Evidence map›Paper›PMID 30256914›Full record

Observational studyThe journals of gerontology. Series A, Biological sciences and medical sciences2019

Evaluation of Frailty as an Unmeasured Confounder in Observational Studies of Antidiabetic Medications.

Caroline A Presley, Jonathan Chipman, Jea Young Min, Carlos G Grijalva, Robert A Greevy, Marie R Griffin, Christianne L Roumie

Open access · hybridAbstract readObservational Study
In one paragraph

Observational study in The journals of gerontology. Series A, Biological sciences and medical sciences, 2019. 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
0.3field-weighted citation impact, top 40% 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, 10 citations in OpenAlex.

  1. Pooled it
  2. Research with cancer registry data in radiation oncology-current possibilities and perspectives : A narrative review.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Impact of longitudinal data-completeness of electronic health record data on risk score misclassification.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  8. Article
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

7 authors at 3 institutions in 1 country.

Caroline A PresleyDepartment of Medicine, University of Alabama at Birmingham, Nashville, Tennessee.
Jonathan ChipmanDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee.
Jea Young MinVeterans Health Administration-Tennessee Valley Healthcare System, Geriatric Research Education and Clinical Center (GRECC), Nashville.
Carlos G GrijalvaVeterans Health Administration-Tennessee Valley Healthcare System, Geriatric Research Education and Clinical Center (GRECC), Nashville.
Robert A GreevyDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee.
Marie R GriffinVeterans Health Administration-Tennessee Valley Healthcare System, Geriatric Research Education and Clinical Center (GRECC), Nashville.
Christianne L RoumieVeterans Health Administration-Tennessee Valley Healthcare System, Geriatric Research Education and Clinical Center (GRECC), Nashville.
Vanderbilt University Medical Center · USVA Tennessee Valley Healthcare System · USUniversity of Alabama at Birmingham · US

Funding

Vanderbilt Center for Diabetes Translation ResearchP30DK092986 · NIDDK · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ELASY, TOM A · 2011 to 2020
$6.7M
Opioid selection and the risk of serious infections in older adultsR01AG043471 · NIA · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GRIJALVA, CARLOS G · 2013 to 2017
$2.3M
Optimal first line therapies for patients with Cardiovascular-Kidney-Metabolic (CKM) Syndrome.I01CX000570 · VA · VETERANS HEALTH ADMINISTRATION · PI ROUMIE, CHRISTIANNE L. · 2013 to 2025
–
CSRD VA I01 CX000570NIA NIH HHS R01 AG043471NIDDK NIH HHS P30 DK092986
6 · The paper itself

Abstract

backgroundIt is unknown whether observational studies evaluating the association between antidiabetic medications and mortality adequately account for frailty. Our objectives were to evaluate if frailty was a potential confounder in the relationship between antidiabetic medication regimen and mortality and how well administrative and clinical electronic health record (EHR) data account for frailty.

methodsWe conducted a retrospective cohort study in a single Veterans Health Administration (VHA) healthcare system of 500 hospitalizations-the majority due to heart failure-of Veterans who received regular VHA care and initiated type 2 diabetes treatment from 2001 to 2008. We measured frailty using a modified frailty index (FI, >0.21 frail). We obtained antidiabetic medication regimen and time-to-death from administrative sources. We compared FI among patients on different antidiabetic regimens. Stepwise Cox proportional hazards regression estimated time-to-death by demographic, administrative, clinical EHR, and FI data.

resultsMedian FI was 0.22 (interquartile range 0.18, 0.27). Frailty differed across antidiabetic regimens (p < .001). An FI increase of 0.05 was associated with an increased risk of death (hazard ratio 1.45, 95% confidence interval 1.32, 1.60). Cox proportional hazards model for time-to-death including demographic, administrative, and clinical EHR data had a c-statistic of 0.70; adding FI showed marginal improvement (c-statistic 0.72).

conclusionsFrailty was associated with antidiabetic regimen and death, and may confound that relationship. Demographic, administrative, and clinical EHR data, commonly used to balance differences among exposure groups, performed moderately well in assessing risk of death, with minimal gain from adding frailty. Study design and analytic techniques can help minimize potential confounding by frailty in observational studies.

Indexed as

Frail ElderlyAgedConfounding Factors, EpidemiologicDiabetes Mellitus, Type 2Electronic Health RecordsFemaleGeriatric AssessmentHeart FailureHospitalizationHumansHypoglycemic AgentsMaleMiddle AgedRetrospective StudiesRisk AssessmentVeteransHypoglycemic AgentsDiabetesDrug-relatedEpidemiologyFrailty

Identifiers

PMID30256914
PMCPMC6625595
OpenAlexW2894003250

What OpenQuestion holds

Textmetadata
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.