Method of Levodopa Response Calculation Determines Strength of Association With Clinical Factors in Parkinson Disease
Bibliographic record
Abstract
BACKGROUND: The levodopa challenge test is routinely used in Parkinson disease (PD) to determine a patient's motor improvement following levodopa administration [levodopa response (LR)]. LR is most commonly reported as a percent OFF to ON change in the Unified Parkinson Disease Rating Scale (UPDRS) part III score, and occasionally as an absolute difference in score. This inconsistency in LR determination alters how clinical factors such as patient age and disease duration are understood in relation to LR in PD. OBJECTIVE: The aim of this study was to compare the calculation of the LR as either a percent change or difference in UPDRS-III motor score between OFF and ON medication. These two scores were then used to correlate to disease duration, patient age, levodopa duration, levodopa equivalent dose (LED), OFF score, cognition, mood, gait, and quality of life (QOL). METHODS: 70 PD patients underwent the levodopa challenge test. The UPDRS-III motor examination was performed in the defined OFF and ON medication states to determine LR. Each patient was assessed after 12-14 h without anti-parkinsonian medication and then given three 100/25 mg levodopa/carbidopa tablets. LR was reported as both a difference in score [OFF - ON; absolute LR (aLR)] and as a percent change in score [(OFF - ON)/OFF*100%; %LR]. Patients completed the following non-motor symptom assessment scales: Montreal Cognitive Assessment, Freezing of Gait Questionnaire, Activities-specific Balance Confidence Scale, Parkinson's Disease Questionnaire, and Geriatric Depression Scale. The effect of the LR calculation method was correlated to the clinical measures. RESULTS: = 0.30). By contrast, the more commonly used %LR demonstrated no significant relationships with any of the variables tested. CONCLUSION: Although the %LR is more commonly employed in clinical protocols and research studies, the aLR is the superior method for reporting motor response to levodopa in PD given its significant associations with the clinical factors evaluated.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".