Patient-Generated Graphs to Measure Pain and Fatigue in Persons with Neuralgic Amyotrophy
Bibliographic record
Abstract
Background: Patients with neuralgic amyotrophy (NA) often experience limitations in daily activities because of pain and fatigue. Visual analogue graphs with a 24-hour x-axis can be used to rate pain and fatigue severity during a typical day. This study aimed to investigate the reliability and validity of the visual analogue graphs in patients with NA. Method: Eight patients completed pain and fatigue graphs on three moments to examine inter-rater and test-retest reliability using Intraclass Correlation Coefficients (ICCs). Concurrent validity (n = 47) was tested by determining correlations between mean pain graph scores and numerical rating scale for pain (NRS-pain) and between mean fatigue graph scores and checklist individual strength-subscale fatigue (CIS-fatigue). Results: ICC for test-retest reliability varied from 0.72– 0.93 for pain and 0.67–0.85 for fatigue scores. ICC for inter-rater reliability varied from 0.76–0.97 for pain and 0.47–0.97 for fatigue scores. Correlation between the mean pain graph score and NRS-pain was strong (rs = 0.75, ps = 0.42, p = 0.003). Conclusion: The visual analogue graph for pain appears reliable and valid in patients with NA. Test-retest reliability and concurrent validity for the fatigue graph warrant further research.
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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 | 0.000 |
| 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 | 0.000 |
| 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".