Evidence map›Paper›PMID 32852787›Full record

ArticleJournal of the American Geriatrics Society2020

Hospitalization Risk Among Older Adults with Sensory Impairments: Development of a Prognostic Model.

William J Deardorff, Richard J Sloane, Juliessa M Pavon, Susan N Hastings, Heather E Whitson

Open access · greenAbstract read
In one paragraph

Article in Journal of the American Geriatrics Society, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
0.1field-weighted citation impact, top 57% 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
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

5 authors at 3 institutions in 1 country.

William J DeardorffDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina.
Richard J SloaneCenter for the Study of Aging and Human Development, Duke University Medical Center, Durham, North Carolina.
Juliessa M PavonDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina.
Susan N HastingsDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina.
Heather E WhitsonDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina.
Duke University · USDuke Medical Center · USDuke University Hospital · US

Funding

Support for QA/QC for Prior Approval ProcessUL1TR002553 · NCATS · DUKE UNIVERSITY · PI LI, JENNIFER S, MCNAMARA, JAMES O. · 2018 to 2023
$58.5M
Resource Core 3 - Metabolomics CoreP30AG028716 · NIA · DUKE UNIVERSITY · PI Virginia B Kraus · 2006 to 2026
$24.6M
Physical Resiliencies: Indicators and Mechanisms in the Elderly CollaborativeUH2AG056925 · NIA · DUKE UNIVERSITY · PI COLON-EMERIC, CATHLEEN S, WHITSON, HEATHER E. · 2017 to 2018
$2.0M
Geriatrics Research: From Bench to BedsideU13AG054139 · NIA · AMERICAN GERIATRICS SOCIETY · PI WHITSON, HEATHER E. · 2016 to 2020
$201k
NCATS NIH HHS UL1 TR002553NCATS NIH HHS UL1TR002553NIA NIH HHS P30 AG028716NIA NIH HHS U13 AG054139NIA NIH HHS UH2 AG056925NIH HHS P30AG028716NIH HHS UH2AG056925VA CIN 13-410
6 · The paper itself

Abstract

objectivesTo develop a prognostic model for hospital admissions over a 1-year period among community-dwelling older adults with self-reported hearing and/or vision impairments based on readily obtainable clinical predictors.

designRetrospective cohort study.

settingMedicare Current Beneficiary Survey from 1999 to 2006.

participantsCommunity-dwelling Medicare beneficiaries, aged 65 years and older, with self-reported hearing and/or vision impairment (N = 15,999). MEASUREMENTS: The primary outcome was any hospital admission over a predefined 1-year study period. Candidate predictors included demographic factors, prior healthcare utilization, comorbidities, functional impairment, and patient-level factors. We analyzed the association of all candidate predictors with any hospital admission over the 1-year study period using multivariable logistic regression. The final model was created using a penalized regression method known as the least absolute shrinkage and selection operator. Model performance was assessed by discrimination (concordance statistic (c-statistic)) and calibration (evaluated graphically). Internal validation was performed via bootstrapping, and results were adjusted for overoptimism.

resultsOf the 15,999 participants, the mean age was 78 years and 55% were female. A total of 2,567 participants (16.0%) had at least one hospital admission in the 1-year study period. The final model included seven variables independently associated with hospitalization: number of inpatient admissions in the previous year, number of emergency department visits in the previous year, activities of daily living difficulty score, poor self-rated health, and self-reported history of myocardial infarction, stroke, and nonskin cancer. The c-statistic of the final model was 0.717. The optimism-corrected c-statistic after bootstrap internal validation was 0.716. A calibration plot suggested that the model tended to overestimate risk among patients at the highest risk for hospitalization.

conclusionThis prognostic model can help identify which community-dwelling older adults with sensory impairments are at highest risk for hospitalization and may inform allocation of healthcare resources.

Indexed as

AgedAged, 80 and overComorbidityEmergency Service, HospitalFemaleHearing LossHospitalizationHumansIndependent LivingLogistic ModelsMaleMedicareRisk FactorsSelf ReportUnited StatesVision Disordershearing impairmenthospitalizationprediction modelsensory impairmentvision impairment

Identifiers

PMID32852787
PMCPMC7988218
OpenAlexW3080432195

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.