Direction of the Biopsy Needle in Ultrasound-Guided Renal Biopsy Impacts Specimen Adequacy and Risk of Bleeding
Bibliographic record
Abstract
INTRODUCTION: Although medical factors such as hypertension and coagulopathy have been identified that are associated with hemorrhage after renal biopsy, little is known about the role of technical factors. The purpose of our study was to examine the effects of biopsy needle direction on renal biopsy specimen adequacy and bleeding complications. METHODS: Two hundred and forty-two patients who had undergone ultrasound-guided renal biopsies were included. A printout of the ultrasound picture taken at the time of the biopsy was used to measure the biopsy angle ("angle of attack" [AOA]) and to determine if the biopsy needle was aimed at the upper or lower pole and if the medulla was targeted or avoided. RESULTS: Of the 3 groups of biopsy angle, an AOA of between 50°-70° yielded the most glomeruli per core (P = .001) and the fewest inadequate specimens (4% vs 15% for > 70°, and 9% for < 50°, P = .038). Biopsy directed at a pole vs an interpolar region resulted in fewer inadequate specimens (8% vs 23%, P = .005), while biopsies that were medulla-avoiding resulted in fewer inadequate specimens (5% vs 16%, P = .004) and markedly reduced bleeding complications (12% vs 46%, P < .001) compared to biopsies where the medulla was entered. DISCUSSION: An AOA of approximately 60°, aiming at the poles, and avoiding the medulla were each associated with fewer inadequate biopsies and bleeding complications. While biopsy of the medulla is necessary for some diagnoses, the increased bleeding risk emphasizes the need for communication between nephrologist, pathologist, and radiologist.
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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 | 0.002 | 0.011 |
| 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".