Effects of underlying morbidities on the occurrence of deaths in COVID-19 patients: A systematic review and meta-analysis

Background Coronavirus disease 2019 (COVID-19), the most hectic pandemic of the era, is increasing exponentially and taking thousands of lives worldwide. This study aimed to assess the prevalence of pre-existing comorbidities among COVID-19 patients and their mortality risks with each category of pre-existing comorbidity. Methods To conduct this systematic review and meta-analysis, Medline, Web of Science, Scopus, and CINAHL databases were searched using pre-specified search strategies. Further searches were conducted using the reference list of the selected studies, renowned preprint servers (eg, medRxiv, bioRxiv, SSRN), and relevant journals’ websites. Studies written in the English language included if those were conducted among COVID-19 patients with and without comorbidities and presented survivor vs non-survivor counts or hazard/odds of deaths or survivors with types of pre-existing comorbidities. Comorbidities reported in the selected studies were grouped into eight categories. The pooled likelihoods of deaths in each category were estimated using a fixed or random-effect model, based on the heterogeneity assessment. Publication bias was assessed by visual inspection of the funnel plot asymmetry and Egger’s regression test. Trim and Fill method was used if there any publication bias was found. Results A total of 41 studies included in this study comprised of 27 670 samples. The most common pre-existing comorbidities in COVID-19 patients were hypertension (39.5%), cardiovascular disease (12.4%), and diabetes (25.2%). The higher likelihood of deaths was found among COVID-19 patients who had pre-existing cardiovascular diseases (odds ratio (OR) = 3.42, 95% confidence interval (CI) = 2.86-4.09), immune and metabolic disorders (OR = 2.46, 95% CI = 2.03-2.85), respiratory diseases (OR = 1.94, 95% CI = 1.72-2.19), cerebrovascular diseases (OR = 4.12, 95% CI = 3.04-5.58), any types of cancers (OR = 2.22, 95% CI = 1.63-3.03), renal (OR = 3.02, 95% CI = 2.60-3.51), and liver diseases (OR = 2.35, 95% CI = 1.50-3.69). Conclusions This study provides evidence that COVID-19 patients with pre-existing comorbidities had a higher likelihood of death. These findings could potentially help health care providers to sort out the most susceptible COVID-19 patients by comorbidities, take precautionary measures during hospitalization, assess susceptibility to death, and prioritize their treatment, which could potentially reduce the number of fatalities in COVID-19.

. Web of science search results for pre-existing morbidities among COVID-19 patients

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Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.

Data items
11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.

Risk of bias in individual studies
12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.
NA Summary measures 13 State the principal summary measures (e.g., risk ratio, difference in means). 7 Synthesis of results 14 Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I 2 ) for each meta-analysis. 7

Section/topic # Checklist item Reported on page #
Risk of bias across studies 15 Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies).

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Additional analyses 16 Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified.

Study selection
17 Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.

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Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations. Risk of bias across studies 22 Present results of any assessment of risk of bias across studies (see Item 15). 9 Additional analysis 23 Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression [see Item 16]).

DISCUSSION
Summary of evidence 24 Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).

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Limitations 25 Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias).

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Conclusions 26 Provide a general interpretation of the results in the context of other evidence, and implications for future research.

FUNDING
Funding 27 Describe sources of funding for the systematic review and other support (e.g., supply of data); role of funders for the systematic review.           Chronic digestive disorder