Evidence map›Paper›PMID 37377522›Full record

ArticleCJC open2023

Young Women With Acute Myocardial Infarction: Risk Prediction Model for 1-Year Hospital Readmission.

Rachel P Dreyer, Andrew Arakaki, Valeria Raparelli, Terrence E Murphy, Sui W Tsang, Gail D'Onofrio, Malissa Wood, Catherine X Wright, Louise Pilote

Abstract read
In one paragraph

Article in CJC open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

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  5. Review
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

9 authors.

Rachel P DreyerDepartment of Emergency Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
Andrew ArakakiDepartment of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut, USA.
Valeria RaparelliDepartment of Translational Medicine, University of Ferrara, Ferrara, Italy.
Terrence E MurphyProgram on Aging, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
Sui W TsangProgram on Aging, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
Gail D'OnofrioDepartment of Emergency Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
Malissa WoodMassachusetts General Hospital Heart Centre, Boston, Massachusetts, USA.
Catherine X WrightDepartment of Cardiovascular Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
Louise PiloteCentre for Outcomes Research and Evaluation, McGill University Health Centre Research Institute, Montreal, Quebec, Canada.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Yale Study Support Suite (YES3): Dashboard and Web Portal Software Supporting Research Workflow through integrated, customizable REDCap External ModulesP30AG021342 · NIA · YALE UNIVERSITY · PI Albert C Shaw · 2002 to 2026
$37.9M
NCATS NIH HHS UL1 TR001863NIA NIH HHS P30 AG021342
6 · The paper itself

Abstract

Background: Although young women ( aged ≤ 55 years) are at higher risk than similarly aged men for hospital readmission within 1 year after an acute myocardial infarction (AMI), no risk prediction models have been developed for them. The present study developed and internally validated a risk prediction model of 1-year post-AMI hospital readmission among young women that considered demographic, clinical, and gender-related variables. Methods: We used data from the US Results: Within 1-year post-AMI, 684 women (34.1%) were readmitted to the hospital at least once. The final model predictors included: any in-hospital complication, baseline perceived physical health, obstructive coronary artery disease, diabetes, history of congestive heart failure, low income ( < $30,000 US), depressive symptoms, length of hospital stay, and race (White vs Black). Of the 9 retained predictors, 3 were gender-related. The model was well calibrated and exhibited modest discrimination (area under the curve = 0.66). Conclusions: Our female-specific risk model was developed and internally validated in a cohort of young female patients hospitalized with AMI and can be used to predict risk of readmission. Whereas clinical factors were the strongest predictors, the model included several gender-related variables (ie, perceived physical health, depression, income level). However, discrimination was modest, indicating that other unmeasured factors contribute to variability in hospital readmission risk among younger women.

Identifiers

PMID37377522
PMCPMC10290947

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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.