Safety and utility of kidney biopsy in patients with estimated glomerular filtration rate < 30 <scp>ml/min/1.73 m<sup>2</sup></scp>
Bibliographic record
Abstract
Abstract Aim Kidney biopsy (KBx) is the gold standard for evaluation of kidney disease, but is associated with a higher risk of complications in patients with reduced glomerular filtration rate (GFR). We studied the safety and utility of KBx in patients with eGFR <30 ml/min/1.73 m2. Methods Consecutive adult patients with eGFR <30 ml/min/1.73 m2, who were planned for a KBx and consented to participate were prospectively enrolled. Patients with solitary/transplant kidney or acute kidney injury were excluded. Haemoglobin was checked on the day of KBx and repeated 18–24 h later along with a screening ultrasound. Post‐KBx complications were noted and their risk‐factors analysed. The utility of the KBx was graded as effecting significant, some, or no change to subsequent management. Results Of the 126 patients included, 75% were male, 27.7% were diabetic, and the median eGFR was 13.5 ml/min/1.73m2. Major complications occurred in 5.6%. Peri‐renal haematomas were detected in 37.3%, and haematomas ≥2 cm were significantly more frequent in those with eGFR <15 ml/min/1.73 m2 (29.2% vs. 13%, p = .032). Dialysis was a risk factor, while pre KBx blood transfusion, diabetes and higher serum albumin were protective against any complication. KBx was more likely to make a significant difference in management in those with eGFR 15–29 ml/min/1.73m2 (44.1% vs. 11.1%, p < .001). Increasing age, lower serum creatinine and albumin were independently associated with KBx utility. Conclusion KBx is relatively safe in severe kidney disease but its risk to benefit balance needs to be carefully considered when eGFR is <15 ml/min/1.73m2.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".