American Society for Parenteral and Enteral Nutrition Clinical Guidelines: The Validity of Body Composition Assessment in Clinical Populations
Bibliographic record
Abstract
On behalf of the American Society for Parenteral and Enteral Nutrition (ASPEN), a systematic review was conducted to evaluate the best available evidence regarding the validity of relevant body composition methods (eg, dual energy X-ray absorptiometry [DXA], ultrasound [US], and bioelectrical impedance analysis [BIA]) in clinical populations. The guidelines targeted adults >18 years of age with a potentially inflammatory condition or pathological end point associated with a specific disease or clinical condition. In total, 7375 studies were retrieved, and 15 DXA, 7 US, and 23 BIA studies provided applicable data. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses was used to assess the diagnostic accuracy of the test method against a "gold standard" reference. The Grading of Recommendations, Assessment, Development and Evaluation criteria were used to separate the evaluation of the body of evidence from the recommendations. Based on a limited number of studies and expert opinion, DXA is recommended for the assessment of fat mass in patients with a variety of disease states; however, the validity of DXA for lean mass assessment in any clinical population remains unknown. No recommendations can be made at this time to support the use of US or BIA in the clinical setting, as data to support its validity in any specific patient population are limited in scope or by the proprietary nature of manufacture-specific BIA regression models to procure body composition data, respectively. Directions for future research are provided. These clinical guidelines were approved by the ASPEN Board of Directors.
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 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 | 0.060 | 0.150 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.016 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".