Development of a Health Questionnaire Specific for End-Stage Renal Disease
Bibliographic record
Abstract
To compare the efficacy of various end-stage renal disease (ESRD) therapies valid and reproducible probes which measure well-being and are specific for ESRD are necessary. Four studies were undertaken to provide and test these probes. (1) 107 dialysis and 119 transplant recipients were interviewed to determine the prevalence of 24 physical symptoms. (2) A questionnaire was devised using 2 new indexes (a symptom scale derived from the first study using 12 symptoms and an affect scale comprising 12 emotions) and 6 indexes previously used in other chronic illnesses. Interobserver and intraobserver reproducibility was satisfactory. (3) Construct validity for the questionnaire was shown by interviewing 97 dialysis and 82 transplant patients in whom we hypothesized that physical well-being would be better in transplant patients. After age matching the transplant group was more active, with a higher objective quality of life and fewer physical symptoms than the dialysis group. (4) 63 stable dialysis, 67 stable transplant, 15 dialysis patients successfully transplanted in the intervening year and 5 failed transplanted patients were reinterviewed 1 year later to assess the responsiveness of the questionnaire. In the group who had recently been successfully transplanted both physical, affect and quality of life scores showed a major improvement following transplant. We conclude that this questionnaire is specific for ESRD, examines physical, psychological, and social well-being, is brief, easily administered, reproducible, has construct validity and is responsive to changes in therapy.
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".