Initiating dopamine agonists rather than levodopa in early Parkinson’s disease does not delay DBS
Bibliographic record
Abstract
Objective & Background To determine whether there is a difference intime between initial levodopa vs dopamine agonists (DA) treatment and the development of disabling motor complications (MC) prompting consideration of deep brain stimulation (DBS). While levodopa is the most effective symptomatic treatment for Parkinson’s disease (PD), its use is asso- ciated with an increased risk of MC compared to DA first therapy.It is not known whether the early delay in MC with initial DA therapy translates into true benefit with respect to disabling MC that are the major indication for DBS later on. Methods We performed a retrospective cohort study of 1627 PD patients attending DBS clinic, Toronto Western Hospital, Canada (03/2004-02/2022). PD patients who underwent globus pallidus interna (GPi)/subthalamic nucleus (STN) DBS >2005 to address disabling MC were included. Results 438 patients were included (352 STN DBS, 86 GPi). The median disease duration was 9 years. 312 patients received levodopa first and 126 a DA. There was no difference in the target selection/amanta- dine use. The duration first treatment-DBS assessment (L-dopa median 8, IQR 4; DA median 9, IQR 4) or DBS surgery, did not significantly differ. This is the only study to date to evaluate the duration between L-dopa/DA first treatment and the devel- opment of MC of sufficient severity to warrant DBS. The development of disabling motor complications warranting DBS is independent of the type of first dopaminergic treatment.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".