Hypermetabolism and symptom burden in advanced cancer patients evaluated in a cachexia clinic
Bibliographic record
Abstract
BACKGROUND: Elevated resting energy expenditure (REE) may contribute to weight loss and symptom burden in cancer patients. AIMS: The aim of this study was to compare the velocity of weight loss, symptom burden (fatigue, insomnia, anxiety, and anorexia-combined score as measured by the Edmonton Symptom Assessment Score), high-sensitivity C-reactive protein, and survival among cancer patients referred to a cachexia clinic with hypermetabolism, elevated REE > 110% of predicted, with normal REE. METHODS: A retrospective analysis of 60 advanced cancer patients evaluated in a cachexia clinic for either >5% weight loss or anorexia who underwent indirect calorimetry to measure REE. Patients were dichotomized to either elevated or normal REE. Descriptive statistics were generated, and a two-sample Student's t-tests were used to compare the outcomes between the groups. Kaplan-Meier and Cox regression methodology were used to examine the survival times between groups. RESULTS: Thirty-seven patients (62%) were men, 41 (68%) were White, 59 (98%) solid tumours, predominantly 23 gastrointestinal cancers (38%), with a median age of 60 (95% confidence interval 57.0-62.9). Thirty-five patients (58%) were hypermetabolic. Non-Caucasian patients were more likely to have high REE [odds ratio = 6.17 (1.56, 24.8), P = 0.01]. No statistical difference regarding age, cancer type, gender, active treatment with chemotherapy, and/or radiation between hypermetabolic and normal REE was noted. The velocity of weight loss over a 3 month period (-8.5 kg vs. -7.2 kg, P = 0.68), C-reactive protein (37.3 vs. 55.6 mg/L, P = 0.70), symptom burden (4.2 vs. 4.5, P = 0.54), and survival (288 vs. 276 days, P = 0.68) was not significantly different between high vs. normal REE, respectively. CONCLUSION: Hypermetabolism is common in cancer patients with weight loss and noted to be more frequent in non-Caucasian patients. No association among velocity of weight loss, symptom burden, C-reactive protein, and survival was noted in advanced cancer patients with elevated REE.
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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 | 0.001 | 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 | 0.000 |
| 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".