Evidence map›Paper›PMID 26955385›Full record

ArticleDementia and geriatric cognitive disorders extra

The Influence of Patient Characteristics on Anticholinergic Events in Older People.

Mohammed Saji Salahudeen, Prasad S Nishtala, Stephen B Duffull

Abstract read
In one paragraph

Article in Dementia and geriatric cognitive disorders extra. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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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, 2 syntheses or guidelines pooled it.

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  9. An overview of pharmacodynamic modelling, ligand-binding approach and its application in clinical practice.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2017
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Mohammed Saji SalahudeenSchool of Pharmacy, University of Otago, Dunedin, New Zealand.
Prasad S NishtalaSchool of Pharmacy, University of Otago, Dunedin, New Zealand.
Stephen B DuffullSchool of Pharmacy, University of Otago, Dunedin, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsTo examine patient characteristics that predict adverse anticholinergic-type events in older people.

methodsThis retrospective population-level study included 2,248 hospitalised patients. Individual data on medicines that are commonly associated with anticholinergic events (delirium, constipation and urinary retention) were identified. Patient characteristics examined were medicines with anticholinergic effects (ACh burden), age, sex, non-anticholinergic medicines (non-ACM), Charlson comorbidity index scores and ethnicity. The Akaike information criterion was used for model selection. The data were analysed using logistic regression models for anticholinergic events using the software NONMEM.

resultsACh burden was found to be a significant independent predictor for developing an anticholinergic event [adjusted odds ratio (aOR): 3.21, 95% CI: 1.23-5.81] for those taking an average of 5 anticholinergic medicines compared to those taking 1. Both non-ACM and age were also independent risk factors (aOR: 1.41, 95% CI: 1.31-1.51 and aOR: 1.08, 95% CI: 1.05-1.10, respectively).

conclusionTo our knowledge, this is the first study that has examined population-level data in a nonlinear model framework to predict anticholinergic-type adverse events. This study evaluated the relationship between important patient characteristics and the occurrence of anticholinergic-type events. These findings reinforce the clinical significance of reviewing anticholinergic medicines in older people.

Indexed as

Adverse eventsAnticholinergic burdenAnticholinergic eventsAntimuscarinic responseElderlyOlder peopleRisk factors

Identifiers

PMID26955385
PMCPMC4777954

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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.