Supplementary Material for: Impact of Muscle Mass on Survival in Patients with Sepsis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
<b><i>Introduction:</i></b> The aim of this study is to investigate the association between loss of muscle mass and prognosis of sepsis. <b><i>Methods:</i></b> Six databases, including PubMed, Embase, Cochrane Library, Web of Science, Scopus, and Ovid, were searched by the deadline of August 18, 2020. A meta-analysis was conducted on the collected data by means of a random-effects model. The quality of each included article was assessed according to the Newcastle-Ottawa Scale. <b><i>Results:</i></b> Out of 1,819 references, 6 articles and 1 conference abstract were included. Sepsis patients with a loss of muscle mass or sarcopenia had higher mortality (risk ratio [RR]: 1.94, 95% confidence intervals [CI]: 1.59–2.37; I-squared = 18.7%, <i>p</i> < 0.001). The RR of mortality within 30 days (RR: 2.31, 95% CI: 1.78–2.99, <i>p</i> < 0.001) was higher than that of mortality over 30 days. Loss of psoas muscle mass, as evaluated by CT, showed the highest RR of sepsis mortality. In addition, based on data on overall survival retrieved from 4 trials, the pooled hazard ratio (HR) for patients with a loss of muscle mass or sarcopenia was 3.04. Subgroup analysis showed that survival time was the main source of heterogeneity for the overall HR. Furthermore, the scanning areas of muscle mass in survival patients were 0.33 cm<sup>2</sup>/m<sup>2</sup> higher than those measured in deceased patients. <b><i>Conclusion:</i></b> A loss of muscle mass, as evaluated by CT scan, was associated with a poor outcome in sepsis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.092 | 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".