Markers of sarcopenia increase 30-day mortality following emergency laparotomy: A systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Decreased skeletal muscle mass and quality are one of the several markers used for sarcopenia diagnosis and are generally associated with increased rates of post-operative infections, poorer recovery and increased mortality. The aim of this review was to evaluate methods applied to detect markers of sarcopenia and the associated outcomes for patients undergoing emergency laparotomy. METHODS: This review was conducted with reference to Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. MEDLINE, Embase and Google Scholar databases were searched. Studies detecting patients with sarcopenia or skeletal muscle decline markers and the associated outcomes after emergency laparotomy surgery were considered. The Newcastle-Ottawa Scale was used to evaluate publication quality. RESULTS: = 967. The age range was 36-95 years. There were 1107 females (53%) and 973 males (47%) across all 7 studies. All studies measured psoas muscle mass and three studies assessed psoas muscle quality using computerized tomography (CT) imaging. No study assessed muscle strength or function, while five studies showed an association between low muscle mass and increased mortality rates after emergency laparotomy. Among the three studies, which assessed muscle quality, two of three studies showed poorer 30-day survival rates. CONCLUSIONS: The existing literature is limited, however it indicates that low psoas muscle mass and quality markers are associated with increased 30-day mortality rates after emergency laparotomy. Therefore, muscle markers can be used as a new feasible tool to identify most at risk patients requiring further interventions.
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.
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 | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it