Prospective randomized trial of 2 versus 12‐weeks of postoperative antibiotics after percutaneous nephrolithotomy in complex patients with infection‐related kidney stones
Bibliographic record
Abstract
PURPOSE: Treatment of struvite kidney stones requires complete surgical stone removal combined with antibiotic therapy to eliminate urinary tract infections and preventive measures to reduce stone recurrence. The optimal duration of antibiotic therapy is unknown. We sought to determine if 2- or 12-weeks of antibiotics post percutaneous nephrolithotomy (PNL) for infection stones resulted in better outcomes for stone recurrence and positive urine cultures. MATERIAL AND METHODS: This multi-center, prospective randomized trial evaluated patients with the clinical diagnosis of infection stones. Patients were randomized to 2- or 12-weeks of postoperative oral antibiotics (nitrofurantoin or culture-specific antibiotic) and included if residual fragments were ≤4 mm on computed tomography imaging after PNL. Imaging and urine analyses were performed at 3-, 6-, and 12-months post-procedure. RESULTS: Thirty-eight patients were enrolled and randomized to either 2-weeks (n = 20) or 12-weeks (n = 18) of antibiotic therapy post-PNL. Eleven patients were excluded due to residual fragments >4 mm, and 3 patients were lost to follow-up. The primary outcome was the stone-free rate (SFR) at 6 months post-PNL. At 3-, 6-, and 12-months follow-up, SFRs were 72.7% versus 80.0%, 70.0% versus 57.1%, 80.0% versus 57.1% (p = ns), between 2- and 12-week-groups, respectively. At 3-, 6-, and 12-months follow-up, positive urine cultures were 50.0% versus 37.5%, 50.0% versus 83.3%, and 37.5% versus 100% between 2- and 12-week groups, respectively (p = ns). CONCLUSIONS: For patients with stone removal following PNL, neither 2-weeks nor 12-weeks of postoperative oral antibiotics is superior to prevent stones and recurrent positive urine cultures.
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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".