Early Clinical Predictors of Treatment‐Resistant and Functional Outcomes in Parkinson's Disease
Bibliographic record
Abstract
Abstract Background The aim of this work was to identify early clinical predictors of important outcomes in Parkinson's disease ( PD ). In PD , treatment‐resistant (e.g., dementia, falling) and other important functional outcomes (e.g., declines in quality of life [ QOL ] and activities of daily living [ ADL ]) emerge and become increasingly disabling. Methods We analyzed longitudinal data from 491 early, untreated PD subjects who enrolled in the Pre CEPT trial, had baseline SPECT dopamine transporter deficit, and have continued in the Post CEPT observational cohort. After Pre CEPT , antiparkinsonian medications were added if needed. Baseline clinical precursors were examined as potential predictors of selected outcomes. Separate and multivariate logistic regressions, adjusted for certain baseline factors, were performed for dichotomized outcomes evaluated at the last Post CEPT visit. Results On enrollment, subjects had average disease duration of 0.8 years and were followed for an average of 5.5 years. Some baseline precursors were found to be predictive: disease stage, cognitive, and ADL scores for dementia; disease stage, ADL , and motor and freezing scores for hallucinations; disease stage, depression, ADL , and freezing and walking scores for falling; and ADL , depression, and motor and walking scores and disease stage for QOL decline. No baseline clinical feature predicted decline in ADL . Being on levodopa was not a significant predictor of any outcome, but subjects on a dopamine agonist were significantly less impaired with respect to falling, abnormal Mini–Mental State Examination, and QOL . Conclusions Although there are limitations, results support the value of longitudinal follow‐up of clinical trial populations to identify early clinical precursors of important outcomes and thereby identify high‐risk patients early on.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| 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".