IMPROVEMENT OF GLYCEMIC CONTROL IN PREDIABETIC AND TYPE 2 DIABETIC PATIENTS UNDERGOING LAPAROSCOPIC SLEEVE GASTRECTOMY (LSG) IN NEWFOUNDLAND AND LABRADOR
Bibliographic record
Abstract
Introduction Newfoundland and Labrador (NL) has the highest prevalence of diabetes in the country. In 2011, 11.1% of the population were identified as diabetic. LSG is a minimally invasive and irreversible procedure in which 80% of the stomach is removed, leaving a much smaller stomach or “sleeve”. It is a promising treatment option for obesity, and recent studies demonstrate that LSG may be effective in improving/resolving T2DM in obese patients. Objectives This study is evaluating LSG and its effectiveness in the improvement of glycemic control in prediabetes or type 2 diabetes mellitus (T2DM). Methods All patients (n=66) undergoing LSG in NL since May 2011 are followed prospectively. Patients are classified as having prediabetes (HbA1c: 5.7–6.4% or FPG: 6.1–6.9 mmol/L) or T2DM (HbA1c>6.5% or FPG≥7.0 mmol/L, self-reported, or antidiabetic medication use) at baseline. Glycemic control is evaluated at 3, 6, and 12 months. The primary outcome is the proportion of patients experiencing improved glycemic control. Results At baseline, 16 (24.2%) patients have prediabetes (average HbA1c 5.8% (SD 0.3), FPG 5.6 mmol/L (SD 0.7)) and 31 (47.0%) have T2DM (average HbA1c 7.6% (SD 1.4), FPG 8.1 mmol/L (SD 2.5)). Interim analysis within 6 months post-surgery: of the 11 prediabetic patients who've completed follow-up, 8 (72.7%) have HbA1c<5.7% (p=0.004) and 11 (100%) FPG<6.1 mmol/L; of T2DM patients who've completed follow-up, 12 of 19 (63.2%) have HbA1c<6.5% (p<0.001) and 14 of 17 (82.4%) have FPG<7.0 mmol/L (p=0.003). Prediabetes and T2DM groups show significant improvements in HbA1c (-0.6% and -1.5% respectively) and FPG (-1.0 mmol/L and -2.0 mmol/L respectively), p<0.001 for all. 9 of 21 T2DM patients (42.9%) who completed follow-up are no longer taking antidiabetic medications. Conclusions Interim analysis indicates better glucose control is achieved within 6 months following LSG.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".