Evidence map›Paper›PMID 26316650›Full record

Observational studyBMJ open2015

Development of a multivariable model to predict vulnerability in older American patients hospitalised with cardiovascular disease.

Susan P Bell, John Schnelle, Samuel K Nwosu, Jonathan Schildcrout, Kathryn Goggins, Courtney Cawthon, Amanda S Mixon, Eduard E Vasilevskis, Sunil Kripalani, Vanderbilt Inpatient Cohort Study

Abstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in BMJ open, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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  5. Article
  6. Mortality Predictive Value of the CJournal of clinical medicine · 2022
    Article
  7. Article
  8. Article
  9. 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

10 authors.

Susan P BellDivision of Cardiovascular Medicine, Department of Medicine, Vanderbilt University, Nashville, Tennessee, USA Division of General Internal Medicine and Public Health, Department of Medicine, Center for Quality Aging, Vanderbilt University, Nashville, Tennessee, USA.
John SchnelleDivision of General Internal Medicine and Public Health, Department of Medicine, Center for Quality Aging, Vanderbilt University, Nashville, Tennessee, USA.
Samuel K NwosuDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Jonathan SchildcroutDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Kathryn GogginsCenter for Clinical Quality and Implementation Research, Nashville, Tennessee, USA.
Courtney CawthonCenter for Health Services Research, Vanderbilt University, Nashville, Tennessee, USA.
Amanda S MixonCenter for Clinical Quality and Implementation Research, Nashville, Tennessee, USA Department of Veterans Affairs, Tennessee Valley Healthcare System-Geriatric Research Education and Clinical Center (GRECC), Nashville, Tennessee, USA Division of General Internal Medicine and Public Health, Department of Medicine, Section of Hospital Medicine, Vanderbilt University, Nashville, Tennessee, USA.
Eduard E VasilevskisCenter for Clinical Quality and Implementation Research, Nashville, Tennessee, USA Department of Veterans Affairs, Tennessee Valley Healthcare System-Geriatric Research Education and Clinical Center (GRECC), Nashville, Tennessee, USA Division of General Internal Medicine and Public Health, Department of Medicine, Section of Hospital Medicine, Vanderbilt University, Nashville, Tennessee, USA.
Sunil KripalaniCenter for Clinical Quality and Implementation Research, Nashville, Tennessee, USA Center for Health Services Research, Vanderbilt University, Nashville, Tennessee, USA Division of General Internal Medicine and Public Health, Department of Medicine, Section of Hospital Medicine, Vanderbilt University, Nashville, Tennessee, USA.
Vanderbilt Inpatient Cohort Study

Funding

The Vanderbilt Institute for Clinical and Translational Research (VICTR)UL1TR000445 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BERNARD, GORDON RAPHAEL · 2012 to 2016
$41.4M
Building Interdisciplinary Research Careers in Women's HealthK12HD043483 · NICHD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI HARTMANN, KATHERINE E, MAJOR, AMY S · 2002 to 2023
$10.3M
Health Literacy, Hospital Discharge, and Cardiovascular OutcomesR01HL109388 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI KRIPALANI, SUNIL · 2011 to 2015
$3.3M
Predicting Acute Brain Dysfunction in Older Patients: A Quality Improvement ToolK23AG040157 · NIA · VANDERBILT UNIVERSITY MEDICAL CENTER · PI VASILEVSKIS, EDUARD E · 2011 to 2015
$609k
Longitudinal Hemodynamic and Vascular Changes associated with FrailtyK23AG048347 · NIA · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BELL, SUSAN POTTER · 2015 to 2016
$345k
NCATS NIH HHS 2 UL1 TR000445-06NCATS NIH HHS UL1 TR000445NHLBI NIH HHS R01 HL109388NIA NIH HHS K23 AG040157NIA NIH HHS K23AG040157NIA NIH HHS K23 AG048347NICHD NIH HHS K12 HD043483NICHD NIH HHS K12HD043483-11
6 · The paper itself

Abstract

objectivesTo identify vulnerable cardiovascular patients in the hospital using a self-reported function-based screening tool.

participantsProspective observational cohort study of 445 individuals aged ≥ 65 years admitted to a university medical centre hospital within the USA with acute coronary syndrome and/or decompensated heart failure.

methodsParticipants completed an inperson interview during hospitalisation, which included vulnerable functional status using the Vulnerable Elders Survey (VES-13), sociodemographic, healthcare utilisation practices and clinical patient-specific measures. A multivariable proportional odds logistic regression model examined associations between VES-13 and prior healthcare utilisation, as well as other coincident medical and psychosocial risk factors for poor outcomes in cardiovascular disease.

resultsVulnerability was highly prevalent (54%) and associated with a higher number of clinic visits, emergency room visits and hospitalisations (all p<0.001). A multivariable analysis demonstrating a 1-point increase in VES-13 (vulnerability) was independently associated with being female (OR 1.55, p=0.030), diagnosis of heart failure (OR 3.11, p<0.001), prior hospitalisations (OR 1.30, p<0.001), low social support (OR 1.42, p=0.007) and depression (p<0.001). A lower VES-13 score (lower vulnerability) was associated with increased health literacy (OR 0.70, p=0.002).

conclusionsVulnerability to functional decline is highly prevalent in hospitalised older cardiovascular patients and was associated with patient risk factors for adverse outcomes and an increased use of healthcare services.

Indexed as

Frail ElderlyVulnerable PopulationsActivities of Daily LivingAcute Coronary SyndromeAgedAged, 80 and overDepressionFemaleGeriatric AssessmentHeart FailureHospitalizationHumansLogistic ModelsLongitudinal StudiesMaleMultivariate AnalysisGERIATRIC MEDICINE

Identifiers

PMID26316650
PMCPMC4554894

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Registered trials

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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.