Evidence map›Paper›PMID 18780128›Full record

ArticleJournal of general internal medicine2008

Risks and advantages of detecting individuals unfit to drive: a Markov decision analysis.

Sandy Leproust, Emmanuel Lagarde, Louis-Rachid Salmi

Abstract read
In one paragraph

Article in Journal of general internal medicine, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
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

3 authors.

Sandy LeproustINSERM, U897, Equipe Avenir Prévention et prise en charge des traumatismes, Bordeaux, France.
Emmanuel Lagarde
Louis-Rachid Salmi

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany countries have initiated legislation to detect individuals who are unfit to drive, without any evidence that positive effects of these screening procedures outweigh negative effects.

objectiveTo measure the potential effectiveness of a screening program to detect individuals unfit to drive.

designMarkov decision analysis was used to compare no screening to two potential screening strategies.

participantsHypothetical cohorts of 10,000 45-year-old, 65-year-old, 75-year-old and 85-year-old individuals seen in primary care practices.

interventionsWithin the screening strategies: a clinical test without on-road confirmatory testing; a clinical test with on-road confirmatory testing, and an imposed driving cessation for patients with a positive test. MEASUREMENTS: For each strategy, we compared for two conditions (sleep disorders and dementia) the numbers of crash-related consequences prevented and of adverse events induced (primary objective) and measured the gain in quality-adjusted life years (secondary objective).

resultsFor sleep disorders, on-road confirmatory annual testing was the preferred strategy. Whatever the medical condition and age when screening starts, no screening was always better than single-test screening without an on-road confirmatory testing. In sensitivity analyses, these baseline conclusions were only affected by extreme values of test specificity.

conclusionBecause of the expected difficult application and cost of road tests and annual screening by clinicians, the most acceptable strategy from public health, clinical, and individual points of view is likely to be no screening.

Indexed as

Automobile Driver ExaminationMarkov ChainsAccidents, TrafficAdultAgedAged, 80 and overDecision Support TechniquesDementiaHumansMass ScreeningMiddle AgedSleep Wake Disorders

Identifiers

PMID18780128
PMCPMC2585670

What OpenQuestion holds

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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.