Evidence map›Paper›PMID 34449622›Full record

ArticleInfectious disease reports2021

Unusually High Risks of COVID-19 Mortality with Age-Related Comorbidities: An Adjusted Meta-Analysis Method to Improve the Risk Assessment of Mortality Using the Comorbid Mortality Data.

Andrew Antos, Ming Lai Kwong, Timothy Balmorez, Alyssa Villanueva, Shin Murakami

Abstract read
In one paragraph

Article in Infectious disease reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Andrew AntosDepartment of Basic Sciences, College of Osteopathic Medicine, Touro University California, 1310 Club Drive, Mare Island, Vallejo, CA 94592, USA.
Ming Lai KwongDepartment of Basic Sciences, College of Osteopathic Medicine, Touro University California, 1310 Club Drive, Mare Island, Vallejo, CA 94592, USA.
Timothy BalmorezDepartment of Basic Sciences, College of Osteopathic Medicine, Touro University California, 1310 Club Drive, Mare Island, Vallejo, CA 94592, USA.
Alyssa VillanuevaDepartment of Basic Sciences, College of Osteopathic Medicine, Touro University California, 1310 Club Drive, Mare Island, Vallejo, CA 94592, USA.
Shin MurakamiDepartment of Basic Sciences, College of Osteopathic Medicine, Touro University California, 1310 Club Drive, Mare Island, Vallejo, CA 94592, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe pandemic of Coronavirus Disease 2019 (COVID-19) has been a threat to global health. In the US, the Centers for Disease Control and Prevention (CDC) has listed 12 comorbidities within the first tier that increase with the risk of severe illness from COVID-19, including the comorbidities that are common with increasing age (referred to as age-related comorbidities) and other comorbidities. However, the current method compares a population with and without a particular disease (or disorder), which may result in a bias in the results. Thus, comorbidity risks of COVID-19 mortality may be underestimated.

objectiveTo re-evaluate the mortality data from the US and estimate the odds ratios of death by major comorbidities with COVID-19, we incorporated the control population with no comorbidity reported and assessed the risk of COVID-19 mortality with a comorbidity.

methodsWe collected all the comorbidity data from the public health websites of fifty US States and Washington DC (originally accessed on December 2020). The timing of the data collection should minimize bias from the COVID-19 vaccines and new COVID-19 variants. The comorbidity demographic data were extracted from the state public health data made available online. Using the inverse variance random-effects model, we performed a comparative analysis and estimated the odds ratio of deaths by COVID-19 with pre-existing comorbidities.

resultsA total of 39,451 COVID-19 deaths were identified from four States that had comorbidity data, including Alabama, Louisiana, Mississippi, and New York. 92.8% of the COVID-19 deaths were associated with a pre-existing comorbidity. The risk of mortality associated with at least one comorbidity combined was 1113 times higher than that with no comorbidity. The comparative analysis identified nine comorbidities with odds ratios of up to 35 times higher than no comorbidities. Of them, the top four comorbidities were: hypertension (odds ratio 34.73; 95% CI 3.63-331.91;

conclusionThe aforementioned comorbidities show surprisingly high risks of COVID-19 mortality when compared to the population with no comorbidity. Major comorbidities were enriched with pre-existing comorbidities that are common with increasing age (cardiovascular disease, diabetes, and hypertension). The COVID-19 deaths were mostly associated with at least one comorbidity, which may be a source of the bias leading to the underestimation of the mortality risks previously reported. We note that the method has limitations stemming primarily from the availability of the data. Taken together, this type of study is useful to approximate the risks, which most likely provide an updated awareness of age-related comorbidities.

Indexed as

age-related comorbidityCOVID-19mortalityrisk assessment

Identifiers

PMID34449622
PMCPMC8395741

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.