Age Is the Only Predictor of Poor Bowel Preparation in the Hospitalized Patient
Bibliographic record
Abstract
Purpose: Poor bowel preparation leads to a need for repeated colonoscopy procedures, with resultant increased length of stays and health care costs. Few investigators have assessed these outcomes in hospitalized patients. Given these considerations, we sought to examine the prognosticating value of several key clinical variables on the likelihood of inpatient poor bowel preparation for colonoscopy. Methods: The records of consecutive patients who underwent colonoscopy at our institution between January 1, 2006 and December 31, 2011 during hospitalization were retrospectively extracted from a dedicated electronic digestive endoscopic institutional database (Endoworks, Olympus, Center Valley, PA). Six individuals independently reviewed hospital charts with 10% of all entered data audited for validation by a separate data entry associate. Univariable and multivariable analyses using logistic regression were carried out assessing clinical variables assumed to possibly be predictive of a poor colonic preparation including gender, use of narcotics, heavy medication burden, comorbidities, history of previous abdominal surgery, marital status, patient with diabetes or a neurological disorder such as stroke, hemiplegia or dementia, as well as product used for bowel preparation and whether or not the bowel regimen was given as split or standard dose as well as time of endoscopy. Data collection and analyses were undertaken following approval and institutional oversight by the Institutional Review Board for the Protection of Human Subjects. Results: Overall, 244 charts of patients undergoing colonoscopy during a hospitalization were assessed. Of those, 83 (34%) patients had poor bowel preparation. During endoscopic examination, the cecum was reached in 193 patients (79.1%). The mean age of the patients was 66 years, 133 were men (54.5%). In univariable analyses, the only clinical variable associated with a poor bowel preparation was advancing age (OR=1.03, 95% CI 1.01 to 1.05, p=0.002). In multivariable logistic regression analyses, it remained independently and significantly predictive (OR=1.026, 95% CI 1.006 to 1.045, p=0.008). Conclusion: In this retrospective cohort analysis, age was found to be the only independent significant predictor of poor bowel preparation amongst hospitalized patients. Further studies are required to help identify and correct factors causing poor bowel preparation in the admitted patient.
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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 | 0.005 |
| 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) | 0.002 | 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".