The Newfoundland and Labrador Bariatric Surgery Cohort Study: Rational and Study Protocol
Bibliographic record
Abstract
In Canada, there has been a disproportionate increase in adults with Class II (BMI 35.0–39.9 kg/m 2 ) or Class III obesity (BMI ≥ 40 kg/m 2 ) affecting 9 % of Canadians with increases projected. Individuals affected by severe obesity (BMI ≥ 35) are at increased risk of high blood pressure, cardiovascular disease, diabetes, cancer, impaired quality of life, and premature mortality. Bariatric surgery is the most effective treatment for severe obesity. Laparoscopic sleeve gastrectomy (LSG), a relatively new type of bariatric surgery, is growing in popularity as a treatment. The global prevalence of LSG increased from 0 to 37.0 % between 2003 and 2013. In Canada and the US, between 2011 and 2013, the number of LSG surgeries increased by 244 % and LSG now comprises 43 % of all bariatric surgeries. Since 2011, Eastern Health, the largest regional health authority in Newfoundland and Labrador (NL), Canada has performed approximately 100 LSG surgeries annually. A population-based prospective cohort study with pre and post surgical assessments at 1, 3, 6, 12, 18, 24 months and annually thereafter of patients undergoing LSG. This study will report on short - to mid-term (2–4 years) outcomes. Patients ( n = 200) followed by the Provincial Bariatric Surgery Program between 19 and 70 years of age, with a BMI between 35.0 and 39.9 kg/m 2 and an obesity-related comorbidity or with a BMI ≥ 40 kg/m 2 are enrolled. The study is assessing the following outcomes: 1) complications of surgery including impact on nutritional status 2) weight loss/regain 3) improvement/resolution of comorbid conditions and a reduction in prescribed medications 4) patient reported outcomes using validated quality of life tools, and 5) impact of surgery on health services use and costs. We hypothesize a low complication rate, a marked reduction in weight, improvement/resolution of comorbid conditions, a reduction in related medications, improvement in quality of life, and a decrease in direct healthcare use and costs and indirect costs compared to pre-surgery. Limited data on the impact of LSG as a stand-alone procedure on a number of outcomes exist. The findings from this study will help to inform evidence-based practice, clinical decision-making, and the development of health policy.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
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".