Evidence map›Paper›PMID 34715061›Full record

ArticleThe American journal of medicine2022

Sex Differences in Symptom Phenotypes Among Older Patients with Acute Myocardial Infarction.

John E Brush, Alexandra M Hajduk, Erich J Greene, Rachel P Dreyer, Harlan M Krumholz, Sarwat I Chaudhry

Open access · greenAbstract read
In one paragraph

Article in The American journal of medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 12% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Observational
  6. Article
  7. Article
  8. 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

6 authors at 3 institutions in 1 country.

John E BrushSentara Healthcare and Eastern Virginia Medical School, Norfolk. Electronic address: jebrush@mac.com.
Alexandra M HajdukSection of Geriatrics, Department of Internal Medicine, Yale School of Medicine, New Haven, Conn.
Erich J GreeneDepartment of Health Policy and Management and Department of Biostatistics, Yale School of Medicine, New Haven, Conn.
Rachel P DreyerSection of Cardiovascular Medicine, Department of Internal Medicine and Department of Emergency Medicine, Yale School of Medicine, New Haven, Conn; Yale School of Public Health; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Conn.
Harlan M KrumholzDepartment of Health Policy and Management and Department of Biostatistics, Yale School of Medicine, New Haven, Conn; Section of Cardiovascular Medicine, Department of Internal Medicine and Department of Emergency Medicine, Yale School of Medicine, New Haven, Conn; Yale School of Public Health; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Conn.
Sarwat I ChaudhrySection of General Internal Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Conn.
Yale New Haven Hospital · USYale University · USEastern Virginia Medical School · US

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
Risk Stratification in Older Persons with Acute Myocardial Infarction: SILVER-AMIR01HL115295 · NHLBI · YALE UNIVERSITY · PI CHAUDHRY, SARWAT I · 2012 to 2016
$11.3M
NCATS NIH HHS UL1 TR001863NHLBI NIH HHS R01 HL115295NIA NIH HHS P30 AG021342
6 · The paper itself

Abstract

backgroundClinicians make a medical diagnosis by recognizing diagnostic possibilities, often using memories of prior examples. These memories, called "exemplars," reflect specific symptom combinations in individual patients, yet most clinical studies report how symptoms aggregate in populations. We studied how symptoms of acute myocardial infarction combine in individuals as symptom phenotypes and how symptom phenotypes are distributed in women and men.

methodsIn this analysis of the SILVER-AMI Study, we studied 3041 patients (1346 women and 1645 men) 75 years of age or older with acute myocardial infarction. Each patient had a standardized in-person interview during the acute myocardial infarction admission to document the presenting symptoms, which enabled a thorough examination of symptom combinations in individuals. Specific symptom combinations defined symptom phenotypes and distributions of symptom phenotypes were compared in women and men using Monte Carlo permutation testing and repeated subsampling.

resultsThere were 1469 unique symptom phenotypes in the entire SILVER-AMI cohort of patients with acute myocardial infarction. There were 831 unique symptom phenotypes in women, as compared with 819 in men, which was highly significant, given the larger number of men than women in the study (P < .0001). Women had significantly more symptom phenotypes than men in almost all acute myocardial infarction subgroups.

conclusionsOlder patients with acute myocardial infarction have enormous variation in symptom phenotypes. Women reported more symptoms and had significantly more symptom phenotypes than men. Appreciation of the diversity of symptom phenotypes may help clinicians recognize the less common phenotypes that occur more often in women.

Indexed as

Myocardial InfarctionSex CharacteristicsFemaleHospitalizationHumansMalePhenotypeRisk FactorsSex FactorsAcute myocardial infarctionDiagnostic reasoningGender disparities

Identifiers

PMID34715061
PMCPMC8901454
OpenAlexW3209970645

What OpenQuestion holds

Textmetadata
LicenceTDM
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.