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Record W2340227446 · doi:10.1017/s0317167100052598

Gait Analysis in Advanced Parkinson's Disease – Effect of Levodopa and Tolcapone

2001· article· en· W2340227446 on OpenAlexvenueno aff
Din‐E Shan, Shwn-Jen Lee, Ling-Yi Chao, Shyh-Ing Yeh

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2001
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
FundersTaipei Veterans General HospitalNational Science Council
KeywordsBenserazideLevodopaGaitPhysical medicine and rehabilitationPlaceboMedicineAnkleParkinson's diseasePsychologyPhysical therapyInternal medicineSurgeryDisease

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the therapeutic effect of levodopa/benserazide and tolcapone on gait in patients with advanced Parkinson's disease. METHODS: Instrumental gait analysis was performed in 38 out of 40 patients with wearing-off phenomenon during a randomized, double-blind, placebo-controlled trial of tolcapone. RESULTS: Gait analysis disclosed a significant improvement by levodopa/benserazide in walking speed, stride length and the range of motion of hip, knee and ankle joints. At the end of the study, both the UPDRS motor scores during off-period and the percentage of off time improved significantly using tolcapone. However, gait analysis could not confirm this improvement. With respect to levodopa/benserazide effect, the reduction in rigidity correlated with improved angular excursion of the ankle, whereas the decreased bradykinesia correlated with improved stride length and angular excursion of the hip and knee joints. CONCLUSION: The results of our gait analysis confirmed that in parkinsonian patients with fluctuating motor symptoms levodopa/benserazide, but not tolcapone, produced a substantial improvement.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.026
GPT teacher head0.328
Teacher spread0.302 · 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 designNon-randomized trial
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

Citations45
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicBalance, Gait, and Falls PreventionFrench-language works237,207