Evidence map›Paper›PMID 32885396›Full record

ArticleDrugs & aging2020

Predictors of Mortality in the Older Population: The Role of Polypharmacy and Other Medication and Chronic Disease-Related Factors.

Nashwa Masnoon, Lisa Kalisch Ellett, Sepehr Shakib, Gillian E Caughey

Abstract read
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In one paragraph

Article in Drugs & aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 12% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Pooled it
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  6. Age and Breast Reconstruction.Aesthetic plastic surgery · 2023
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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 at 2 institutions in 1 country.

Nashwa MasnoonUniSA Clinical and Health Sciences, University of South Australia, Frome Road, Adelaide, SA, Australia. Nashwa.Masnoon@mymail.unisa.edu.au.ORCID 0000-0002-7123-9583
Lisa Kalisch EllettUniSA Clinical and Health Sciences, University of South Australia, Frome Road, Adelaide, SA, Australia.
Sepehr ShakibDiscipline of Pharmacology, Adelaide Medical School, University of Adelaide, North Terrace, Adelaide, SA, Australia.
Gillian E CaugheyUniSA Clinical and Health Sciences, University of South Australia, Frome Road, Adelaide, SA, Australia.
Royal Adelaide Hospital · AUUniversity of South Australia · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPolypharmacy has been associated with increased mortality but the contribution of different medication-related factors to this is unknown.

aimsThe aim of this study was to identify demographic and medication-related predictors of mortality in the older population. Given the intrinsic link between polypharmacy and multimorbidity, the secondary aim was to examine if the medicines or underlying diseases predicted mortality.

methodsPatients aged ≥ 65 years from an outpatient multimorbidity clinic were included. Medication-related factors included the medicines count, high-risk medicines, inappropriate medicines duplication, and potential drug-drug and drug-disease interactions. Logistic regression was used to identify mortality predictors within a year of clinic discharge from the outpatient clinic. Patients attend the clinic until medications and comorbidity management have been optimised, at which point they are discharged from the clinic, and their General Practitioner provides ongoing care.

resultsA total of 584 patients were included (median age 80.0 years) and 9.9% (n = 58) died within a year of discharge. Demographics, namely age (adjusted odds ratio [aOR] 1.05; 95% CI 1.01-1.09; p = 0.018) and being male (aOR 5.10; 95% CI 2.63-9.88; p < 0.001); chronic disease, namely heart failure (aOR 3.36; 95% CI 1.78-6.35; p < 0.001); and medication-related factors, namely the number of sedative and anticholinergic medicines (aOR 1.66; 95% CI 1.19-2.33; p = 0.003) predicted mortality in the study population.

conclusionWhilst polypharmacy has been defined using the number of medicines in the literature, a combination of demographics, chronic disease and medications predicted mortality in our study. This provides guidance for the development of future tools and guidelines regarding the inclusion of key factors for identifying high-risk patients at risk of adverse health outcomes such as mortality.

Indexed as

Medication Therapy ManagementPolypharmacyAgedAged, 80 and overAmbulatory CareCholinergic AntagonistsChronic DiseaseCohort StudiesComorbidityDrug InteractionsFemaleGeneral PractitionersHumansHypnotics and SedativesLogistic ModelsMaleCholinergic AntagonistsHypnotics and Sedatives

Identifiers

PMID32885396
OpenAlexW3083188000

What OpenQuestion holds

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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.