Evidence map›Paper›PMID 35331147›Full record

ArticleBMC geriatrics2022

Strong evidence for age as the single most dominant predictor of medically supervised driving test-mini mental status test outcomes provide only weak but significant moderate additional predictive value.

Yannik Isler, Simon Schwab, Regula Wick, Stefan Lakämper

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Article in BMC geriatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yannik IslerInstitute for Forensic Medicine, Traffic Medicine, University of Zürich, Andreasstrasse 15, 8050, Zürich, Switzerland.
Simon SchwabCenter for Reproducible Science, University of Zürich, Hirschengraben 84, 8001, Zürich, Switzerland.
Regula WickInstitute for Forensic Medicine, Traffic Medicine, University of Zürich, Andreasstrasse 15, 8050, Zürich, Switzerland.
Stefan LakämperInstitute for Forensic Medicine, Traffic Medicine, University of Zürich, Andreasstrasse 15, 8050, Zürich, Switzerland. stefan.lakaemper@irm.uzh.ch.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith age, medical conditions impairing safe driving accumulate. Consequently, the risk of accidents increases. To mitigate this risk, Swiss law requires biannual assessments of the fitness to drive of elderly drivers. Drivers may prove their cognitive and physical capacity for safe driving in a medically supervised driving test (MSDT) when borderline cases, as indicated by low performance in a set of four cognitive tests, including e.g. the mini mental status test (MMST). Any prognostic, rather than indicative, relations for MSDT outcomes have neither been confirmed nor falsified so far. In order to avoid use of unsubstantiated rules of thumb, we here evaluate the predictive value for MSDT outcomes of the outcomes of the standard set of four cognitive tests, used in Swiss traffic medicine examinations.

methodsWe present descriptive information on age, gender and cognitive pretesting results of all MSDTs recorded in our case database from 2017 to 2019. Based on these retrospective cohort data, we used logistic regression to predict the binary outcome MSDT. An exploratory analysis used all available data (model 1). Based on the Akaike Information Criterion (AIC), we then established a model including variables age and MMST (model 2). To evaluate the predictive value of the four cognitive assessments, model 3 included cognitive test outcomes only. Receiver operating characteristics (ROC) and area under the curve (AUC) allowed evaluating discriminative performance of the three different models using independent validation data.

resultsUsing N = 188 complete data sets of a total of 225 included cases, AIC identified age (p < 0.0008) and MMST (p = 0.024) as dominating predictors for MSDT outcomes with a median AUC of 0.71 (95%-CI 0.57-0.85) across different training and validation splits, while using the four cognitive test results exclusively yielded a median AUC of 0.55 (95%-CI 0.40-0.71).

conclusionsOur analysis provided strong evidence for age as the single most dominant predictor of MSDT outcomes. Adding MMST provides only weak additional predictive value for MSDT outcomes. Combining the results of four cognitive test used as standard screen in Swiss traffic medicine alone, proved to be of poor predictive value. This highlights the importance of MSDTs for balancing between the mitigation of risks by and the right to drive for the elderly.

Indexed as

Accidents, TrafficAutomobile DrivingAgedHumansMental Status and Dementia TestsNeuropsychological TestsRetrospective StudiesClock testCognitive testingElderly driversFitness to driveMedically supervised driving testMini mental status testReceiver operating characteristicsTraffic medicineTrail making test

Identifiers

PMID35331147
PMCPMC8951702

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LicenceCC BY
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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.