Fecacrit: Validation of a Novel and Objective Tool for the Evaluation of High Quality Bowel Preparations: 2017 Presidential Poster Award
Bibliographic record
Abstract
Introduction: Bowel preparation is an important quality indicator in colonoscopy. Validated scales suffer from low concordance and intra-and inter-observer variability. Adenoma detection rates (ADR) are reported to be similar between fair, good and excellent preparations. Aims: To develop and validate a new objective method for assessing high-quality bowel preparation and examine variability in ADR according to quality of preparation. Methods: Ambulatory patients undergoing screening or surveillance colonoscopy were enrolled. Exclusion criteria were presence of thick non-suctionable debris, incomplete exam, IBD or prior colon surgery. All residual fluid was suctioned during the insertion phase (with no washing). Upon reaching the cecum, 10 mL was sampled, centrifuged and fecacrit (% pellet over supernatant) measured. The endoscopist scored the preparation using the Aronchick, Ottawa, and Boston scales (BBPS). Statistical analysis included the Kruskal-Wallis, pairwise comparison analysis and Mann-Whitney U tests. ROC curves were created to select appropriate cut-off values of fecacrit indicative of high-quality preparations on the above scales (excellent/good for Aronchick, Ottawa ≤7, or BBPS ≥6). Results: 197 patients were enrolled and corresponding samples collected, 80 for derivation and 117 for validation. Preparations were high-quality in 80.2% and fair in 19.8% of patients on the Aronchick scale with a median %fecacrit of 1.70 (IQR 1.0-2.63) and 4.00 (IQR 2.50-7.50) respectively (p < 0.001). Fecacrit distributions were also significant on Ottawa and Boston scales (p < 0.0001). ADR was significantly superior in high-quality vs. fair preparations on the Aronchick (53.2% vs. 25.6%, p=0.002), Ottawa (51.6% vs. 32.5%, p=0.03) and BBPS (51.6% vs. 30.6%, p=0.023). Median adenoma per colonoscopy (APC) was also superior in high-quality vs. fair preparations on all scales (1.0, IQR 0.0-2.0 vs. 0.0, IQR 0.0-1.0 respectively, p=0.026). ROC curves generated using derivation sample were validated using cutoff of < 2.75% to indicate high-quality preparations (Aronchick scale: AUC 0.796, sensitivity 75.3%, specificity 71.8% and PPV 91.5%). Conclusion: Fecacrit is a new objective and sensitive tool of bowel preparation quality. Although impractical in practice, it may be useful when developing or comparing purgatives aiming at high-quality preparations. Using this highly objective measure, we show that fair preparations are associated with significantly lower adenoma detection.
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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".