Radiographic assessment of sarcopenia in the trauma setting: a systematic review
Bibliographic record
Abstract
BACKGROUND: Compared with similarly injured patients of a younger age, elderly patients have worse outcomes from acute injury. One factor adversely affecting outcomes is sarcopenia, which has been assessed in healthy elderly populations through established clinical and radiological criteria. However, in the acute care setting, no such criteria have been established. Sarcopenia has been opportunistically assessed via radiographic means but there is as of yet no gold standard. The purpose of this review is to summarize the radiological methods used to diagnose sarcopenia in the acute care setting, and suggest ways in which these methods may lead to a consensus definition of sarcopenia and its relationship to patient outcomes. METHODS: A systematic survey of medical databases was conducted, with 902 unique publications identified. After screening and application of inclusion and exclusion criteria, data regarding study population, outcome, imaging modality, and criteria for assessment of sarcopenia were extracted from 20 studies. Quality was assessed with the Newcastle-Ottawa Scale. RESULTS: CT was the imaging modality for 18 of the studies, with total psoas muscle cross-sectional area at the level of L3 and L4 being the dominant method for assessing sarcopenia. Adjustment for body morphology most commonly used patient height or L4 vertebral body area. The majority of articles found radiographically assessed sarcopenia to be significantly correlated to outcomes such as mortality, length of hospital stay, morbidity, and in-hospital complications. CONCLUSIONS: Establishing a consistent definition would strengthen its applicability and generalizability to admission and discharge planning. LEVEL OF EVIDENCE: Systematic review, level III.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".