Stone composition of renal stone formers from different global regions
Bibliographic record
Abstract
OBJECTIVE: To study urinary stone composition patterns in different populations around the world. MATERIALS AND METHODS: Data were collected by reviewing charts of 1204 adult patients of 10 countries with renal or ureteral stones (> 18 years) in whom a stone analysis was done and available. Any method of stone analysis was accepted, but the methodology had to be registered. RESULTS: In total, we observed 710 (59%) patients with calcium oxalate, 31 (1%) with calcium phosphate, 161 (13%) with mixed calcium oxalate/calcium phosphate, 15 (1%) with carbapatite, 110 (9%) with uric acid, 7 (< 1%) with urate (ammonium or sodium), 100 (9%) with mixed with uric acid/ calcium oxalate, 56 (5%) with struvite and 14 (1%) with cystine stones. Calciumcontaining stones were the most common in all countries ranging from 43 to 91%. Oxalate stones were more common than phosphate or mixed phosphate/oxalate stones in most countries except Egypt and India. The rate of uric acid containing stones ranged from 4 to 34%, being higher in Egypt, India, Pakistan, Iraq, Poland and Bulgaria. Struvite stones occurred in less than 5% in all countries except India (23%) and Pakistan (16%). Cystine stones occurred in 1% of cases. CONCLUSIONS: The frequency of different types of urinary stones varies from country to country. Calcium-containing stones are prevalent in all countries. The frequency of uric acid containing stones seems to depend mainly on climatic factors, being higher in countries with desert or tropical climates. Dietary patterns can also lead to an increase in the frequency of uric acid containing stones in association with high obesity rates. Struvite stones are decreasing in most countries due to improved health conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".