Quality audit of colonoscopy reports amongst patients screened or surveilled for colorectal neoplasia
Bibliographic record
Abstract
AIM: To complete a quality audit using recently published criteria from the Quality Assurance Task Group of the National Colorectal Cancer Roundtable. METHODS: Consecutive colonoscopy reports of patients at average/high risk screening, or with a prior colorectal neoplasia (CRN) by endoscopists who perform 11 000 procedures yearly, using a commercial computerized endoscopic report generator. A separate institutional database providing pathological results. Required documentation included patient demographics, history, procedure indications, technical descriptions, colonoscopy findings, interventions, unplanned events, follow-up plans, and pathology results. Reports abstraction employed a standardized glossary with 10% independent data validation. Sample size calculations determined the number of reports needed. RESULTS: Two hundreds and fifty patients (63.2 ± 10.5 years, female: 42.8%, average risk: 38.5%, personal/family history of CRN: 43.3%/20.2%) were scoped in June 2009 by 8 gastroenterologists and 3 surgeons (mean practice: 17.1 ± 8.5 years). Procedural indication and informed consent were always documented. 14% provided a previous colonoscopy date (past polyp removal information in 25%, but insufficient in most to determine surveillance intervals appropriateness). Most procedural indicators were recorded (exam date: 98.4%, medications: 99.2%, difficulty level: 98.8%, prep quality: 99.6%). All reports noted extent of visualization (cecum: 94.4%, with landmarks noted in 78.8% - photodocumentation: 67.2%). No procedural times were recorded. One hundred and eleven had polyps (44.4%) with anatomic location noted in 99.1%, size in 65.8%, morphology in 62.2%; removal was by cold biopsy in 25.2% (cold snare: 18%, snare cautery: 31.5%, unrecorded: 20.7%), 84.7% were retrieved. Adenomas were noted in 24.8% (advanced adenomas: 7.6%, cancer: 0.4%) in this population with varying previous colonic investigations. CONCLUSION: This audit reveals lacking reported items, justifying additional research to optimize quality of reporting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".