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Record W4220941752 · doi:10.1155/2022/4047710

Clinical Factors Predicting Voluntary Driving Cessation among Patients with Parkinson’s Disease

2022· article· en· W4220941752 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBehavioural Neurology · 2022
Typearticle
Languageen
FieldHealth Professions
TopicOlder Adults Driving Studies
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsOdds ratioMedicineMontreal Cognitive AssessmentLogistic regressionDementiaConfidence intervalInternal medicineDiseaseMultivariate analysisParkinson's diseaseCognitionGaitTurnoverPhysical therapyPhysical medicine and rehabilitationPsychiatry

Abstract

fetched live from OpenAlex

Factors that influence the decision of voluntary driving cessation in patients living with Parkinson’s disease (PD) are still unclear. We aimed to reveal the factors affecting the decision of voluntary driving cessation in patients with PD. This hospital-based cross-sectional study recruited consecutive outpatients with PD. Data on sociodemographic and clinical characteristics and medication use were collected from the patients using semistructured interviews. Cognitive function was evaluated using the Japanese version of the Montreal Cognitive Assessment (MoCA-J). We excluded patients with dementia or motor impairment ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mtext>Hoehn</a:mtext> <a:mo>−</a:mo> <a:mtext>Yahr</a:mtext> <a:mtext> </a:mtext> <a:mtext>stage</a:mtext> <a:mo>&gt;</a:mo> <a:mn>3</a:mn> </a:math> ). We divided the patients into two groups, with and without voluntary driving cessation (D: driver; RD: retired driver), and conducted investigations using multivariate logistic regression analyses. Of the 40 patients, 8 (20.0%) voluntarily retired from driving. Patients who decided on driving cessation had a higher prevalence of freezing of gait (FOG) (D vs. RD, 25.0% vs. 87.5%; <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" id="M2"> <c:mi>P</c:mi> <c:mo>=</c:mo> <c:mn>0.001</c:mn> </c:math> ) and tended to have lower scores for attention in the MoCA-J (D vs. RD, <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" id="M3"> <e:mn>5.0</e:mn> <e:mo>±</e:mo> <e:mn>1.2</e:mn> </e:math> vs. <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" id="M4"> <g:mn>4.1</g:mn> <g:mo>±</g:mo> <g:mn>1.4</g:mn> </g:math> ; <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" id="M5"> <i:mi>P</i:mi> <i:mo>=</i:mo> <i:mn>0.086</i:mn> </i:math> ). Multivariable analysis showed that FOG was independently associated with driving cessation (odds ratio: 14.46, 95% confidence interval: 1.91–303.74). FOG was associated with voluntary driving cessation in patients with PD without dementia or severe motor impairment. Physicians should consider providing extensive social support to maintain patients’ mobility and independence, especially if the patients have these clinical factors.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.354
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it