Metabolic Syndrome Negatively Impacts Stone-Specific Quality of Life
Bibliographic record
Abstract
Purpose: Metabolic syndrome (MetS) is a cluster of metabolic diseases that is linked to atherosclerotic cardiovascular disease. MetS has also been linked to increased nephrolithiasis. However, limited research has been conducted on MetS and its impact on stone-specific health-related quality of life (HRQOL). This study aims to examine the hypothesis that the presence of MetS is associated with decreased HRQOL. Materials and Methods: The Wisconsin Stone Quality of Life Questionnaire, a stone-specific HRQOL questionnaire, was used to survey 3051 patients with kidney stones. Medical history was collected from patients. These data were used to distinguish MetS patients from non-MetS patients. Among patients with current stones, a Wilcoxon rank sum test was used to compare HRQOL scores from MetS patients and non-MetS patients. HRQOL from patients with and without individual MetS components were also compared, and a multivariate analysis was conducted. Results: Statistical comparison between MetS patients (median score 102/140) and non-MetS patients (median score 106/140) demonstrated a lower stone-specific HRQOL in patients with MetS ( p = 0.049). Among individual MetS components, patients with diabetes mellitus (DM) or body mass index (BMI) >30 had significantly lower HRQOL than patients without DM or BMI <30 ( p = 0.028 and p < 0.001, respectively). The multivariate analysis supported this trend as MetS remained a significant predictor of decreased HRQOL ( p = 0.002) after controlling for other variables assessed. Conclusions: This study indicates an association between MetS and a lower stone-specific QOL. This has important implications for stone prevention strategies in patients with MetS. Clinical Trial Registration number: H14-01143
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".