Levodopa Equivalent Daily Dosage: Geographical Variations and Real‐Life Modules in Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: The Levodopa Equivalent Daily Dosage (LEDD) calculation algorithms help in capturing and harmonization of Parkinson's Disease (PD) therapies. Analyzing these updates is essential for validating their effectiveness. OBJECTIVE: To assess updated LEDD conversion factors in capturing the newer therapies in PD and therapy modules in different geographical cohorts. METHODS: Data were sourced from 10 Centers from 6 countries representing 2 different continents. The study compared the LEDD conversion factors proposed by Tomlinson et al and Jost et al, alongside investigating demographic disparities. RESULTS: The analysis involved 2943 subjects; 87% (n = 2577) met the UK Brain Bank criteria for PD. The LEDD differed significantly across methodologies (Tomlinson vs. Jost, 598 mg vs 610 mg, P < 0.0001). Geographical disparities highlighted variations in PD onset age (P < 0.0001). Jost and Tomlinson's calculations demonstrated consistency within but significant differences across countries (P < 0.0001).Age at onset revealed statistically significant differences in LEDD requirements (P < 0.0001), which were particularly higher in 21-50 years (718 mg vs 566 mg). This subgroup also demonstrated increased usage of non-Levodopa therapies (P < 0.0001). Men exhibited higher total LEDD (P = 0.001). 34% reported dyskinesia, associated with higher LEDD (756 mg, P < 0.0001). Surgically treated patients also had higher LEDD (P < 0.0001) and a significant difference between Jost and Tomlinson dosages (761 mg vs716mg) reflecting the incorporation of newer therapeutic molecules. CONCLUSION: This analysis delineates the importance of updated LEDD algorithms and intricacies in the landscape of PD treatment, underscored by geographical, age-related, and gender-specific variations, in real-life management scenarios.
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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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".