Platelet and INR Thresholds and Bleeding Risk in Ultrasound Guided Percutaneous Liver Biopsy: A Before-After Implementation of the 2019 Society of Interventional Radiology Guidelines Observational Quality Improvement Study
Bibliographic record
Abstract
Purpose: To evaluate if implementation of the 2019 Society of Interventional Radiology (SIR) guidelines for periprocedural management of bleeding risk in patients undergoing percutaneous ultrasound guided liver biopsy is associated with increased haemorrhagic adverse events, change in pre-procedural blood product utilization, and evaluation of guideline compliance rate at a single academic institution. Methods: Ultrasound guided percutaneous liver biopsies from (January 2019-January 2023) were retrospectively reviewed (n = 504), comparing biopsies performed using the 2012 SIR pre-procedural coagulation guidelines (n = 266) to those after implementation of the 2019 SIR pre-procedural guidelines (n = 238). Demographic, preprocedural transfusion, laboratory, and clinical data were reviewed. Chart review was conducted to evaluate the incidence of major bleeding adverse events defined as those resulting in transfusion, embolization, surgery, or death. Results: Implementation of the 2019 SIR periprocedural guidelines resulted in reduced guideline non-compliance related to the administration of blood products, from 5.3% to 1.7% ( P = .01). The rate of pre-procedural transfusion remained the same pre and post guidelines at 0.8%. There was no statistically significant change in the incidence of bleeding adverse events, 0.8% pre guidelines versus 0.4% post ( P = 1.0). Conclusion: Implementation of the 2019 SIR guidelines for periprocedural management of bleeding risk in patients undergoing percutaneous ultrasound guided liver biopsy did not result in an increase in bleeding adverse events or pre-procedural transfusion rates. The guidelines can be safely implemented in clinical practice with no increase in major adverse events.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".