MP45-06 POPULATION-BASED DIETARY RISKS FOR KIDNEY STONES: IMPLICATIONS FOR DIETARY COUNSELING AND PREVENTION
Bibliographic record
Abstract
You have accessJournal of UrologyStone Disease: Epidemiology & Evaluation II (MP45)1 May 2024MP45-06 POPULATION-BASED DIETARY RISKS FOR KIDNEY STONES: IMPLICATIONS FOR DIETARY COUNSELING AND PREVENTION Anna J. Black, Ghizlane Moussaoui, and Connor M. Forbes Anna J. BlackAnna J. Black , Ghizlane MoussaouiGhizlane Moussaoui , and Connor M. ForbesConnor M. Forbes View All Author Informationhttps://doi.org/10.1097/01.JU.0001008764.86460.8e.06AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Dietary risk factors for kidney stone formation have been identified, and guidelines for preventing kidney stone recurrences have been developed. In the context of the increasing incidence of kidney stones, we aim to assess the percentage of the population who are eating an at-risk diet for kidney stones and to understand the baseline diet for future counseling. METHODS: The 2015 Canadian Community Health Survey, a national cross-sectional instrument administered by Statistics Canada and Health Canada, was queried. Intake of relevant nutrients was compared to dietary risk factors for kidney stone formation. Factors associated with nutrient intake were analyzed in a multivariable regression. RESULTS: Data for 14 275 participants was included, of whom only 34% consumed>2 L of fluid per day and only 9.4% consumed 1000-1200 mg of dietary calcium. 53.9% consumed too much sodium but 61% of the population had the recommended protein intake. Less than 1% of the population had no dietary risk factors for developing kidney stones, while 92.2% have two or more risk factors. Fluid, sodium, calcium, and protein intake increased significantly with education level, income, and if employed (p<0.01). Participants with food insecurity were more likely to have low dietary protein and calcium but had no significant differences in sodium or fluid intake.Hypertension was associated with lower intake of fluid, sodium, calcium, and protein, while an elevated BMI was associated with increased intake of each of these (p<0.05 for all). Osteoporosis but not dairy-free diets were associated with low calcium.Supplements were common, with 62.3% of the population taking a supplement containing vitamin C, 51.2% vitamin B6, 47.2% calcium, and 38% magnesium. CONCLUSIONS: While only a subset of the population will develop stones, this study shows that 92.2% of the population is eating a diet that elevated the risk of stone disease. As the incidence of kidney stones increases, population-based dietary interventions should be considered. Furthermore, clinicians may use these data to understand the average diet as a starting point for questioning and counseling patients. Source of Funding: None © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e744 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Anna J. Black More articles by this author Ghizlane Moussaoui More articles by this author Connor M. Forbes More articles by this author Expand All Advertisement PDF downloadLoading ...
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.088 | 0.018 |
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".