Bibliographic record
Abstract
Obesity is a global epidemic associated with many comorbidities and mortality with over 24% of the Canadian population classified as obese. Even more alarming is the rapid rise in severe obesity with a prevalence that has more than tripled in Canada. While diet, exercise and more recently, pharmaceutical treatments are well-known options for weight loss, bariatric surgery (surgical weight loss) has become the best treatment option for this population. The surgery not only results in weight loss but also in improvements of comorbidities and mortality. Unfortunately, these results post-surgery plateau after 2 years and some patients show a regain of lost weight in the long-term.Long-term weight loss maintenance after bariatric surgery is critical to maintain the benefits associated with the surgery. However, studies assessing the weight loss results of bariatric surgery are often limited to reporting total body weight loss, or specific tissue changes with limited pre-surgery values, due to the size and weight limitations of body composition assessment methods. Being able to precisely measure and understand the specific tissue changes following bariatric surgery are important since lean tissue and optimal functional body composition are well known for maintaining long-term health and quality of life. Therefore, this dissertation involves a series of investigations that address measurement issues with assessing body composition in severely obese individuals, thus allowing for longitudinal assessment of specific tissue changes and specific regional body composition assessment in bariatric patients who have regained their lost weight in the long-term.The first three investigations presented in this dissertation focused on determining whether the latest technology in assessing regional body composition (Lunar iDXATM, GE Healthcare) was able to precisely measure severely obese individuals. It was determined to have excellent precision for the measurement of lean tissue, fat tissue, bone mineral density, and visceral adipose tissue; thus allowing for the precise assessment of body composition changes with the iDXATM. Therefore, the fourth investigation was undertaken by longitudinally tracking and assessing patients during the first year post-surgery, which resulted in, not only significant losses in fat tissue, but also in metabolically active lean tissue and bone mineral density. In addition, given the significant loss of lean tissue following bariatric surgery and its known association to physical function, a final investigation was designed in order to have a deeper understanding of long-term results on functional body composition. This final investigation provided insight into the longer-term impact of bariatric surgery and major weight loss (and possible weight regain) on lean tissue mass, muscle quality of the thigh, mechanical efficiency, and physical activity levels; using a cross-sectional design of bariatric patients 10 years following surgery.This dissertation fills important gaps in the scientific literature in several ways. First, it provides evidence that the iDXATM can be used to precisely assess changes in body composition in severely obese individuals, as well as measures of specific regional body composition in this population. Second, it provides the important results that with the significant amount of fat tissue lost following surgery, bariatric patients also lose significant amounts of lean tissue in the first three months, and BMD decreases throughout the 1st year post-surgery. Finally, this dissertation includes the first known study to examine functional body composition using the iDXATM in bariatric patients 10 years post-surgery. The results of this dissertation demonstrate the usefulness of the iDXATM as a new and precise way to track body composition with the additional feature of specific regional assessment which gives clinicians important insights into tissue markers of severely obese individuals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".