4CPS-180 From evidence based medicine to practice: gum chewing for postoperative recovery of gastrointestinal function after colorectal surgery with interprofessional teamwork
Bibliographic record
Abstract
Background and importance Flatus is an important indicator of postoperative recovery of gastrointestinal function. Gum chewing is a cheap and simple intervention that mimics food intake to stimulate the vagus nerve and bowel movements. Aim and objectives To confirm the efficacy of gum chewing through an evidence approach and to implement this approach through interprofessional teamwork. Material and methods Evidence approach: setting the patient, intervention, comparison and outcome (PICO) to form a therapy question. In the Pubmed, Cochrane and Embase databases, using MeSH terms and Boolean logic combinations (chewing gum AND (colorectal surgery OR colostomy) AND postoperative ileus) for the literature search. Filters activated were randomised controlled trial (RCT), published from 2000 to 2018, in humans. Eleven RCTs were selected for review and showed a trend in improvement in the time to first flatus, starting feeding and discharge. Implementation we formed an interprofessional team including physicians, nurses, dieticians and pharmacists. The study involved 39 patients who underwent colorectal surgery between March and August 2018. In the gum chewing group, 19 patients took gum three times a day on the first day after surgery until the first flatus. Twenty patients who disagreed with gum chewing were in the control group. Evaluation of the findings was done with analysis of covariance (ANCOVA). Results Compared with the control group, the time to first flatus and the start of feeding were shorter in the gum chewing group (66.97±24.78 vs 54.82±19.74 hours and 91.53±51.41 vs 74.77±21.54 hours, respectively). However, the difference was not significant (p=0.166, 0.283). The time to discharge was significantly shorter in the gum chewing group (12.55±5.96 vs 9.16±1.71 days, p=0.047). Other influencing factors for the time to first flatus, start of feeding and discharge were analysed (eg, taking promotility agents, such as metoclopramide), but no significant differences were found between the two groups (p=0.375, 0.162, 0.960). Conclusion and relevance Could evidence based medicine lead to an equally satisfying practice? The implementation of the interprofessional team was essential (eg, the core physician team had not participated at the beginning and thus missed many possible cases). References and/or acknowledgements No conflict of interest.
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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 | 0.014 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.033 | 0.004 |
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".