Evidence map›Paper›PMID 19929031›Full record

ArticleDrugs & aging2009

Polypharmacy status as an indicator of mortality in an elderly population.

Johanna Jyrkkä, Hannes Enlund, Maarit J Korhonen, Raimo Sulkava, Sirpa Hartikainen

Registry-linked trialAbstract readComparative Study
PubMed Publisher
In one paragraph

Article in Drugs & aging, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03501108 (Medication Rationalization for Older People Awaiting Long-term Nursing Home Care), which is not on this map. Cited by 140 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
140citing papers in PubMed, 9 pooled it
5.3field-weighted citation impact, top 5% 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.

NCT03501108 naunknown statusnot on this mapstarted 2018, after this paper: background citation

Medication Rationalization for Older People Awaiting Long-term Nursing Home Care: a Randomized Controlled Trial Using the STOPPfrail Criteria

TypeinterventionalSponsorUniversity College CorkRan2018 to 2019Enrolled160ConditionsPolypharmacy, Frail Elderly Syndrome, Inappropriate Prescribing, Drug-Related Side Effects and Adverse ReactionsArmsSTOPPFrail deprescribing criteria
3 · Its place in the literature

Who cites it

140 citing papers in PubMed, 9 syntheses or guidelines pooled it, 354 citations in OpenAlex.

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  13. Polypharmacy and major adverse events in atrial fibrillation: observations from the AFFIRM trial.Clinical research in cardiology : official journal of the German Cardiac Society · 2016
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80 more citing papers are in PubMed but not listed here.

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 2 countries.

Johanna JyrkkäSchool of Public Health and Clinical Nutrition, University of Kuopio, Kuopio, Finland. johanna.jyrkka@uef.fi
Hannes Enlund
Maarit J Korhonen
Raimo Sulkava
Sirpa Hartikainen
University of Eastern Finland · FIKuopio University Hospital · FIKuwait University · KW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIncreased use of drugs has raised concern about the risks of polypharmacy in elderly populations. Adverse outcomes, such as hospitalizations and falls, have been shown to be associated with polypharmacy. So far, little information is available on the association between polypharmacy status and mortality.

objectiveTo assess whether polypharmacy (six to nine drugs) or excessive polypharmacy (ten or more drugs) could be indicators of mortality in elderly persons.

methodsThis was a population-based cohort study conducted between 1998 and 2003 with mortality follow-up through to 2007. The data in this study were derived from the population-based Kuopio 75+ Study, which involved elderly persons aged>or=75 years living in the city of Kuopio, Finland. The initial sample (sample frame n=4518, random sample n=700) was drawn from the population register. For the purpose of this study, two separate analyses were carried out. In the first phase, participants (aged>or=75 years, n=601) were followed from 1998 (baseline) to 2002. In the second phase, survivors (aged>or=80 years, n=339) were followed from 2003 to 2007. Current medications were determined from drug containers and prescriptions during interviews conducted by a trained nurse. The Kaplan-Meier method and Cox proportional hazards regression were used to examine the association between polypharmacy status and mortality.

resultsIn the first phase, 28% (n=167) belonged to the excessive polypharmacy group, 33% (n=200) to the polypharmacy group, and the remaining 39% (n=234) to the non-polypharmacy (0-5 drugs) group. The corresponding figures in the second phase were 28% (n=95), 39% (n=132) and 33% (n=112), respectively. The mortality rate was 37% in the first phase and 40% in the second phase. In both phases, the survival curves showed a significant difference in all-cause mortality between the three polypharmacy groups. In the first phase, the univariate model showed an association between excessive polypharmacy and mortality (hazard ratio [HR] 2.53, 95% CI 1.83, 3.48); however, after adjustment for demographics and other variables measuring functional and cognitive status, this association did not remain statistically significant (HR 1.28, 95% CI 0.86, 1.91). In the second phase, the association between excessive polypharmacy and mortality (HR 2.23, 95% CI 1.21, 4.12) remained significant after adjustments. Age, male sex and dependency according to the Instrumental Activities of Daily Living screening instrument were associated with mortality in both phases.

conclusionThis study points to the importance of excessive polypharmacy as an indicator for mortality in elderly persons. This association needs to be confirmed following adjustment for co-morbidities.

Indexed as

PolypharmacyAgedAged, 80 and overCohort StudiesFemaleFollow-Up StudiesHumansMaleMortalityProspective StudiesSurvival Rate

Identifiers

PMID19929031
OpenAlexW2169875489

What OpenQuestion holds

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Registered trials

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.