Risk Factors and Timing of Native Kidney Biopsy Complications
Bibliographic record
Abstract
BACKGROUND: The appropriate observation period, rate and risk factors of complications after a percutaneous renal biopsy remain debated. METHODS: We retrospectively studied native kidney biopsies performed in our institution between January 2007 and July 2011. Outpatients had either an 8- (67%) or a 24-hour (33%) observation period. RESULTS: 312 biopsies were reviewed (287 patients), 51% of patients were female and the mean age was 54 ± 15 years. Half of these biopsies were performed in outpatients. A total of 15% of patients developed a symptomatic hematoma, 9% received a red blood cell transfusion and 1% required an angio-intervention. Eighty-four percent of the complications manifested within the first 8 h, 86% at 12 h and 94% at 24 h. Outpatients experienced significantly less complications, all manifesting within the first 8 h, 14% required an observation period longer than planned. The risk of symptomatic hematoma increased to 11, 20, 35 and 40% in patients with >200, 140-200, 100-140 and <100 × 10(9)/l platelets, respectively (p = 0.002). It also increased in hemodialysis patients (29% compared to 14%, p = 0.02). We found no association of risk with the number of biopsy passes and only a trend with needle size. CONCLUSION: Symptomatic hematomas occurred in 15% of kidney biopsies and were strongly associated with platelet count and hemodialysis. Outpatients experienced fewer complications; therefore, we can conclude that same-day discharge in selected patients is safe.
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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 | 0.006 |
| 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 | 0.000 |
| Research integrity | 0.000 | 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".