Research Letter—Outcomes of Outpatient Native Kidney Biopsies at the McGill University Health Center: A Quality Assurance Audit
Bibliographic record
Abstract
Background: Percutaneous kidney biopsies are essential for diagnosis and management of kidney diseases. However, post-procedural bleeding is a significant risk associated with biopsies. At the McGill University Health Center, the 2 main hospitals, the Royal Victoria Hospital and the Montreal General Hospital, have different observation protocols for outpatient native kidney biopsies. Currently, patients are admitted for a 24-hour inpatient observation at the Montreal General Hospital, whereas patients biopsied at the Royal Victoria Hospital are discharged after 6 to 8 hours of observation at the end of the day. Most Canadian centers do not admit patients for an overnight observation, and it was unclear why this practice continued at the Montreal General Hospital. Objective: Our objective was to determine the incidence of complications post-renal biopsy over the past 5 years at both hospital sites, and compare them to each other, as well as to established rates in the available literature. Design: This assessment was designed as a quality assurance audit. Setting: This audit was conducted from a local registry of renal biopsies performed at the McGill University Health Center between January 2015 to January 2020. Patients: We included all adult patients (between the ages 18 and 80) with outpatient native kidney biopsies performed at the McGill University Health Center between 2015 and 2020. Measurements: We collected the included patients' baseline demographics and risk factors at the time of biopsy, including age, BMI, creatinine, estimated glomerular filtration rate, pre- and post-biopsy hemoglobin, platelet, urea, coagulation profile, blood pressure, kidney side/size as well as needle size, and number of passes made. Methods: We compared the incidence of both minor and major bleeding complications at the Montreal General and the Royal Victoria Hospital. Variables that were measured included hemoglobin before and after biopsy, incidence of minor bleeding complications (defined by hematomas and gross hematuria), and incidence of major complications (defined by post-biopsy bleeding requiring either transfusions or another procedure to stop the bleeding), as well as the incidence of admissions post-biopsy. Results: The incidence of major complications was 2.87% over 5 years (5/174 patients), which is comparable with that reported in the literature. Our transfusion incidence was 1.72% (3/174 patients) and our embolization incidence was 2.3% (4/174 patients) over the 5 study years. Our total number of major events was low and the patients who had major events had significant risk factors for bleeding. All events occurred within 6 hours of observation. Limitations: This was a retrospective study with a low event number. Additionally, since the events included only those recorded at the McGill University Health Center, it is possible that the events of interest may have occurred at other hospital sites without the author's knowledge. Conclusions: Based on the results of this audit, all major bleeding events occurred within 6 hours of a percutaneous kidney biopsy, suggesting that patients should be monitored for 6 to 8 hours following biopsy. The next step after this quality assurance audit is a quality improvement project and a cost-effectiveness analysis to assess whether post-biopsy practices should be amended at the McGill University Health Center.
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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 | 0.032 | 0.139 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".