Parkinson's disease‐related fatigue: A case definition and recommendations for clinical research
Bibliographic record
Abstract
Fatigue is one of the most common and disabling symptoms in Parkinson's disease (PD). Since fatigue was first described as a common feature of PD 20 years ago, little progress has been made in understanding its causes or treatment. Importantly, PD patients attending the 2013 World Parkinson Congress voted fatigue as the leading symptom in need of further research. In response, the Parkinson Disease Foundation and ProjectSpark assembled an international team of experts to create recommendations for clinical research to advance this field. The working group identified several areas in which shared standards would improve research quality and foster progress including terminology, diagnostic criteria, and measurement. Terminology needs to (1) clearly distinguish fatigue from related phenomena (eg, sleepiness, apathy, depression); (2) differentiate subjective fatigue complaints from objective performance fatigability; and (3) specify domains affected by fatigue and causal factors. We propose diagnostic criteria for PD-related fatigue to guide participant selection for clinical trials and add rigor to mechanistic studies. Recommendations are made for measurement of subjective fatigue complaints, performance fatigability, and neurophysiologic changes. We also suggest areas in which future research is needed to address methodological issues and validate or optimize current practices. Many limitations in current PD-related fatigue research may be addressed by improving methodological standards, many of which are already being successfully applied in clinical fatigue research in other medical conditions (eg, cancer, multiple sclerosis). © 2016 International Parkinson and Movement Disorder Society.
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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 | 0.015 | 0.039 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.013 | 0.007 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.008 | 0.034 |
| Open science | 0.010 | 0.009 |
| Research integrity | 0.028 | 0.014 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".