Only Size Matters in Stone Patients: Computed Tomography Controlled Stone-Free Rates after Mini-Percutaneous Nephrolithotomy
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Bibliographic record
Abstract
OBJECTIVE: To examine and predicting stone-free rates (SFRs) after minimally invasive-percutaneous nephrolithotomy (mini-PNL) based on computed tomography (CT), instead of X-ray or ultrasound control. PATIENTS AND METHODS: We identified 146 mini-PNL patients with pre- and postoperative CT scans. Patient and stone characteristics were assessed. Stone-free status was defined as ≤3 mm residual fragment after mini-PNL according to postsurgery CT scan. Multivariable logistic regression analyses predicted stone-free status after mini-PNL. RESULTS: Overall, 62 (42.5%) patients achieved stone-free status after mini-PNL. In multivariable analyses, stone size was the only independent predictor for stone-free status (OR 0.9; p = 0.02). Patients with stones > 20 mm were less likely to achieve stone-free status, than those harboring stones 10-20 mm (OR 0.3; p = 0.009). SFRs according to stone size categories (< 10, 10-20, and > 20 mm) were 33.3, 50.5, and 25%. Body mass index (BMI) and stone density (Houndsfield units) were no independent predictors for stone-free status after mini-PNL. CONCLUSIONS: We report lower SFRs than expected. Stone size was the only independent predictor for stone-free status after mini-PNL. Patients with larger stones need to be informed about high risk of additional interventions. High BMI and high stone density do not represent a barrier for stone-free status after mini-PNL.
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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) | 0.002 | 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 it