One-Year Lifestyle Intervention, Muscle Lipids, and Cardiometabolic Risk
Bibliographic record
Abstract
PURPOSE: Low-attenuation muscle (LAM) area at mid-thigh, a computed tomography (CT)-derived index of intramuscular lipids, is associated with insulin resistance, obesity, and type 2 diabetes. The present study aimed at testing the hypothesis that changes in LAM area in trunk muscles from a single abdominal scan could provide relevant information to evaluate the effects of a lifestyle intervention without the use of a mid-thigh CT scan. METHODS: Cardiometabolic risk variables, including waist circumference, lipoprotein-lipid profile, glucose tolerance, and cardiorespiratory fitness, were assessed in a sample of 102 dyslipidemic viscerally obese men at baseline and after a 1-yr lifestyle intervention. Abdominal (L4-L5) and mid-thigh CT scans were performed and abdominal muscles classified as psoas and core muscles. Scans were segmented to calculate muscle areas, LAM areas, and mean attenuation values. RESULTS: All muscle groups showed a decrease in LAM areas (P < 0.0001) in response to the lifestyle intervention. Changes in LAM areas were significantly associated with changes in triglycerides, high-density lipoprotein (HDL) cholesterol, cholesterol/HDL cholesterol ratio and log triglycerides/HDL cholesterol ratio (mid-thigh, 0.20 ≤ |r| ≤ 0.29; psoas, 0.28 ≤ |r| ≤ 0.38; core, 0.29 ≤ |r| ≤ 0.34, P < 0.05). Changes in core LAM area were significantly associated with changes in 2-h glucose levels, glucose area measured during the oral glucose tolerance test and homeostasis model assessment of insulin resistance (0.21 ≤ r ≤ 0.34, P < 0.05). Stepwise regression analyses showed that changes in LAM psoas area were associated with changes in HDL cholesterol and the cholesterol/HDL cholesterol ratio independently from changes in visceral adiposity. CONCLUSIONS: Changes in trunk LAM areas are useful indices of changes in mid-thigh LAM area observed with a 1-yr lifestyle intervention. Thus, an additional mid-thigh scan is not necessary to evaluate muscle lipid content by CT when an abdominal CT scan is available.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".