Gait Differences between Initial Symptom Onset of Tremor-Dominant and Non-Tremor Dominant Sub-Types in Parkinson’s Disease (P1.051)
Bibliographic record
Abstract
Objective: Based on gait abnormality, the goal of the current study was to establish an objective criterion to aid clinical diagnosis of tremor dominant (TD) vs. non-tremor dominant (NTD) Parkinson's disease (PD). Background: Clinical separation into TD and NTD sub-types is associated with disease prognosis. While it is expected that NTD patients should exhibit increased deficits related to gait, surprisingly, results have been inconsistent and the relationship between sub-types and objective measures of gait have not yet been fully described. Methods: Thirty-one PD participants (mean UPDRS-III = 15) were included in this study and stratified into TD (n=18) or NTD (n=13) based on initial onset symptom. Participants were provided with an Ambulosono walking device consisting of an iPod Touch and GaitReminder application that utilizes gait signals to control music playlists to motivate subjects in undertaking unrestricted, naturalistic, and long-distance walking in their communities. Walking data captured under such walking conditions may give rise to a diverse dataset related to stride length and time. Results: We found no significant differences in gender, age, leg-length, UPDRS-III score, walking speed, walking time, or number of walks between PD sub-types. However there was a significant difference in the relationship between cadence and step-length relative to speed. NTD exhibited disproportionately smaller contributions of step-length relative to cadence with decreased walking speed. This gait index, the speed-standardized cadence-step length ratio, had an optimal specificity and sensitivity of 94.4[percnt] and 76.9[percnt] respectively for predicting the NTD sub-type. Conclusion: These findings may provide a quantitative index to better longitudinally track disease progression and further help in understanding the mechanisms that may contribute to gait in PD. Acknowledgements: CIHR, AIHS, MITACs, Branch Out Foundation, Pedal for Parkinson’s, the MDC-AHS, the Brazilian agencies: CNPq and CAPES, and Dr. Patrick Whelan for insightful discussion. TC and FVP are co-first authors.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".