Evidence map›Paper›PMID 33937569›Full record

ArticleGlobal health & medicine2021

Epidemiological correlation between COVID-19 epidemic and prevalence of α-1 antitrypsin deficiency in the world.

Hiroshi Yoshikura

Open access · bronzeAbstract read
In one paragraph

Article in Global health & medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.0field-weighted citation impact, top 29% of its field
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

14 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
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  5. COVID-19 in Individuals with Severe Alpha 1-Antitrypsin Deficiency.International journal of chronic obstructive pulmonary disease · 2024
    Article
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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

1 author at 1 institution in 1 country.

Hiroshi YoshikuraEmeritus Member, National Institute of Infectious Diseases, Tokyo, Japan.
National Institute of Infectious Diseases · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Among 68 countries in the world, severity of the COVID-19 epidemic was correlated with the prevalence of α-1 antitrypsin (AAT) deficiency. For the severe variant, PI*Z, the correlation coefficient (CC) was 0.8584 for the number of patients and 0.8713 for the number of deaths. For the milder variant, PI*S, it was 0.5818 and 0.6326, respectively. In Japan, the number of patients and deaths correlated with the population size with a CC of 0.6667 and 0.7074 respectively, and was proportional to the population size to the power of 1.65 and 1.54. The prevalence of AAT deficiency also correlated with the epidemiological pattern of COVID-19. In countries with high prevalence of AAT deficiency, after the initial rise, the daily number of patients and that of deaths ran parallel at a high level for more than 6 months without sign of abatement. In countries with a low prevalence of AAT deficiency, after the first wave of the epidemic, the number of the deaths decreased continuously while the number of patients remained the same or even increased resulting in a decreasing case-fatality rate. When the cumulative number of deaths was plotted on the y-axis against the cumulative number of patients on the x-axis, plots fell on a straight line in countries with a high prevalence of AAT deficiency; while in countries with a low prevalence of AAT deficiency, a break appeared, after which the plots fell on flatter slope indicating decreasing case-fatality rate. The observation suggests emergence of an attenuated variant in countries with a low prevalence of AAT deficiency.

Indexed as

adaptationcase-fatalitycoronavirusCOVID-19quasi-species

Identifiers

PMID33937569
PMCPMC8071687
OpenAlexW3092308689

What OpenQuestion holds

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Registered trials

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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.