Evidence map›Paper›PMID 34605767›Full record

ArticleJMIR cardio2021

The Effect of Cardiovascular Comorbidities on Women Compared to Men: Longitudinal Retrospective Analysis.

Elma Dervic, Carola Deischinger, Nils Haug, Michael Leutner, Alexandra Kautzky-Willer, Peter Klimek

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in JMIR cardio, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07703124 (Female-Specific Modifiers for Healthy Early Action in Cardiovascular Risk Trajectories), which is not on this map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.4field-weighted citation impact, top 17% 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.

NCT07703124 nanot yet recruitingnot on this mapstarted 2027, after this paper: background citation

Female-Specific Modifiers for Healthy Early Action in Cardiovascular Risk Trajectories

TypeinterventionalSponsorLudwig Boltzmann Institute for Cardiovascular ResearchRan2027 to 2031Enrolled605ConditionsPerimenopausal Women, Postmenopausal Female Patients, Cardiovascular (CV) RiskArmsPersonal training, App-based physical intervention
3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 13 citations in OpenAlex.

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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

6 authors at 3 institutions in 1 country.

Elma Dervic *Section for Science of Complex Systems, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.ORCID https://orcid.org/0000-0001-7168-3310
Carola Deischinger *Department of Internal Medicine III, Clinical Division of Endocrinology and Metabolism, Gender Medicine Unit, Medical University of Vienna, Vienna, Austria.ORCID https://orcid.org/0000-0003-4857-222X
Nils HaugSection for Science of Complex Systems, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.ORCID https://orcid.org/0000-0002-5130-9193
Michael LeutnerDepartment of Internal Medicine III, Clinical Division of Endocrinology and Metabolism, Gender Medicine Unit, Medical University of Vienna, Vienna, Austria.ORCID https://orcid.org/0000-0003-3959-1496
Alexandra Kautzky-WillerDepartment of Internal Medicine III, Clinical Division of Endocrinology and Metabolism, Gender Medicine Unit, Medical University of Vienna, Vienna, Austria.ORCID https://orcid.org/0000-0002-3520-4105
Peter KlimekSection for Science of Complex Systems, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.ORCID https://orcid.org/0000-0003-1187-6713
Medical University of Vienna · ATComplexity Science Hub · ATStatistics Austria · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough men are more prone to developing cardiovascular disease (CVD) than women, risk factors for CVD, such as nicotine abuse and diabetes mellitus, have been shown to be more detrimental in women than in men.

objectiveWe developed a method to systematically investigate population-wide electronic health records for all possible associations between risk factors for CVD and other diagnoses. The developed structured approach allows an exploratory and comprehensive screening of all possible comorbidities of CVD, which are more connected to CVD in either men or women.

methodsBased on a population-wide medical claims dataset comprising 44 million records of inpatient stays in Austria from 2003 to 2014, we determined comorbidities of acute myocardial infarction (AMI; International Classification of Diseases, Tenth Revision [ICD-10] code I21) and chronic ischemic heart disease (CHD; ICD-10 code I25) with a significantly different prevalence in men and women. We introduced a measure of sex difference as a measure of differences in logarithmic odds ratios (ORs) between male and female patients in units of pooled standard errors.

resultsExcept for lipid metabolism disorders (OR for females [ORf]=6.68, 95% confidence interval [CI]=6.57-6.79, OR for males [ORm]=8.31, 95% CI=8.21-8.41), all identified comorbidities were more likely to be associated with AMI and CHD in females than in males: nicotine dependence (ORf=6.16, 95% CI=5.96-6.36, ORm=4.43, 95% CI=4.35-4.5), diabetes mellitus (ORf=3.52, 95% CI=3.45-3.59, ORm=3.13, 95% CI=3.07-3.19), obesity (ORf=3.64, 95% CI=3.56-3.72, ORm=3.33, 95% CI=3.27-3.39), renal disorders (ORf=4.27, 95% CI=4.11-4.44, ORm=3.74, 95% CI=3.67-3.81), asthma (ORf=2.09, 95% CI=1.96-2.23, ORm=1.59, 95% CI=1.5-1.68), and COPD (ORf=2.09, 95% CI 1.96-2.23, ORm=1.59, 95% CI 1.5-1.68). Similar results could be observed for AMI.

conclusionsAlthough AMI and CHD are more prevalent in men, women appear to be more affected by certain comorbidities of AMI and CHD in their risk for developing CVD.

Indexed as

acute myocardial infarctioncardiovascular diseaseschronic ischemic heart diseasecomorbiditiesdiabetesgendergender gaprisk factorssex differencessmoking

Identifiers

PMID34605767
PMCPMC8723790
OpenAlexW3203728377

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.