Screening for asymptomatic nephrolithiasis in primary hyperparathyroidism patients is warranted
Bibliographic record
Abstract
BACKGROUND: We aimed to investigate the prevalence, characteristics, and management of nephrolithiasis in primary hyperparathyroidism (PHPT) patients. METHODS: Medical records of patients who underwent parathyroidectomy at a tertiary care hospital in British Columbia from January 2016 to April 2023 were retrospectively reviewed. Demographic data, laboratory results, imaging reports, and urologic consultations were examined. Descriptive statistics and relevant statistical tests, including logistic regressions, were utilized for data analysis. RESULT: Of the 413 PHPT patients included in the study population, 41.9% harbored renal stones, and nearly half (48.6%) required urological interventions. Male sex, elevated preoperative serum ionized calcium (iCa) and 24-h urinary calcium (24 h urine Ca) levels were independent risk factors for stone formation. Additionally, male sex, younger age, and lower preoperative serum 25-hydroxyvitamin D (25(OH)D) level were associated with higher odds of requiring urological intervention for stones. CONCLUSIONS: This study identified significant prevalence of asymptomatic renal calcifications in PHPT patients, with a substantial proportion necessitating urological intervention. These findings emphasize the importance of incorporating screening and treatment of renal stones into the management of PHPT 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".