based comparative study was conducted at a tertiary care hospital in Uttarakhand, India. The study included all COVID-19 RT PCR-positive patients admitted to the hospital during the first wave, from 1 st April 2020 to 31 st January 2021, and the second wave from 1 st March 2021 to 30 th June 2021. Comparisons were made with respect to demographic, clinical, laboratory parameters, and course of hospital stay. ResultsThe study exhibited 11.34% more casualties in the second wave, with the number of deaths being 424 and 475 for the first and second waves, respectively. A male preponderance of mortality was evident in both waves with significant differences (p=0.004). There was no significant difference in age between the two waves (p=0.809). The significantly different comorbidities were hypertension (p=0.003) and coronary artery disease (p=0.014). The clinical manifestations demonstrating a significant difference were cough (p=0.000), sore throat (p=0.002), altered mental status (p=0.002), headache (p=0.025), loss of taste and smell (p=0.001), and tachypnea (p=0.000). The lab parameters with a significant difference across both waves were lymphopenia (p=0.000), elevated aspartate aminotransferase (p=0.004), leukocytosis (p=0.008), and thrombocytopenia (p=0.004). During the hospital course of the second wave, in terms of intensive care unit stay, the need for non-invasive ventilation and inotrope support was higher. The complications manifesting in the form of acute respiratory distress syndrome and sepsis were observed more in the second wave. A significant difference was discerned in the median duration of hospital stay in both waves (p=0.000). ConclusionDespite being of shorter duration, the second wave of COVID-19 culminated in more deaths. The study demonstrated that most of the baseline demographic and clinical characteristics attributed to mortality were more common during the second wave of COVID-19, including lab parameters, complications, and duration of hospital stays. The unpredictable nature of COVID-19 waves calls for instituting a well-planned surveillance mechanism in place to identify the surge in cases at the earliest possible time and prompt response, along with developing infrastructure and capacity to manage complications.

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Section: Figure 3: Trend Of Covid-19 Cases In India (Authors Prepared...supporting

confidence: 89%

Comparative Study Between the First and Second Wave of COVID-19 Deaths in India: A Single Center Study

Tendulkar¹,

Pandey²,

Panda³

et al. 2023

Cureus

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show abstract

“…Few studies from India suggested the same. [ 8 9 10 ] The present study also found higher COVID deaths in states with a higher proportion of people with diabetes and hypertension. However, no relation was found between preexisting chronic liver disease and COVID mortality.…”

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confidence: 72%

Factors associated with mortality from COVID 19

Roy

2021

Lung India

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“…9 Therefore, age is a prognostic factor for mortality because it is associated with comorbidities in the study population. 6 A decrease in glomerular filtration rate indicated by an increase in serum urea-creatinine was statistically associated as a predictor of death. Acute kidney injury (AKI) itself is a predictor of mortality in critically ill patients.…”

Section: Discussionmentioning

confidence: 93%

“…In a cohort study by Jain et al of 425 patients, patients aged >65 years had a high risk of mortality, the OR (4.034; 95% CI 1.68-9.71; p=0.002) of in-hospital mortality, but this finding was not that far off in comparison with patients aged >47 years. 6 Research by Estiri et al 9 also suggests that death occurs in two age groups, namely 45-65 and 65-85. The 45-65 years age group has a high risk of death due to underlying diseases such as DM and mean cancer, while 65-85 years is due to the pulmonary system, including interstitial lung disease, chronic obstructive pulmonary disease, lung cancer, and smoking history.…”

Section: Discussionmentioning

confidence: 98%

“…Several studies have shown this mortality predictor, including old age and the presence of various comorbid factors such as diabetes mellitus, chronic renal failure, and malignancy. 5,6 This study aims to determine the predictor of mortality of COVID-19 at Dr. Soetomo General Academic Hospital Surabaya and Airlangga University Hospital Surabaya to improve the case management of COVID-19 as well as predict the prognostic condition of the patient based on existing comorbidities.…”

Section: Introductionmentioning

confidence: 99%

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