Visceral Organ-to-Percutaneous Tract Distance Is Shorter When Patients Are Placed in the Prone Position on Bolsters Compared with the Supine Position
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Percutaneous nephrolithotomy (PCNL) in the prone position is associated with a 0.1% risk of colon injury, yet there have not been any reported cases of colon injury with supine PCNL. The aim of the present study was to prospectively compare CT scans of patients performed in both supine and prone positions on bolsters. PATIENTS AND METHODS: Sixteen consecutive patients (mean age 55, 12 men) with 19 renal units (3 bilateral) who presented for PCNL underwent preoperative supine (without bolsters) and prone (with bolsters) noninfused CT scans. Axial images through lower pole calices containing stones necessitating percutaneous access were then analyzed. Percutaneous access was planned based on both supine and prone CT scans. Skin-to-stone distance (cm), angle of the percutaneous tract to the anterior-posterior axis (degrees), and visceral organ-to-tract distance (cm) were measured. RESULTS: Visceral organ-to-tract distance was significantly shorter in the prone position when compared with the supine position (2.8 cm vs 3.5 cm, P=0.04). In three renal units, visceral organ-to-tract distance in the prone position was less than 0.4 cm. Furthermore, the prone position was associated with significantly shorter skin-to-stone distance (7.6 cm vs 9.0 cm, P=0.0005) and significantly wider angles (40 degrees vs 35 degrees, P=0.02). Small sample size and simulation of the percutaneous access tract are two limitations of the present study. CONCLUSIONS: When prone PCNL is contemplated, preoperative planning CT scans that are performed in the prone position with bolsters provide better preoperative assessment of colon-to-percutaneous renal tract distance.
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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 | 0.000 | 0.001 |
| 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) | 0.003 | 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".