A324 FOUR OR MORE EUS-FNA PASSES FOR PANCREATIC SOLID LESIONS IS ASSOCIATED WITH INCREASED RISK WITHOUT IMPROVING DIAGNOSTIC YIELD: RESULTS FROM THE OTTAWA HOSPITAL EUS RYSE QA INITIATIVE
Bibliographic record
Abstract
Endoscopic ultrasound (EUS) is an established procedure for the investigation of the gastrointestinal and hepatobiliary systems. Due to study limitations such as small sampling and data quality, adverse events (AEs) related to EUS procedures may be underreported. Further the relationship between EUS-FNA diagnostic yield and adverse event risk has not previously been described. To examine risk factors associated with AEs from EUS procedures performed at The Ottawa Hospital (TOH). A retrospective chart-review of all EUS cases was performed from September 2009 until August 2015. AEs considered a priori included perforation, bleeding, infection, aspiration and pneumonia. All patient encounters to the emergency department and/or hospitalizations within 30 days of the EUS procedure were reviewed. Each possible AE case was reviewed by three of the authors (MA, PJ, AC) to determine the likelihood that the event was related to the EUS procedure. The TOH AE Database was then merged with the TOH EUS Procedure Database to examine patient and procedure factors associated with AE risk. 1,389 procedures were included. 663 (48%) EUS procedures were performed on women. 44 possible or definite adverse events related to EUS procedures were identified (3.2%) and 28 (2%) resulted in hospitalization. Infection (n=7), abdominal pain (n=6), pancreatitis (n=5), bleeding (n=5) were identified AEs. The risk of EUS alone was 0.9% which increased to 1.8% when an FNA was performed. Cases involving anesthesia support were more likely to result in AEs (5.4%) vs 2.7% for non-anesthesia cases. The presence of an advanced endoscopy fellow was associated with an increased risk of AEs 23 (3.8%) vs 2.3% when a fellow was not present). For EUS-FNA of solid pancreatic tumours, AE risk increased with the number of passes performed: 0% AEs with 2 or less passes, 2% with 3 passes and 5% when 4 or more passes were performed. We have previously shown that performing more than 4 passes is not associated with increased diagnostic yield. This is the largest EUS-related adverse event study performed in Canada to date. Anesthesia assistance, the presence of a fellow in training and performing an FNA increase the overall risk of AEs. Performing four or more FNA passes may subject the patient to increased risk without increasing diagnostic yield. None
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".