Comparison of Supracostal <i>Versus</i> Infracostal Percutaneous Nephrolithotomy Using the Novel Prone-Flexed Patient Position
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Percutaneous nephrolithotomy (PCNL) is considered standard therapy for large and complex renal calculi. The optimal patient position and puncture site for collecting system access remains controversial. This purpose of this retrospective review is to analyze our PCNL series with respect to puncture tracts, success, and complications using our novel prone-flexed position. PATIENTS AND METHODS: Perioperative data were collected on consecutive PCNL cases for renal calculi performed in the prone-flexed position from 2004 to 2009. Patient demographic, stone, operative, postoperative, and follow-up data were collected. Successful treatment was defined as stone free or sandlike (≤1 mm) particles visible on CT scan at 3 months. RESULTS: A total of 318 patients, with a mean age of 52.9 years and body mass index of 27.8 kg/m(2), underwent PCNL in the prone-flexed position (57.9% male). Sixteen tracts were above the 11th rib, 138 were above the 12th rib, and 164 were infracostal. Multiple tracts were used in 16 patients. There were no significant differences between patients undergoing supracostal vs infracostal puncture with respect to side, stone area, number of tracts, number of stones, or the presence of staghorn or struvite calculi. Success in the supracostal group (89.8%) was not statistically different from the infracostal group (94.1%), P>0.05. Overall complication rates across groups was low (11.6%), with a significant difference in complications between the supracostal and infracostal puncture groups across Clavien grades, P<0.01. No patients needed blood transfusions or angioembolization. CONCLUSION: Regardless of supracostal or infracostal renal access, our novel prone-flexed position assists with percutaneous renal access and ease of nephrolithotomy, while maintaining excellent success rates and minimizing procedural morbidity.
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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 | 0.000 | 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) | 0.001 | 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".