Low skeletal muscle area is a risk factor for mortality in mechanically ventilated critically ill patients
Bibliographic record
Abstract
INTRODUCTION: Higher body mass index (BMI) is associated with lower mortality in mechanically ventilated critically ill patients. However, it is yet unclear which body component is responsible for this relationship. METHODS: This retrospective analysis in 240 mechanically ventilated critically ill patients included adult patients in whom a computed tomography (CT) scan of the abdomen was made on clinical indication between 1 day before and 4 days after admission to the intensive care unit. CT scans were analyzed at the L3 level for skeletal muscle area, expressed as square centimeters. Cutoff values were defined by receiver operating characteristic (ROC) curve analysis: 110 cm2 for females and 170 cm2 for males. Backward stepwise regression analysis was used to evaluate low-muscle area in relation to hospital mortality, with low-muscle area, sex, BMI, Acute Physiologic and Chronic Health Evaluation (APACHE) II score, and diagnosis category as independent variables. RESULTS: This study included 240 patients, 94 female and 146 male patients. Mean age was 57 years; mean BMI, 25.6 kg/m2. Muscle area for females was significantly lower than that for males (102 ± 23 cm2 versus 158 ± 33 cm2; P < 0.001). Low-muscle area was observed in 63% of patients for both females and males. Mortality was 29%, significantly higher in females than in males (37% versus 23%; P = 0.028). Low-muscle area was associated with higher mortality compared with normal-muscle area in females (47.5% versus 20%; P = 0.008) and in males (32.3% versus 7.5%; P < 0.001). Independent predictive factors for mortality were low-muscle area, sex, and APACHE II score, whereas BMI and admission diagnosis were not. Odds ratio for low-muscle area was 4.3 (95% confidence interval, 2.0 to 9.0, P < 0.001). When applying sex-specific cutoffs to all patients, muscle mass appeared as primary predictor, not sex. CONCLUSIONS: Low skeletal muscle area, as assessed by CT scan during the early stage of critical illness, is a risk factor for mortality in mechanically ventilated critically ill patients, independent of sex and APACHE II score. Further analysis suggests muscle mass as primary predictor, not sex. BMI is not an independent predictor of mortality when muscle area is accounted for.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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 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".