Sensitivity and specificity of 24-hour urine chemistry levels for detecting elevated calcium oxalate and calcium phosphate supersaturation
Bibliographic record
Abstract
OBJECTIVES: The gold standard for determining likelihood of calcium oxalate (CaOx) and calcium phosphate (CaPhos) stone formation in urine is supersaturation of CaOx and CaPhos. Our objective was to investigate whether traditional measurement of total calcium, oxalate and phosphate in a 24-hour urine collection is sufficiently sensitive and specific for detecting elevated supersaturation to preclude the more expensive supersaturation test. METHODS: We performed a retrospective review of 150 consecutive patients with nephrolithiasis who underwent measurement of CaOx supersaturation (CaOxSS) and CaPhos supersaturation (CaPhosSS), as well as total calcium, oxalate and phosphate in a 24-hour urine collection. We used various cut-off values to determine sensitivity and specificity of 24-hour urine measurements for detecting elevated CaOxSS and CaPhosSS. RESULTS: In men and women, the sensitivity of 24-hour calcium for detecting elevated CaOxSS was 71% and 79%, respectively; for oxalate, sensitivity was 59% and 36%, respectively. In men and women, the sensitivity of 24-hour calcium for detecting elevated CaPhosSS was 74% and 88%, respectively; for phosphate, sensitivity was 57% and 8%, respectively. In men and women, the specificity of 24-hour calcium for detecting elevated CaOxSS was 55% and 48%, respectively; it was 60% for detecting elevated CaPhosSS in both men and women. CONCLUSION: Traditional 24-hour urine analysis is sensitive, but not specific, for detecting elevated CaOxSS and CaPhosSS. Most patients with abnormal 24-hour urine analysis have normal supersaturation, and treatment decisions based on traditional urine analysis would lead to overtreatment in these patients.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".