The effect of travel distance on health-related quality of life for patients with nephrolithiasis
Bibliographic record
Abstract
INTRODUCTION: Urolithiasis causes a significant impact on health-related quality of life (HRQOL). Patients with kidney stones have high levels of stress and anxiety. Symptom resolution often requires treatment. Travel distance is a barrier to care but little is known about its effects on HRQOL. We hypothesize that increased distance to treatment site is associated with decreased HRQOL. METHODS: Patients with a history of stones were enrolled at 11 tertiary centers as part of the QOL Stone Consortium of North America. HRQOL data were obtained using the Wisconsin Stone Quality of Life questionnaire (WISQOL). We calculated distance between patient and treatment site using national ZIP codes. We used linear models to evaluate the effect of distance on HRQOL, while also considering demographics data, stones/symptom status, and distance. RESULTS: Of the 1676 enrolled patients, 52% were male, 86% non-Latino White, and the mean age was 53 years. Mean distance to treatment site was 63.3 km (range 0-3774), with 74% reporting current stones and 45% current symptoms. WISQOL score and distance were negatively correlated for patients reporting current stones and symptoms (p=0.0010). Linear modelling revealed decreased WISQOL scores for patients with symptoms as distance increased from treatment site (p=0.0001), with a 4.7-point decrease for every 100 km traveled. CONCLUSIONS: Stone disease imposes significant burden on patients' HRQOL due to a variety of factors. Patients with active stone symptoms report worse HRQOL with increased distance to their treatment site. Possible etiologies include travel burden, increased disease burden, decreased healthcare use, and delays in care.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".