Evidence map›Paper›PMID 39158558›Full record

ArticleJournal of the American Heart Association2024

Measuring Frailty Using Self-Report or Automated Tools to Identify Risk of Cardiovascular Events and Mortality: The Million Veteran Program.

Saadia Qazi, Benjamin Seligman, Sarah R Preis, Manas Rane, Luc Djousse, David R Gagnon, Peter W F Wilson, J Michael Gaziano, Jane A Driver, Kelly Cho and 2 more

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. What Do We Know About Prevention of Frailty in Women?American journal of lifestyle medicine · 2025
    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

12 authors.

Saadia QaziDivision of Aging Brigham and Women's Hospital and Harvard Medical School Boston MA USA.ORCID 0000-0002-5394-9530
Benjamin SeligmanGreater Los Angeles GRECC, VA Greater Los Angeles Health Care System Los Angeles CA USA.ORCID 0000-0002-8223-5924
Sarah R PreisMassachusetts Veterans Epidemiology Research and Information Center (MAVERIC) VA Boston Healthcare System Boston MA USA.ORCID 0000-0002-9360-4166
Manas RaneDivision of Aging Brigham and Women's Hospital and Harvard Medical School Boston MA USA.
Luc DjousseDivision of Aging Brigham and Women's Hospital and Harvard Medical School Boston MA USA.ORCID 0000-0002-9902-3047
David R GagnonMassachusetts Veterans Epidemiology Research and Information Center (MAVERIC) VA Boston Healthcare System Boston MA USA.ORCID 0000-0002-6367-3179
Peter W F WilsonVeterans Affairs Atlanta Healthcare System Decatur GA USA.ORCID 0000-0002-5653-7056
J Michael GazianoDivision of Aging Brigham and Women's Hospital and Harvard Medical School Boston MA USA.ORCID 0000-0002-5384-9767
Jane A DriverDivision of Aging Brigham and Women's Hospital and Harvard Medical School Boston MA USA.ORCID 0000-0001-9759-4607
Kelly ChoDivision of Aging Brigham and Women's Hospital and Harvard Medical School Boston MA USA.
Ariela R OrkabyDivision of Aging Brigham and Women's Hospital and Harvard Medical School Boston MA USA.ORCID 0000-0002-4297-6306
Million Veteran Program (MVP)

Funding

Statins for Primary Prevention of Cardiovascular Disease and FrailtyIK2CX001800 · VA · VA BOSTON HEALTH CARE SYSTEM · PI ORKABY, ARIELA R · 2019 to 2023
–
CSRD VA IK2 CX001800
6 · The paper itself

Abstract

backgroundFrailty, a syndrome of physiologic vulnerability, increases cardiovascular disease (CVD) risk. Whether in person or automated frailty tools are ideal for identifying CVD risk remains unclear. We calculated 3 distinct frailty scores and examined their associations with mortality and CVD events in the Million Veteran Program, a prospective cohort of nearly 1 million US veterans. METHODS AND

resultsVeterans aged ≥50 years and enrolled from 2011 to 2018 were included. Two frailty indices (FI) based on the deficit accumulation theory were calculated: the questionnaire-based 36-item Million Veteran Program-FI and 31-item Veterans Affairs-FI using claims data. We calculated Fried physical frailty using the self-reported, 3-item Study of Osteoporotic Fractures. Multivariable-adjusted Cox models examined the association of frailty by each score with primary (all-cause and CVD mortality) and secondary (myocardial infarction, stroke, and heart failure) outcomes. In 190 688 veterans (69±9 years, 94% male, 85% White), 33, 233 (17%) all-cause and 10 115 (5%) CVD deaths occurred. Using Million Veteran Program-FI, 29% were robust, 42% pre-frail, and 29% frail. Frailty prevalence increased by age group (27% in 50-59 to 42% in ≥90 years). Using the Million Veteran Program-FI, over 6±2 years, frail veterans had a higher hazard of all-cause (hazard ratio [HR], 3.05 [95% CI, 2.95-3.16]) and CVD mortality (HR, 3.65 [95% CI, 3.43-3.90]). Findings were concordant for the Veterans Affairs-FI and Study of Osteoporotic Fractures frailty definitions, and remained significant even among younger veterans aged 50-59 years.

conclusionsIrrespective of frailty measure, frailty is associated with a higher risk of all-cause mortality and adverse CVD events. Further study of frailty in veterans aged <60 years old is warranted.

Indexed as

Cardiovascular DiseasesFrailtySelf ReportAgedAged, 80 and overFemaleFrail ElderlyGeriatric AssessmentHumansMaleMiddle AgedProspective StudiesRisk AssessmentRisk FactorsUnited StatesVeteranscardiovascular diseasefrailtyrisk stratification

Identifiers

PMID39158558
PMCPMC11963909

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.