Thigh muscle by CT images as a predictor of mortality in patients with newly diagnosed colorectal cancer
Bibliographic record
Abstract
This study aimed to evaluate the prognostic value of thigh muscle assessed by CT images to predict overall mortality in patients with colorectal cancer (CRC). This was a multicenter cohort study including adults (≥ 18 years old) newly diagnosed with CRC, who performed a diagnostic computed tomography (CT) exam including thigh regions. CT images were analyzed to evaluate skeletal muscle (SM in cm 2 ), skeletal muscle index (SMI in cm 2 /m 2 ), and skeletal muscle density (SMD in HU). Muscle abnormalities (low SM, SMI, and SMD) were defined as the values below the median by sex. Kaplan–Meyer curves and hazard ratios (HRs) for low SM, SMI and SMD were evaluated for overall mortality, stratified by sex. A total of 257 patients were included in the final analysis. Patients’ mean age was 62.6 ± 12.1 years, and 50.2% (n = 129) were females. In males, low thigh SMI was associated with shorter survival (log-rank P = .02). Furthermore, this low thigh SMI (cm 2 /m 2 ) was independently associated with higher mortality rates (HR adjusted 2.08, 95% CI 1.03–4.18). Our additional findings demonstrated that low SMD was independently associated with overall mortality among early-stage patients (I–III) (HR adjusted 2.78, 95% CI 1.26–6.15).
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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) | 0.001 | 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".