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MP40-15 THE PREVALENCE OF VITAMIN D DEFICIENCY AMONG PATIENTS IN A TERTIARY METABOLIC STONE CLINIC IN ONTARIO, CANADA

2024· article· en· W4394803180 on OpenAlexaboutno aff
Mario Basulto-Martínez, Tariq Alotaibi, Jennifer Bjazevic, Hassan Razvi

Bibliographic record

VenueThe Journal of Urology · 2024
Typearticle
Languageen
FieldHealth Professions
TopicTherapeutic Uses of Natural Elements
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTertiary carevitamin D deficiencyPediatricsTertiary levelInternal medicineVitamin D and neurologyPsychology

Abstract

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You have accessJournal of UrologyStone Disease: Epidemiology & Evaluation I (MP40)1 May 2024MP40-15 THE PREVALENCE OF VITAMIN D DEFICIENCY AMONG PATIENTS IN A TERTIARY METABOLIC STONE CLINIC IN ONTARIO, CANADA Mario Basulto-Martínez, Tariq Alotaibi, Jennifer Bjazevic, and Hassan Razvi Mario Basulto-MartínezMario Basulto-Martínez , Tariq AlotaibiTariq Alotaibi , Jennifer BjazevicJennifer Bjazevic , and Hassan RazviHassan Razvi View All Author Informationhttps://doi.org/10.1097/01.JU.0001008788.18007.3f.15AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Metabolic stone disease is becoming increasingly common worldwide due to a variety of factors. Vitamin D deficiency has been implicated as a variable although its exact role in the development of calcium oxalate stones is uncertain and its management controversial. In this study we sought to determine the prevalence of Vitamin D deficiency among a cohort of stone-formers in southern Ontario, Canada and compared their clinical and metabolic data with those patients with normal Vitamin D levels. METHODS: Data from patients seen in the Metabolic Stone Clinic at St. Joseph's Hospital in London, Ontario, Canada between 2005-2019 -was retrospectively reviewed. Clinical data as well results of 24 hour urine collections and serum biochemistry values were recorded. Vitamin D levels were defined as deficient if<50 mmol/L, insufficient if between 50 – 75 mmol/L, and sufficient when between 75 – 250 mmol/L. Clinical and metabolic data were compared between the low and normal vitamin D subjects. RESULTS: A total of 748 stone-formers were included. Two hundred and seventy-four patients (36.5%) had a normal vitamin D whereas 474 (63.5%) had low vitamin D [220 deficient (29.5%), and 254 insufficient (34%)]. Stone-formers with low vitamin D were younger [53 (42.5 – 61) vs 57 (44 – 67) years, p<0.001], had higher body mass index (BMI) [29.3 (25.7 – 33.3) vs 27.5 (24.3 – 31.9) Kg/m2, p<0.001], and were predominately female [55.6 vs 46.4%, p=0.019]. In the metabolic workup, stone-formers with low vitamin D had lower urinary volume [1.66 (1.24 – 2.35) vs 1.97 (1.40 – 2.70) L/day, p<0.001], slightly lower serum calcium [2.30 (2.23 – 2.36) vs 2.32 (2.25 – 2.39) mmol/L, p=0.015], and higher PTH [4.3 (3.2 – 5.8) vs 3.8 (3 – 4.8) pmol/L, p<0.001]. Among patients with low Vitamin D, 13.3% had evidence of secondary hyperparathyroidism. Stone composition was comparable between groups. CONCLUSIONS: This study of stone patients in a southern Canadian community found that Vitamin D deficiency is common. Patients with low Vitamin D levels were predominantly female, younger, and had higher BMIs than those with normal vitamin D. Moreover, low vitamin D stone-formers had lower serum calcium levels, probably due to decreases in intestinal absorption of calcium but no difference were observed in 24-h urine calcium. Higher PTH levels were observed in low vitamin D stone-formers related to secondary hyperparathyroidism. The implications of these findings are significant in that failure to correct Vitamin D deficiency in these patients in addition to potentially contributing to ongoing stone formation may also have deleterious effects on bone health. Identifying Vitamin D deficiency among stone formers in regions with seasonal variations in sunlight exposure seems warranted. Source of Funding: None © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e669 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Mario Basulto-Martínez More articles by this author Tariq Alotaibi More articles by this author Jennifer Bjazevic More articles by this author Hassan Razvi More articles by this author Expand All Advertisement PDF downloadLoading ...

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score0.807

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.027
GPT teacher head0.351
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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