Impact of weight gain on outcomes in type 2 diabetes
Bibliographic record
Abstract
BACKGROUND: The majority of patients with type 2 diabetes mellitus (T2DM) are overweight or obese. Obesity is a significant risk factor for increased morbidity and mortality in people with T2DM, and increased weight has been shown to worsen glycemic control and increase the risk of diabetes progression. METHODS: A search was conducted of the National Library of Medicine (PubMed) for articles published from 1990 to 2009 about the treatments of T2DM, relationship between T2DM and weight gain, obesity-related comorbidities of T2DM, and T2DM therapies associated with increased weight. Reference lists of retrieved articles were reviewed for additional publications. FINDINGS: Results from large, prospective clinical trials have shown that weight reduction significantly improves glycemic control and blood pressure in T2DM patients and lowers the risk of progression of T2DM as well as CV disease and cancer. Treatment-related weight gain is a side effect of many oral antidiabetes agents and insulin. The thiazolidinediones (TZD), sulfonylureas, and glinides are associated with weight gain. Despite the weight gain, TZDs also redistribute fat from the central to peripheral compartments, which may lead to a beneficial effect on insulin resistance. Among insulin products, the basal insulin analog detemir is typically associated with a smaller weight increase than human insulin and insulin analog preparations, including glargine, biphasic, and prandial insulin regimens. Alpha-glucosidase inhibitors and dipeptidyl peptidase-4 inhibitors are weight neutral, whereas glucagon-like peptide1-R agonists and metformin are associated with weight loss. DISCUSSION: An effective approach to management of the obese patient with diabetes is to communicate the significant benefits of a 1 kg reduction in body weight or prevention of weight gain on glycemic control and reduced morbidity and mortality. LIMITATION: This article is based on an extensive literature review rather than the prospective studies needed to define further the effect of weight gain on the management of T2DM. CONCLUSION: Weight management should be an integral part of a T2DM treatment strategy that includes selecting oral antidiabetes medications and insulin products that are weight beneficial.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".