Comprehensive assessment of the morbidity of renal mass biopsy: A population-based assessment of biopsy-related complications
Bibliographic record
Abstract
INTRODUCTION: We sought to assess seven-day and 30-day complications following renal mass biopsy (RMB), including mortality, hospitalizations, emergency department (ED) visits, and operative and non-operative complications and compare these to rates in population-matched controls. METHODS: We performed a population-based, matched, retrospective cohort study of patients undergoing RMB following consultation with a urologist and axial imaging from 2003-2015 in Ontario, Canada. Data on seven-day and 30-day rates of mortality, as well as operative and non operative complications after RMB were reported. The seven-day and 30-day rates of mortality, operative and non-operative interventions, hospitalizations, and ED visits were compared to matched controls using multivariable logistic regression. RESULTS: Among 6840 patients who underwent RMB in the study period, 24 (0.4%) and 159 (2.3%) died within seven and 30 days of their biopsy, respectively. Seven- and 30-day operative intervention rates were 79 (1.2%) and 236 (3.4%), respectively. Seven- and 30-day non-operative intervention rates were 227 (3.3%) and 529 (7.7%), respectively. Thirty-day mortality (odds ratio [OR] 8.1, 95% confidence interval [CI] 5.1-13.0), hospitalizations (OR 12.6, 95% CI 10.6-15.2), and ED visits (OR 3.8, 95% CI 3.4-4.3) were more common among patients who underwent RMB than the matched controls (p<0.001 for each). CONCLUSIONS: Patients undergoing RMB may have a small but non-negligible increased risk of mortality, hospital readmission, and ED visits compared to matched controls. However, limitations in the granularity of the dataset limits the strength of these conclusions. Further studies are needed to confirm our results. These risks should be discussed with patients for shared decision-making and considered in the risk/benefit tradeoff for the management of small renal masses.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".