Time Interval Between Purgative Completion and Colonoscopy Start Time Is an Independent Predictor of Bowel Preparation Quality Among Hispanic Patients at a Large County Hospital
Bibliographic record
Abstract
Purpose: Risk factors for poor bowel preparation (BP) quality among Hispanic patients in the United States have not been well studied. The objective of our study was to identify the risk factors for poor BP quality among Hispanic patients at our hospital. Methods: We prospectively collected data on 161 Hispanic outpatients undergoing surveillance or diagnostic colonoscopies at a large county hospital from January 2011 to April 2011. All patients received a split-dose polyethylene glycol-based regimen to be completed within two hours of their appointment time. Data on patient demographics, time of purgative completion, colonoscopy start time, and BP quality were collected. Our primary outcome was BP quality, measured using the Ottawa Bowel Preparation Scale (0 to 14). Inadequate bowel preparation was defined as an Ottawa score ≥ 8. Univariate analysis was performed for each risk factor. Factors with a p-value <0.20 was included in a stepwise logistic regression model to identify independent risk factors for poor BP quality. Results: The mean age of the 161 Hispanic patients was 55±8 and 65% were female. The risk factors with p-value <0.20 are listed in the table. Stepwise logistic regression identified the time interval between last purgative dose to procedure start time as the only significant independent risk factor for inadequate BP quality (adjusted OR 2.47; 95% CI: 1.10, 5.56; p=0.028). Conclusion: Our finding suggests that the optimal time interval between completion of purgative and procedure start time is less than 8 hours prior to colonoscopy. Improving compliance with the split-dose bowel preparation regimen appears to be an important quality improvement goal for this patient population.Figure: No Caption available.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".