The impact of kidney stone disease on quality of life in high‐risk stone formers
Bibliographic record
Abstract
OBJECTIVE: To assess the impact of kidney stone disease (KSD) and its treatment on the health-related quality of life (HRQOL) of high-risk stone formers with hyperparathyroidism, renal tubular acidosis, malabsorptive disease, and medullary sponge kidney. PATIENTS AND METHODS: The Wisconsin Stone Quality of Life questionnaire was used to evaluate HRQOL in 3301 patients with a history of KSD from 16 institutions in North America between 2014 and 2020. Baseline characteristics and medical history were collected from patients, while active KSD was confirmed through radiological imaging. The high-risk group was compared to the remaining patients (control group) using the Wilcoxon rank-sum test. RESULTS: Of 1499 patients with active KSD included in the study, the high-risk group included 120 patients. The high-risk group had significantly lower HRQOL scores compared to the control group (P < 0.01). In the multivariable analyses, medullary sponge kidney disease and renal tubular acidosis were independent predictors of poorer HRQOL, while alkali therapy was an independent predictor of better HRQOL (all P < 0.01). CONCLUSIONS: Among patients with active KSD, high-risk stone formers had impaired HRQOL with medullary sponge kidney disease and renal tubular acidosis being independent predictors of poorer HRQOL. Clinicians should seek to identify these patients earlier as they would benefit from prompt treatment and prevention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".