In a recent study published in The International Journal of Environmental Research and Public Health , researchers identified independent factors associated with early and late deaths in hospitalized coronavirus disease 2019 (COVID-19) patients.
As of March 2022, COVID-19 has claimed over 6 million lives worldwide. This fatal infection due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly contagious and manifests acute life-threatening symptoms in some individuals, especially immunocompromised and hospitalized patients.
Several studies have examined the clinical condition in hospitalized COVID-19 patients. In a study conducted in France, the research team found that the median time from intensive care unit (ICU) admission to death was 14 days in patients with COVID-19; and the time of death varied according to comorbidities and severity of illness.
Determining and understanding the predictors of mortality concerning the time of death in COVID-19 patients could provide much-needed evidence to aid the clinical management of these patients.
About the study
In the present cohort study, researchers identified the factors associated with mortality in COVID-19 patients admitted to Taipei City Hospital (TCH) in Taipei, Taiwan between 14 May and 31 July 2021. The research team recruited COVID-19 patients of 18 years or above with a positive reverse-transcriptase polymerase chain reaction (RT-PCR) test. The follow-up with the study patients continued until death, hospital discharge, or up to 13 August 2021.
The primary variable of interest of the study was the treatment outcome, categorized as successful treatment or mortality; they further classified mortality – as early or late death. As per study definitions, early death referred to mortality within the first two weeks of hospitalization, and late death referred to mortality after two weeks of hospitalization.
The study covariates included socio-demographic characteristics (age and sex) and comorbidities. The researchers analyzed the demographic data of the study participants and presented it as standard deviation (SD). They used a one-way analysis of variance (ANOVA) for intergroup comparisons.
The team computed odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) for assessing the crude associations of factors related to mortality. Further, they reported adjusted ORs (AORs) with 95% CIs to indicate the strength and direction of the association of factors related to mortality.
They also performed a sex-based subgroup analysis to determine the factors associated with mortality. Additionally, using multinomial logistic regression, they examined the factors associated with early and late death among these patients.
The cohort study included 831 COVID-19 patients, with an overall mean age of 59.3 years; 49% of these patients were men, and 12.2% died during hospitalization. Notably, of the 101 deceased COVID-19 patients, 66 (65.3%) and 35 (34.7%) died early and late, respectively.
The deceased patients were older, more likely male, and suffered from a higher proportion of cancer rates, heart failure, as well as end-stage renal disease. These patients were also more likely to be admitted to the ICU and receive intubation treatment.
After adjusting for demographics, comorbidities, and disease severity, the uni-variate and multi-variate analyses showed AOR values (with 95% CIs) for independent predictors of mortality, including age ≥ 65 years, heart failure, and end-stage renal disease as 6.47, 11.67, and 18.67, respectively.
The subgroup analysis results showed that age ≥ 65 years was associated with a higher risk of mortality in both male and female COVID-19 patients; likewise, heart failure and end-stage renal disease were the predictors for mortality in male patients.
Taken together, the study findings showed that the overall mortality risk in hospitalized patients with COVID-19 was exceptionally high. Notably, two-thirds of COVID-19 deaths occurred within two weeks of hospitalization, and the observed median time from hospitalization to death, in such cases was six days.
Since the clinical condition of the hospitalized patients could deteriorate rapidly, it is crucial to monitor their clinical symptoms during the treatment, particularly for the elderly and those with comorbidities.
The observed in-hospital mortality rate of 12.2% among hospitalized patients was almost similar to 11.1% and 12.0% among hospitalized patients with COVID-19 in the US and UK, respectively.
Age over 65 years was found to be an independent predictor of early and late death in patients with COVID-19. Additionally, age-related defects in T-cell and B-cell function might explain the high mortality in older patients with COVID-19. Hence, the authors recommended prioritizing the elderly for antiviral treatment with sotrovimab, molnupiravir, and paxlovid to reduce the risk of mortality.
Previous studies showed that the male sex was associated with an increased expression of angiotensin-converting enzyme 2 (ACE2), which is known to be associated with severe COVID-19.
Hence, monitoring male patients with COVID-19 for their clinical condition during hospitalization is also recommended. Likewise, COVID-19 patients with heart failure or end-stage renal disease should be considered priority groups for COVID-19 treatment.
- Yen, Y.-F.; Chan, S.-Y.; Chen, C.-C.; Deng, C.-Y. (2022). Predictors for Early and Late Death in Adult Patients with COVID-19: A Cohort Study. International Journal of Environmental Research and Public Health. doi: https://doi.org/10.3390/ijerph19063357 https://www.mdpi.com/1660-4601/19/6/3357
Posted in: Medical Science News | Medical Research News | Disease/Infection News
Tags: ACE2, Angiotensin, Angiotensin-Converting Enzyme 2, Cancer, Cell, Coronavirus, Coronavirus Disease COVID-19, covid-19, Enzyme, Heart, Heart Failure, Hospital, Intensive Care, Mortality, Polymerase, Polymerase Chain Reaction, Public Health, Renal disease, Research, Respiratory, SARS, SARS-CoV-2, Severe Acute Respiratory, Severe Acute Respiratory Syndrome, Sotrovimab, Syndrome, T-Cell
Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.
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