Percutaneous Nephrolithotripsy in Patients with Urinary Diversions: A Case-Control Comparison of Perioperative Outcomes
Bibliographic record
Abstract
PURPOSE: To compare the operative techniques and perioperative outcomes of patients with urinary intestinal diversions undergoing percutaneous nephrolithotripsy (PCNL), to a control cohort of patients without diversions. PATIENTS AND METHODS: The medical records of all patients who were treated with PCNL from 1990 to 2009 were retrospectively reviewed. Each urinary diversion patient's first PCNL was age-matched with four controls who were undergoing PCNL. The perioperative outcomes were compared between the diversion and control cohorts. RESULTS: Twenty-five patients with a urinary diversion who had undergone 33 PCNLs were identified. The mean age was 49.3 (8-85) years for the diversion group and 48.9 (4-84) for the control group. Urinary tract infection (64% vs 15% patients, P<0.0001), neurologic disease (64% vs 2%, P<0.0001), previous procedure for the same calculus (24% vs 4%, P=0.0004), urinary tract abnormalities (56% vs 14%, P<0.0001), solitary kidney (20% vs 3%, P=0.0081), and struvite stones (80% vs 12.5%, P=0.0006) were more commonly observed in the diversion group. Percutaneous access gained by a radiologist (40% vs 0%, P<0.0001), second-look nephroscopy (36% vs 16%, P=0.0466), and an increase in the frequency of fever or sepsis (8% vs 0%, P=0.0387) were identified more frequently in the diversion group. CONCLUSIONS: Patients with upper tract calculi and urinary diversions are challenging to the endourologist because of anatomic factors that can make percutaneous access more difficult; ultrasonography-guided access can be helpful in this setting. Patients with urinary diversions can be treated as safely and effectively by PCNL as nondiverted 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".