Risk factors for infections after endoscopic retrograde cholangiopancreatography (ERCP): a retrospective cohort analysis of US Medicare Fee-For-Service claims, 2015–2021
Bibliographic record
Abstract
OBJECTIVE: Contaminated reprocessed duodenoscopes pose a serious threat to patients in the endoscopy unit. Despite manufacturer changes to reprocessing guidelines, 20% of reprocessed duodenoscopes meet criteria for quarantine-level contamination based on microbiological or ATP testing. We aimed to examine risk factors for postendoscopic retrograde cholangiopancreatography (ERCP) infection. DESIGN: Retrospective cohort analysis. SETTING: US Medicare Fee-For-Service claims (2015-2021) and all-payer data (2017). PARTICIPANTS: In the Medicare data, 823 575 ERCP procedures were included. The all-payer five-state data, 16 609 procedures were included. INTERVENTIONS: ERCP was identified by Current Procedural Terminology and International Classification of Disease (ICD) procedure codes. We identified inpatient infections using ICD diagnosis codes. OUTCOME MEASURES: A logistic regression model predicted risk factors for infections occurring within 7-day and 30-day periods following ERCP. 7-day and 30-day all-cause hospitalisations and post-ERCP pancreatitis were also examined. RESULTS: Post-ERCP infection occurred within 3.5% of 7-day and 7.7% of 30-day periods in Medicare. Disposable duodenoscopes were billed in 711 procedures, with 1.4% (n=10, 7-day) and 3.5% (n=25, 30-day) post-ERCP infections. Urgent ERCPs were the strongest risk factor for infections in the 7-day period (OR 3.3, 95% CI 3.2 to 3.4). Chronic conditions, sex (male), age (older) and race (non-white) were also risk factors. In the all-payer five-state data, fewer infections (2.4%, 7 days) were observed. No difference arose between Medicare and other payers for 7-day period infections (OR 1.0, 95% CI 0.7 to 1.3). CONCLUSIONS: Urgent ERCPs, patient chronic conditions and patient demographics are post-ERCP infection risk factors. Patients with infection risk factors should be targeted for specialised infection control prevention measures, including disposable duodenoscopes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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".