Periprocedural Anticoagulation Management of Patients Undergoing Colonoscopy with Polypectomy
Bibliographic record
Abstract
Abstract Introduction/Objective Colonoscopy with polypectomy is an integral component of colorectal cancer screening. There are limited data and consensus on periprocedural anticoagulation management, especially regarding bleeding risk with uninterrupted anticoagulation and thromboembolic risk with interruption. Our aim was to determine the incidence of bleeding and thromboembolic complications among colon screening participants undergoing colonoscopy following implementation of a novel patient care pathway for standardized periprocedural anticoagulation management. Methods We conducted a retrospective study including all participants (age 50–74) on an oral anticoagulant (e.g., vitamin K antagonists, direct oral anticoagulants) referred to the British Columbia Colon Screening Program for colonoscopy following abnormal fecal immunochemical test in a 6-month period (March–August 2022). Data relating to their specific periprocedural anticoagulant management and colonoscopy results including method of polypectomy were obtained. Primary outcomes were major bleeding and arterial or venous thromboembolic events from time of oral anticoagulant interruption until 14 days of postcolonoscopy. Secondary outcomes included nonmajor and minor bleeding, acute coronary syndrome, emergency room visit, hospital admission, and death due to any cause. Results Over the 6-month period, 162 participants completed standardized periprocedural anticoagulation management, colonoscopy ± polypectomy, and 14-day follow-up. One (0.6%) had a major bleeding event and one (0.6%) had an arterial thromboembolic event. Conclusions A novel patient care pathway for standardized periprocedural anticoagulation management with a multidisciplinary team is associated with low rates of major bleeding and thrombotic complications after colonoscopy with polypectomy.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".