Validation of a simple disease-specific, quality-of-life measure for diabetic polyneuropathy
Bibliographic record
Abstract
OBJECTIVE: We studied the performance of a 15-item, health-related quality-of-life polyneuropathy scale in the clinic setting in patients with diabetic distal sensorimotor polyneuropathy (DSPN). METHODS: Patients with DSPN from 11 academic sites completed a total of 231 Chronic Acquired Polyneuropathy Patient-Reported Index (CAPPRI) scales during their clinic visits. Conventional and modern psychometric analyses were performed on the completed forms. RESULTS: Conventional and modern analyses generally indicated excellent psychometric properties of the CAPPRI in patients with DSPN. For example, the CAPPRI demonstrated unidimensionality and performed like an interval-level scale. CONCLUSION: Attributes of the CAPPRI for DSPN include ease of use and interpretation; unidimensionality, allowing scores to be summed; adequate coverage of disease severity; and the scale's ability to address relevant life domains. Furthermore, the CAPPRI is free and in the public domain. The CAPPRI may assist the clinician and patient with DSPN in estimating disease-specific quality of life, especially in terms of pain, sleep, psychological well-being, and everyday function. The CAPPRI may be most useful in the everyday clinical setting but merits further study in this setting, as well as the clinical trial setting.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".