Evidence map›Paper›PMID 28422270›Full record

ArticleJournal of the American Geriatrics Society2017

Characteristics and Incidence of Chronic Illness in Community-Dwelling Predominantly Male U.S. Veteran Centenarians.

Raya Elfadel Kheirbek, Ali Fokar, Nawar Shara, Leakie K Bell-Wilson, Hans J Moore, Edwin Olsen, Marc R Blackman, Maria D Llorente

Open access · greenAbstract read
In one paragraph

Article in Journal of the American Geriatrics Society, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
10.3field-weighted citation impact, top 2% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

  1. Pooled it
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  12. The Burden of Frailty Among U.S. Veterans and Its Association With Mortality, 2002-2012.The journals of gerontology. Series A, Biological sciences and medical sciences · 2019
    Article
  13. Article
  14. Neuropsychological Test Norms in Cognitively Intact Oldest-Old.Journal of the International Neuropsychological Society : JINS · 2019
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 5 institutions in 1 country.

Raya Elfadel KheirbekWashington DC Veterans Affairs Medical Center, Washington, District of Columbia.ORCID http://orcid.org/0000-0003-0755-1940
Ali FokarWashington DC Veterans Affairs Medical Center, Washington, District of Columbia.
Nawar SharaMedStar Health Research Institute, Hyattsville, Maryland.
Leakie K Bell-WilsonWashington DC Veterans Affairs Medical Center, Washington, District of Columbia.
Hans J MooreWashington DC Veterans Affairs Medical Center, Washington, District of Columbia.
Edwin OlsenMiller School of Medicine, University of Miami, Miami, Florida.
Marc R BlackmanWashington DC Veterans Affairs Medical Center, Washington, District of Columbia.
Maria D LlorenteWashington DC Veterans Affairs Medical Center, Washington, District of Columbia.
Georgetown University · USWashington DC VA Medical Center · USGeorgetown-Howard Universities Center for Clinical and Translational Science · USUniformed Services University of the Health Sciences · USUniversity of Miami · US

Funding

Maternal Morbidity and Mortality: Risk Factors, Early Detection and Personalized InterventionUL1TR001409 · NCATS · GEORGETOWN UNIVERSITY · PI GONDRE-LEWIS, MARJORIE C, MELLMAN, THOMAS A · 2015 to 2024
$37.8M
NCATS NIH HHS UL1 TR001409
6 · The paper itself

Abstract

objectivesTo assess the incidence of chronic illness and its effect on veteran centenarians.

designRetrospective longitudinal cohort study.

settingUnited States Veterans Affairs Corporate Data Warehouse (CDW).

participantsCommunity-dwelling veterans born between 1910 and 1915 who survived to at least age 80 (N = 86,892; 31,121 octogenarians, 52,420 nonagenarians, 3,351 centenarians). MEASUREMENTS: The Kaplan-Meier method was used to estimate cumulative incidence of chronic conditions according to age group. Incidence rates were compared using the log-rank test. Cox proportional hazards models were used to estimate unadjusted hazard ratios.

resultsNinety-seven percent of Centenarians were male, 88.0% were white, 31.8% were widowed, 87.5% served in World War II, and 63.9% did not have a service-related disability. The incidence rates of chronic illnesses were higher in octogenarians than centenarians (atrial fibrillation, 15.0% vs 0.6%, P < .001; heart failure, 19.3% vs 0.4%, P < .001; chronic obstructive pulmonary disease, 17.9% vs 0.6%, P < .001; hypertension, 29.6% vs 3.0%, P < .001; end-stage renal disease, 7.2% vs 0.1%, P < .001; malignancy, 14.1% vs 0.6%, P < .001; diabetes mellitus, 11.1% vs 0.4%, P < .001; stroke, 4.6% vs 0.4%, P < .001) and in nonagenarians than centenarians (atrial fibrillation, 13.2% vs 3.5%, P < .001; heart failure, 15.8% vs 3.3%, P < .001; chronic obstructive pulmonary disease, 11.8% vs 3.5%, P < .001; hypertension, 27.2% vs 12.8%, P < .001; end-stage renal disease, 11.9% vs 4.5%, P < .001; malignancy, 8.6% vs 2.3%, P < .001; diabetes mellitus, 7.5% vs 2.2%, P < .001; and stroke, 3.5% vs 1.3%, P < .001).

conclusionIn a large cohort of predominantly male community-dwelling elderly veterans, centenarians had a lower incidence of chronic illness than those in their 80s and 90s, demonstrating similar compression of morbidity and extension of health span observed in other studies.

Indexed as

Independent LivingAged, 80 and overAge FactorsChronic DiseaseDatabases, FactualFemaleHeart FailureHumansHypertensionIncidenceLongitudinal StudiesMaleMorbidityPulmonary Disease, Chronic ObstructiveRetrospective StudiesUnited Statescentenarianschronic illnessincidencenonagenariansoctogenariansveterans

Identifiers

PMID28422270
PMCPMC5724032
OpenAlexW2606449281

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.