Extracellular–to–Body Cell Mass Ratio and Subjective Global Assessment in Head-and-Neck Cancers
Bibliographic record
Abstract
BACKGROUND: The ratio of extracellular mass to body cell mass (ecm/bcm), determined by bioelectrical impedance analysis, has been found to be a potentially useful indicator of nutrition status. Subjective global assessment (sga) is a subjective method of evaluating nutrition status in head-and-neck cancer. The present study was conducted to investigate the association between ecm/bcm and sga in head-and-neck cancer. METHODS: Patients were classified as either well-nourished or malnourished by sga. Bioelectrical impedance analysis was conducted on a population of 75 patients with histologically confirmed head-and-neck cancer, and the ecm/bcm was calculated. Receiver operating characteristic curves were estimated using the nonparametric method to determine an optimal cut-off value of the ecm/bcm. RESULTS: Compared with malnourished patients, those who were well-nourished had a statistically significantly lower ecm/bcm (1.11 vs. 1.28, p = 0.005). An ecm/bcm cut-off of 1.194 was 76% sensitive and 63% specific in detecting malnutrition. CONCLUSIONS: The ecm/bcm can be an indicator that detects malnutrition in patients with head-and-neck cancer. Further observations are needed to validate the significance of the ecm/bcm and to monitor nutrition interventions.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".