Utilization rates, complications and costs of percutaneous liver biopsy: a population‐based study including 4275 biopsies
Bibliographic record
Abstract
BACKGROUND: Liver biopsy is an important tool in the management of patients with liver disease. Because biopsy practices may be changing, we studied patterns of use in a large Canadian Health Region. We aimed to describe trends in biopsy utilization and the incidence and costs of complications from a population-based perspective. METHODS: Administrative databases were used to identify percutaneous liver biopsies performed between 1994 and 2002. Significant complications were identified by reviewing medical records of patients hospitalized within 7 days of a biopsy and those with a diagnostic code indicative of a procedural complication. Analyses of biopsy rates employed Poisson regression. RESULTS: Between 1994 and 2002, 3627 patients had 4275 liver biopsies (median 1 per patient; range 1-12). Radiologists performed the majority (90%), particularly during the latter years (1994 vs. 2002: 73 vs. 98%; P<0.0001). The overall annual biopsy rate was 54.8 per 100 000 population with a 41% (95% CI 23-61%) increase between 1994 and 2002. Annual increases were greatest in males and patients 30-59 years. Thirty-two patients (0.75%) had significant biopsy-related complications (1994-1997 vs. 1998-2002: 1.28 vs. 0.44%; P=0.003). Pain requiring admission (0.51%) and bleeding (0.35%) were most common. Six patients (0.14%) died; all had malignancies. The median direct cost of a hospitalization for complications was $4579 (range $1164-29 641). CONCLUSIONS: Liver biopsy rates are increasing likely owing to the changing epidemiology and management of common liver diseases. The similarity of the complication rate in our population-based study with estimates from specialized centres supports the safety of this important procedure.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| 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".