Evidence map›Paper›PMID 35612095›Full record

ArticleStudies in health technology and informatics2022

Using Big Data to Identify Impact of Asthma on Mortality in Patients with COVID-19.

Jinyan Lyu, Wanting Cui, Joseph Finkelstein

Open access · hybridAbstract read
In one paragraph

Article in Studies in health technology and informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
3.3field-weighted citation impact, top 9% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Association of Diagnostic Discrepancy with Length of Stay and Mortality in Congestive Heart Failure Patients Admitted to the Emergency Department.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024
    Article
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

3 authors at 1 institution in 1 country.

Jinyan LyuIcahn School of Medicine at Mount Sinai, USA.
Wanting CuiIcahn School of Medicine at Mount Sinai, USA.
Joseph FinkelsteinIcahn School of Medicine at Mount Sinai, USA.
Icahn School of Medicine at Mount Sinai · US

Funding

CD2H - The National COVID Cohort Collaborative (N3C) IDeA CTR CollaborationU24TR002306 · NCATS · UNIVERSITY OF COLORADO DENVER · PI CHUTE, CHRISTOPHER G, EICHMANN, DAVID A. · 2017 to 2021
$28.9M
NCATS NIH HHS U24 TR002306
6 · The paper itself

Abstract

The goal of this paper was to assess if mortality in COVID-19 positive patients is affected by a history of asthma in anamnesis. A total of 48,640 COVID-19 positive patients were included in our analysis. A propensity score matching was carried out to match each asthma patient with two patients without history of chronic respiratory diseases in one stratum. Matching was based on age, comorbidity score, and gender. Conditional logistics regression was used to compute within each strata. There were 5,557 strata in this model. We included asthma, ethnicity, race, and BMI as risk factors. The results showed that the presence of asthma in anamnesis is a statistically significant protective factor from mortality in COVID-19 positive patients.

Indexed as

AsthmaCOVID-19Big DataComorbidityHumansRetrospective StudiesRisk FactorsConditional Logistic RegressionCOVID-19Mortality

Identifiers

PMID35612095
PMCPMC10640797
OpenAlexW4281480507

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.