Computed tomography-based body composition measures in COPD and their association with clinical outcomes: A systematic review
Bibliographic record
Abstract
Background Computed tomography (CT) is commonly utilized in chronic obstructive pulmonary disease (COPD) for lung cancer screening and emphysema characterization. Computed tomography-morphometric analysis of body composition (muscle mass and adiposity) has gained increased recognition as a marker of disease severity and prognosis. This systematic review aimed to describe the CT-methodology used to assess body composition and identify the association of body composition measures and disease severity, health-related quality of life (HRQL), cardiometabolic risk factors, respiratory exacerbations, and survival in patients with COPD. Methods Six databases were searched (inception-September 2021) for studies evaluating adult COPD patients using thoracic or abdominal CT-muscle or adiposity body composition measures. The systematic review was conducted in accordance with the PRISMA guidelines. Results Twenty eight articles were included with 15,431 COPD patients, across all GOLD stages with 77% males, age range (mean/median 59–78 years), and BMI range 19.8–29.3 kg/m 2 . There was heterogeneity in assessment of muscle mass and adiposity using thoracic ( n = 22) and abdominal ( n = 8) CT-scans, capturing different muscle groups, anatomic locations, and adiposity compartments (visceral, subcutaneous, and epicardial). Low muscle mass and increased adiposity were associated with increased COPD severity measures (lung function, exercise capacity, dyspnea) and lower HRQL, but were not consistent across studies. Increased visceral adiposity ( n = 6) was associated with cardiovascular disease or risk factors (hypertension, hyperlipidemia, and diabetes). Low muscle CSA was prognostic of respiratory exacerbations or mortality in three of six studies, whereas the relationship with increased intermuscular adiposity and greater mortality was only observed in one of three studies. Conclusion There was significant variability in CT-body composition measures. In several studies, low muscle mass was associated with increased disease severity and lower HRQL, whereas adiposity with cardiovascular disease/risk factors. Given the heterogeneity in body composition measures and clinical outcomes, the prognostic utility of CT-body composition in COPD requires further study.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".