Evidence map›Paper›PMID 24353407›Full record

ArticlePatient preference and adherence2013

Electronically monitored medication adherence predicts hospitalization in heart failure patients.

Barbara Riegel, George J Knafl

Open access · goldAbstract read
In one paragraph

Article in Patient preference and adherence, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
5.6field-weighted citation impact, top 4% 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

26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 61 citations in OpenAlex.

  1. Pooled it
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  14. Incorporating nonlinearity into mediation analyses.BMC medical research methodology · 2017
    Article
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  17. Article
  18. Determinants of Behavioral Alertness in Adults with Heart Failure.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2016
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  20. Review
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

2 authors at 2 institutions in 1 country.

Barbara RiegelUniversity of Pennsylvania School of Nursing, Philadelphia, PA, USA ; University of Pennsylvania Leonard Davis Institute, Philadelphia, PA, USA.
George J KnaflUniversity of North Carolina School of Nursing, Chapel Hill, NC, USA.
University of North Carolina at Chapel Hill · USUniversity of Pennsylvania · US

Funding

Impact of sleepiness on heart failure self-careR01HL084394 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI RIEGEL, BARBARA J · 2007 to 2009
$2.1M
NHLBI NIH HHS R01 HL084394
6 · The paper itself

Abstract

backgroundHospitalization contributes enormously to health care costs associated with heart failure. Many investigators have attempted to predict hospitalization in these patients. None of these models has been highly effective in prediction, suggesting that important risk factors remain unidentified. PURPOSE: To assess prospectively collected medication adherence, objectively measured by the Medication Event Monitoring System, as a predictor of hospitalization in heart failure patients. MATERIALS AND

methodsWe used recently developed adaptive modeling methods to describe patterns of medication adherence in a sample of heart failure patients, and tested the hypothesis that poor medication adherence as determined by adaptive methods was a significant predictor of hospitalization within 6 months.

resultsMedication adherence was the best predictor of hospitalization. Besides two dimensions of poor adherence (adherence pattern type and low percentage of prescribed doses taken), four other single factors predicted hospitalization: low hemoglobin, depressed ejection fraction, New York Heart Association class IV, and 12 or more medications taken daily. Seven interactions increased the predictive capability of the model: 1) pattern of poor adherence type and lower score on the Letter-Number Sequencing test, a measure of short-term memory; 2) higher number of comorbid conditions and higher number of daily medications; 3) higher blood urea nitrogen and lower percentage of prescribed doses taken; 4) lower hemoglobin and much worse perceived health compared to last year; 5) older age and lower score on the Telephone Interview of Cognitive Status; 6) higher body mass index and lower hemoglobin; and 7) lower ejection fraction and higher fatigue. Patients with none of these seven interactions had a hospitalization rate of 9.7%. For those with five of these interaction risk factors, 100% were hospitalized. The C-index (the area under the receiver-operating characteristics [ROC] curve) for the model based on the seven interactions was 0.83, indicating excellent discrimination.

conclusionMedication adherence adds important new information to the list of variables previously shown to predict hospitalization in adults with heart failure.

Indexed as

heart failurehospitalizationmedication adherenceoutcomespatient complianceself-care

Identifiers

PMID24353407
PMCPMC3862652
OpenAlexW2076950088

What OpenQuestion holds

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LicenceCC BY-NC
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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.