Evidence map›Paper›PMID 28456694›Full record

ArticlePM & R : the journal of injury, function, and rehabilitation2017

Predictive Indices for Functional Improvement and Deterioration, Institutionalization, and Death Among Elderly Medicare Beneficiaries.

Jibby E Kurichi, Pui L Kwong, Dawei Xie, Hillary R Bogner

Abstract read
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In one paragraph

Article in PM & R : the journal of injury, function, and rehabilitation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Trial
  2. Article
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  4. Article
  5. Stroke to Dementia Associated with Environmental Risks-A Semi-Markov Model.International journal of environmental research and public health · 2020
    Article
  6. Article
  7. Article
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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

4 authors.

Jibby E KurichiCenter for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Perelman School of Medicine, 423 Guardian Dr, 907 Blockley Hall, Philadelphia, PA 19104-6021(∗). Electronic address: jkurichi@mail.med.upenn.edu.
Pui L KwongCenter for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA(†).
Dawei XieCenter for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA(‡).
Hillary R BognerCenter for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA(§).

Funding

Course and risk factors for depression in late lifeR01MH082799 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI BOGNER, HILLARY R · 2009 to 2010
$798k
NIMH NIH HHS R01 MH082799
6 · The paper itself

Abstract

backgroundPrediction models can help clinicians provide the best and most appropriate care to their patients and can help policy makers design services for groups at highest risk for poor outcomes.

objectiveTo develop prediction models identifying both risk factors and protective factors for functional deterioration, institutionalization, and death.

designCohort study using data from the Medicare Current Beneficiary Survey (MCBS).

settingCommunity survey.

participantsThis study included 21,264 Medicare beneficiaries 65 years of age and older who participated in the MCBS from the 2001-2008 entry panels and were followed up for 2 years.

methodsThe index was derived in 60% and validated in the remaining 40%. β Coefficients from a multinomial logistic regression model were used to derive points, which were added together to create scores associated with the outcome.

main outcome measureThe outcome was activity of daily living (ADL) stage transitions over 2 years following entry into the MCBS. Beneficiaries were categorized into 1 of 4 outcome categories: stable or improved function, functional deterioration, institutionalization, or death.

resultsOur model identified 16 factors for functional deterioration (age, gender, education, living arrangement, dual eligibility, proxy use, Alzheimer disease/dementia, angina pectoris/coronary heart disease, diabetes, emphysema/asthma/chronic obstructive pulmonary disease, mental/psychiatric disorder, Parkinson disease, stroke/brain hemorrhage, hearing impairment, vision impairment, and baseline ADL stage) after backward selection (P < .05). Compared to stable or improved function, the risk of functional deterioration ranged from ≤1 to ≥6, ≤4 to ≥22 for the risk of institutionalization, and ≤3 to ≥16 for the risk of death.

conclusionPredictive indices, or point and scoring systems used to predict outcomes, can identify elderly Medicare beneficiaries at risk for functional deterioration, institutionalization, and death and can aid policy makers, clinicians, and family members in improving care for older adults and supporting successful aging in the community. LEVEL OF EVIDENCE: III.

Indexed as

Activities of Daily LivingChronic DiseaseInstitutionalizationInsurance BenefitsMedicareRecovery of FunctionAgedAged, 80 and overCohort StudiesFemaleHealth StatusHumansMaleOutcome Assessment, Health CarePredictive Value of TestsSurveys and Questionnaires

Identifiers

PMID28456694
PMCPMC5658275

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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.