Freezing of Gait can persist after an acute levodopa challenge in Parkinson’s disease
Bibliographic record
Abstract
Study objectives included testing whether presumed levodopa-unresponsive freezing of gait (FOG) in Parkinson's disease (PD) actually persists in the presence of adequate dopaminergic dosing and to investigate whether the presence of other parkinsonian features and their responsiveness to therapy varies across patients without FOG (NO-FOG), with levodopa-responsive FOG (OFF-FOG), and with levodopa-unresponsive FOG (ONOFF-FOG). Fifty-five PD patients completed levodopa challenges after >12-h OFF with supratherapeutic doses of dopaminergic medications. Observed responses in FOG, measured with MDS-UPDRS-III during the patient reported full "ON", were used to classify them as NO-FOG, OFF-FOG, or ONOFF-FOG. Serum levodopa levels were measured. Only those with ≥20% improvement in MDS-UPDRS-III score were included in analyses. Levodopa challenge was sufficient to bring about a full "ON" state with ≥20% improvement in 45 patients. Levodopa-equivalent-dose utilized was 142 ± 56% of patients' typical morning doses. Overall, 19/45 patients exhibited FOG in the full "ON" state (ONOFF-FOG), 11 were classified as OFF-FOG, and 15 NO-FOG. Linear mixed models revealed a highly significant association between serum levodopa level and total MDS-UPDRS-III score that was similar across groups. The ONOFF-FOG group exhibited significantly higher New-FOG-questionnaire and MDS-UPDRS-II scores compared to the OFF-FOG group. Among MDS-UPDRS-III subdomains significant effects of group (highest in ONOFF-FOG) were identified for other axial parkinsonian features. We found that FOG can persist in the full "ON" state brought about by ample dopaminergic dosing in PD. Other axial measures can also be levodopa-unresponsive among those with ONOFF-FOG only. These data provide evidence that ONOFF-FOG is distinct from responsive freezing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".