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The Relationship Between Urinary Stone Disease and Nutrition Type in Infants

2022· article· en· W4221125408 on OpenAlexvenueno aff
Kyaw Zin Latt, Yelda Türkmenoğlu, Alper Kaçar, Ahmet İrdem, Hasan Dursun

Bibliographic record

VenueInternational Journal of Child Health and Nutrition · 2022
Typearticle
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreastfeedingUrinary systemPediatricsBreast milkUrineCreatinineFamily historyBreast feedingVitamin D and neurologyPhysiologyInternal medicine

Abstract

fetched live from OpenAlex

The relationship between urinary stone disease and nutrition in infants is not well known. This study investigates the relationship between breast milk, formula and supplementary foods, vitamin D usage, and family stone history with urinary system stones in children aged 3-24 months. The study included 100 infants aged 3-24 months of age with urinary tract stones and 40 healthy infants with similar age and gender as the control group. Sixty of the patients were boys, and 40 were girls; the control group consisted of 26 boys and 16 girls. There was no significant difference in only breastfeeding, breastfeeding plus formula, and formula feeding in the patients and controls. Positive family history of urolithiasis was significantly higher in the patients compared to the controls (p=0.04). While breastfeeding duration time was negatively correlated with spot urine calcium to creatinine ratio in children exclusively breastfed infants. No direct effect of nutrition type and vitamin D usage on stone formation was found in infants. It has been shown that stone formation in this age group is associated with a family history of stones. In this study, the duration of breastfeeding is negatively correlated with the spot urinary calcium to creatinine ratio.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.350
Teacher spread0.320 · 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 source (direct Gemma or distilled Codex), 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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Child Health and NutritionSame topicKidney Stones and Urolithiasis TreatmentsFrench-language works237,207