OAGB with shortened excluded ileal loop as an effective treatment for type 2 diabetes mellitus in the cases of Caucasian Men and Women with obesity of the first degree (BMI 30-35 kg/m2)
Bibliographic record
Abstract
Abstract Introduction: The aim of the study is to assess long-term results of surgical treatment (One Anastomosis Gastric Bypass) of type 2 diabetes in patients with Io obesity. Material and Methods: The study included 25 patients with BMI 30-35 kg / m2 and diagnosed diabetes mellitus type 2 undergoing OAGB with excluded 150 cm of the small intestine (this is one of the innovative elements of this work).Results: There were no: deaths in the study group, bleeding during the postoperative period requiring reoperation, anastomotic leak/leakage of mechanical stitching. The mean HbA1C level 12 months after surgery is 6.16 ± 0.96%, the decrease was 2.29 ± 3.3%. In more than 85% of patients taking insulin before surgery, it was discontinued in the postoperative period. Additionally, the level of glycaemia was assessed in patients on the day of surgery (163 ± 58 mg%) and on the day of discharge from the hospital (4.7 ± 1.3 day) - it was lower by over 18% (133 ± 39.2 mg). Over the period of 12 months following OAGB: reduction in the mean BMI value from 33.5 ± 2 kg / m2 to 25.5 ± 2.5 kg / m2, improvement in lipid parameters and mean values of blood pressure.Conculsion: OAGB with excluded 150 cm of the small intestine has beneficial effect on resolution of T2DM in patients with BMI of 30-35kg/m2 and is associated with an acceptable level of complications. Achieved weight loss after surgery is satisfactory.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".