MP45-06 POPULATION-BASED DIETARY RISKS FOR KIDNEY STONES: IMPLICATIONS FOR DIETARY COUNSELING AND PREVENTION
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Résumé
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 ...
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,088 | 0,018 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».