'Don't delay, start today': delaying levodopa does not delay motor complications
Bibliographic record
Abstract
This scientific commentary refers to ‘The modern pre-levodopa era of Parkinson’s disease: insights into motor complications from sub-Saharan Africa’, by Cilia et al. (doi:10.1093/brain/awu195). Preventing the development of motor complications is one of the principal concerns when treating patients with Parkinson’s disease, and ‘levodopa-sparing’ approaches have been commonly touted as the best method of achieving this. Early use of dopamine agonists, rather than levodopa, was the preferred management strategy in the 1990–2000s, and several large randomized controlled trials reported delayed development of motor complications with this approach. However, follow-up studies revealed that once patients were started on levodopa, they developed motor complications of the same severity and at the same rate irrespective of whether levodopa had been initiated earlier or later. Indeed, after 10–14 years of treatment, patient profiles were essentially identical regardless of how they began dopaminergic therapy (Katzenschlager et al. , 2008). These results, combined with increasing awareness of the major side-effects of dopamine agonists—particularly sleepiness and impulse-control disorders—have led many physicians to switch to earlier use of levodopa as monotherapy, particularly in patients over 60 years of age in whom the risk of dyskinesia is lower. In this issue of Brain , Cilia and colleagues present data that help endorse this strategy (Cilia et al. , 2014). This cross-sectional and 4-year longitudinal study recruited patients with Parkinson’s disease from Ghana ( n = 91) and Italy ( n = 2282). The authors took advantage of the opportunity to study patients from sub-Saharan Africa who typically experience longer delays in receiving levodopa therapy than patients in first world countries. Demographics and disease-related factors influencing the development of motor fluctuations and levodopa-induced dyskinesia (LID) were evaluated for both groups. Although accurate recording of LID can be difficult, the authors attempted to determine dates of onset as precisely as possible. …
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".