Early outcome of bariatric surgery for the treatment of type 2 diabetes mellitus in super-obese Malaysian population
Bibliographic record
Abstract
INTRODUCTION: Despite many challenges, the benefit of bariatric surgery in super-obese population remains irrefutable with significant improvement in metabolic syndrome and quality of life. There are currently no published data from Malaysia on this topic. OBJECTIVE AND METHODOLOGY: A single-centre retrospective study aimed at analysing the outcome of laparoscopic bariatric surgery on super-obese Malaysians with type 2 diabetes mellitus (T2DM) at 12 months following surgery. Demographic details, glycaemic control and weight-loss parameters were analysed.P < 0.01 was considered statistically significant. RESULTS: . Majority of patients were of Malay ethnicity (82%). Malaysian-Indians and Malaysian-Chinese each accounted for 9% of total case volume. The three types of laparoscopic bariatric surgery recorded in this study were sleeve gastrectomy (82%), Roux-en-Y gastric bypass (9%) and mini-gastric bypass (9%) with operative time of 103.5 ± 31.1, 135.8 ± 32.6 and 116.2 ± 32.3 min, respectively. Percentage total body weight loss was 33.11% ± 9.44% at 12 months following surgery (P < 0.01). BMI change and percentage excess BMI loss showed similar improvement. Glycosylated haemoglobin and fasting blood sugar decreased from pre-operative values of 7.0% ± 1.0% and 7.0 ± 0.9 mmol/L to 5.6% ± 0.4% and 5.0 ± 0.6 mmol/L at 12 months (P < 0.01). Remission of T2DM was noted in 93% of patients. There was no correlation between weight loss and improvement in glycaemic status. CONCLUSION: There are significant weight loss and improvement of glycaemic control at 12 months post-laparoscopic bariatric surgery among super-obese Malaysians.
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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 | 0.001 |
| 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".