Evidence map›Paper›PMID 26847674›Full record

ArticleNeurology and therapy2015

Concurrent Use of Benzodiazepines and Antidepressants and the Risk of Motor Vehicle Accident in Older Drivers: A Nested Case-Control Study.

Jean-Pascal Fournier, Machelle Wilchesky, Valérie Patenaude, Samy Suissa

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Article in Neurology and therapy, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

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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

9 citing papers in PubMed.

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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.

Jean-Pascal FournierCentre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, Canada.
Machelle WilcheskyCentre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, Canada.
Valérie PatenaudeCentre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, Canada.
Samy SuissaCentre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, Canada. samy.suissa@mcgill.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAging of the population results in an increase in senior drivers. Elderly are frequently treated with benzodiazepines and antidepressants. The objective of this study was to determine whether the concurrent use of benzodiazepines and antidepressants is associated with motor vehicle accidents (MVAs) in the elderly.

methodsThis was a nested case-control study within a cohort of drivers aged 67-84 years between 1990 and 2000, identified from the Société de l'Assurance Automobile du Québec and the Régie de l'Assurance Maladie du Québec databases. First cases of MVAs during follow-up were matched with up to ten controls from the cohort. Odds ratios (ORs) for the association between MVA and the use of benzodiazepines and antidepressants were estimated using conditional logistic regression.

resultsThe cohort included 373,818 drivers, with 74,503 MVA cases matched with 744,663 controls. The risk of MVA was higher in current users of long-acting benzodiazepines [OR 1.23; 95% confidence interval (CI) 1.16-1.29] than in current users of short-acting benzodiazepines (OR 1.05; 95% CI 1.02-1.08). The risk of MVA was increased in current users of selective serotonin reuptake inhibitors (SSRIs; OR 1.13; 95% CI 1.04-1.22), while it was not in current users of tricyclic antidepressants (TCAs; OR 1.04; 95% CI 0.96-1.14). The highest ORs of MVA were observed in long-acting benzodiazepines users concurrently using SSRIs (OR 1.37; 95% CI 1.07-1.77, P value for interaction = 0.964) or TCAs (OR 1.54; 95% CI 1.21-1.95, P value for interaction = 0.077).

conclusionUse of long-acting benzodiazepines is associated with an increased risk of MVA in the elderly, particularly in those concurrently using SSRIs or TCAs.

Indexed as

AgedAntidepressantsAutomobile drivingBenzodiazepinesDrug interactions

Identifiers

PMID26847674
PMCPMC4470976

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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.