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Record W3010116895 · doi:10.3389/fnagi.2020.00055

Executive Function Is Related to the Urinary Urgency in Non-demented Patients With Parkinson’s Disease

2020· article· en· W3010116895 on OpenAlexaboutno aff
Zuzanna Tkaczynska, Sara Becker, Walter Maetzler, Maarten Timmers, Luc Van Nueten, Patricia Sulzer, Giacomo Salvadore, Eva Schäffer, Kathrin Brockmann, Johannes Streffer, Daniela Berg, Inga Liepelt‐Scarfone

Bibliographic record

VenueFrontiers in Aging Neuroscience · 2020
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersDeutsche Parkinson Vereinigung
KeywordsMontreal Cognitive AssessmentNocturiaExecutive dysfunctionMedicineParkinson's diseaseUrinary urgencyNeuropsychologyInternal medicineCognitionDiseaseQuality of life (healthcare)Urinary systemExecutive functionsBayesian multivariate linear regressionCohortPsychologyPsychiatryOveractive bladderCognitive impairmentLinear regressionPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Evidence suggests urinary urgency is associated with cognitive impairment in a subtype of Parkinson’s disease (PD) patients. This study investigates if cognitive impairment independently predicts the presence of urinary dysfunction. METHODS: We report data of 189 idiopathic PD patients, excluding those with concomitant diseases or medication interacting with bladder function. A standardized questionnaire was used to define presence of urinary urgency. All patients underwent a comprehensive motor, cognitive non-motor and health-related quality of life (HRQoL) assessment. Multivariable linear regression analysis was performed to identify independent variables characterizing urinary urgency in PD (PD-UU), which were assigned as discriminant features to estimate their individual contribution to the phenotype of PD-UU group. RESULTS: Of 189 PD patients, 115 (60.8%) reported PD-UU. The linear regression showed that among cognitive domains, executive function (EF) (p = .04) had a significant negative association with PD-UU. In a second model, scores of the Montreal Cognitive Assessment (MoCA) significantly differentiated between study groups (p = .007) and with non-motor symptom (NMS) burden (p < .001). The third model consisted of reports of HRQoL, of which stigma was the only subscale of the Parkinson’s Disease Questionnaire (PDQ-39) differentiating between patients with and without PD-UU (p = .02). Linear discriminant analysis provided evidence that the combination of EF, NMS impairment, nocturia and stigma discriminated between groups with 72.4% accuracy. CONCLUSION: In our large, non-demented PD cohort, urinary urgency was associated with executive dysfunction, supporting a possible causative link between both symptoms. A combination of neuropsychological and non-motor aspects identified patients with PD-UU with high discriminative accuracy.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.233
Teacher spread0.222 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2020
Admission routes1
Has abstractyes

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