A Systematic Review and Meta-Analysis of Outcomes for Type 1 Diabetes after Bariatric Surgery
Bibliographic record
Abstract
Background. The utility of bariatric surgery in type 1 diabetes remains controversial. The aim of the present study is to evaluate glycemic control outcomes in obese patients with type 1 diabetes after bariatric surgery. Methods. A comprehensive search of electronic databases was completed. Inclusion criteria included human adult subjects with BMI ≥35 kg/m(2) and a confirmed diagnosis of type 1 diabetes who underwent a bariatric surgical procedure. Results. Thirteen primary studies (86 patients) were included. Subjects had a mean age of 41.16 ± 6.76 years with a mean BMI of 42.50 ± 2.65 kg/m(2). There was a marked reduction in BMI postoperatively at 12 months and at study endpoint to 29.55 ± 1.76 kg/m(2) (P < 0.00001) and 30.63 ± 2.09 kg/m(2) (P < 0.00001), respectively. Preoperative weighted mean total daily insulin requirement was 98 ± 26 IU/d, which decreased significantly to 36 ± 15 IU/d (P < 0.00001) and 42 ± 11 IU/d (P < 0.00001) at 12 months and at study endpoint, respectively. An improvement in HbA1c was also seen from 8.46 ± 0.78% preoperatively to 7.95 ± 0.55% (P = 0.01) and 8.13 ± 0.86% (P = 0.03) at 12 months and at study endpoint, respectively. Conclusion. Bariatric surgery in patients with type 1 diabetes leads to significant reductions in BMI and improvements in glycemic control.
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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 | 0.015 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.030 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".