220 A Systematic Review on Under-Recognized Condition: Duodenogastric Reflux After Cholecystectomy
Bibliographic record
Abstract
Abstract Aim About 66,660 cholecystectomies are performed yearly in the UK. Dissatisfaction rates following surgery range from 7-41% and abdominal pain can persist post-operatively in 33% of cases according to literature. Duodenogastric reflux (DGR) has been suggested as a cause of persistent symptoms after cholecystectomy. Our study was the first systematic review to assess the DGR after cholecystectomy. Method Medline, Embase, and Cochrane were searched by two independent researchers up to June 2022. Eligible studies were appraised on correlation between DGR and post-cholecystectomy symptoms as well as on how DGR was diagnosed and managed. Results Initial 379 records were identified and screened leaving 11 papers in total. Out of included papers (2013-2022) studying 1334 patients from seven different countries, there were 2 randomised controlled trials (RCT) and 9 observational studies. The average Newcastle-Ottawa scale for observational studies was 6. Included RCTs had low to some risks of bias. Only 1 study could correlate between DGR and post-cholecystectomy symptoms. Six studies identified alkaline reflux and gastritis with combined investigations after cholecystectomies. The gold-standard investigation was yet to be identified although gastroscopy was commonly used. Single or combined medications were better than no treatment for DGR. Conclusions DGR induced gastritis was confirmed with investigations in this study. However, further research is required to prove extensive DGR related symptoms after cholecystectomy. There were limitations such as having more observational studies than RCT and having small samples in some studies. More substantial studies with great randomization and longer duration of follow up are recommended for future studies.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.001 | 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) | 0.000 | 0.001 |
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".