A Brief History of the Surgery for Obesity to the Present, with an Overview of Nutritional Implications
Bibliographic record
Abstract
Massive obesity results in serious diseases, which are a major public health problem. Surgery is frequently the only means to achieve and sustain significant weight loss. This historical overview is aimed at providing knowledge and appreciation of this surgery to scientists in other complex areas of nutrition. The development of these operations is provided, including their potential nutritional sequelae. Because type 2 diabetes frequently improves or resolves postoperatively, related operations are being investigated in patients with lower weights.Key teaching points: Severe obesity is often resistant to conservative therapy.Operations providing weight loss via gastric restriction with early satiety or intestinal bypass with malabsorption have evolved over the past 50 years.These operations are now being performed laparoscopically rather than by an open approach.Among the obesity-related diseases that resolve with weight loss, type 2 diabetes (T2D) is of great importance, and bypass operations are being modified for T2D in patients with less obesity.Postoperative surveillance and multivitamin supplementation are necessary, especially for vitamin D, calcium, iron, B12, and folate.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".