Evidence map›Paper›PMID 28535297›Full record

ArticleAmerican journal of hypertension2017

Antihypertensive Adherence Trajectories Among Older Adults in the First Year After Initiation of Therapy.

Jennifer L Hargrove, Virginia Pate, Carri H Casteel, Yvonne M Golightly, Laura R Loehr, Stephen W Marshall, Til Stürmer

Abstract read
In one paragraph

Article in American journal of hypertension, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
–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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Medication Adherence Trajectories: A Systematic Literature Review.Journal of managed care & specialty pharmacy · 2020
    Pooled it
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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

7 authors.

Jennifer L HargroveGillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Virginia PateGillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Carri H CasteelCollege of Public Health, The University of Iowa, Iowa City, Iowa, USA.
Yvonne M GolightlyGillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Laura R LoehrGillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Stephen W MarshallGillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Til StürmerGillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

Funding

North Carolina Translational & Clinical Sciences Institute (NC TraCS)UL1TR001111 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, CAREY, TIMOTHY S · 2013 to 2017
$43.9M
Propensity Scores and Preventive Drug Use in the ElderlyR01AG023178 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI STURMER, TIL · 2005 to 2014
$2.7M
Propensity scores and preventive drug use in the elderlyR56AG023178 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI STURMER, TIL · 2015 to 2015
$412k
NCATS NIH HHS UL1 TR001111NIA NIH HHS R01 AG023178NIA NIH HHS R56 AG023178
6 · The paper itself

Abstract

backgroundAdherence to antihypertensives is suboptimal, but previous methods of quantifying adherence fail to account for varying patterns of use over time. We sought to improve classification of antihypertensive adherence using group-based trajectory models, and to determine whether individual factors predict adherence trajectories.

methodsWe identified older adults initiating antihypertensive therapy during 2008-2011 using a 20% sample of Medicare (federal health insurance available to US residents over the age of 65) beneficiaries enrolled in parts A (inpatient services), B (outpatient services), and D (prescription medication). We developed monthly adherence indicators using prescription fill dates and days supply data in the 12 months following initiation. Adherence was defined as having at least 80% of days covered. Logistic models were used to identify trajectory groups. Bayesian information criterion and trajectory group size were used to select the optimal trajectory model. We compared the distribution of covariates across trajectory groups using multivariable logistic regression.

resultsDuring 2008-2011, 282,520 Medicare beneficiaries initiated antihypertensive therapy (mean age 75 years, 60% women, 84% White). Six trajectories were identified ranging from perfect adherence (12-month adherence of 0.97, 40% of beneficiaries) to immediate stopping (12-month adherence of 0.10, 18% of beneficiaries). The strongest predictors of nonadherence were initiation with a single antihypertensive class (adjusted odds ratio = 2.08 (95% confidence interval: 2.00-2.13)), Hispanic (2.93 (2.75-3.11)) or Black race/ethnicity (2.04 (1.95-2.13)), and no prior history of hypertension (2.04 (2.00-2.08)) (Area under the receiving operating characteristic curve: 0.53).

conclusionsThere is substantial variation in antihypertensive adherence among older adults. Certain patient characteristics are likely determinants of antihypertensive adherence trajectories.

Indexed as

AgingMedication AdherenceAgedAged, 80 and overAge FactorsAntihypertensive AgentsArea Under CurveBayes TheoremBlood PressureDrug Therapy, CombinationFemaleHumansHypertensionLogistic ModelsMaleMultivariate AnalysisAntihypertensive Agentsantihypertensive adherenceblood pressureepidemiologyhypertensionolder adults

Identifiers

PMID28535297
PMCPMC7190965

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.