Comparison of Yield and Complications between Pediatric Renal Biopsy Devices: A Retrospective Review
Bibliographic record
Abstract
Introduction: The purpose of this study was to perform a retrospective review comparing the yield and complications between the Bard Magnum and Merit Corvocet Automatic Biopsy Devices and investigate our hypothesis that the latter device would demonstrate greater yield and complications owing to its mechanism. Method(s): A total of 112 pediatric kidney biopsies for 99 patients were performed by interventional radiologists with real-time ultrasound guidance between 2017 and 2021. Sixty-eight and 44 biopsies were completed using the Bard and Corvocet devices, respectively, with 2 biopsies completed using both devices. The mean age, weight, and body mass index were 138.13 months, 46.09 kg, and 21.58 kg/m 2 , respectively. Fifty-seven biopsies corresponded to females. Patient data were extracted and compared using t -tests and chi-square tests. Result(s): The most common complication was a Hb drop (67.86%). Hematuria and Hb drop >15 g/dL were higher in the Corvocet group, X2 = 5.72, p = 0.017, and X2 = 4.61, p = 0.032. The mean number of cores and Hb drop in transplant kidney biopsies were higher in the Bard group, t (109) = 2.16, p = 0.033, and t (8) = 2.49, p = 0.038. Conclusion(s): This is the first study to compare these biopsy devices and report on the performance of the Corvocet device. These findings should be considered when evaluating renal biopsy device choice. Publication History Article published online: 09 February 2023 © 2023. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/) Thieme Medical and Scientific Publishers Pvt. Ltd. A-12, 2nd Floor, Sector 2, Noida-201301 UP, India
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".