A systematic and interdisciplinary approach to the measurement of outcomes over the disease trajectory in a unique specialized cachexia clinic.
Bibliographic record
Abstract
25 Background: Cancer cachexia affects 60-80% of advanced cancer patients and leads to weight loss, worsening functional status, and increased mortality. Thus, specialized clinics are needed to measure nutritional and functional trajectories over time in this population. Recently, the McGill University Health Centre has developed a systematic, standardized and interdisciplinary approach for the profiling and management of cancer cachexia. Methods: Patients with advanced cancer were recruited and categorized as cachetic. The following information was collected at baseline and at three follow-up visits: hand grip strength measured by Jamar dynamometer, the Edmonton Symptom Assessment System (ESAS) and the abridged Patient Generated Subjective Global Assessment (aPG-SGA) questionnaires. Results: Fifty-nine patients were eligible for this study yet only 24 completed 3 follow-ups and were included. There were 15 men and 9 women, mean age 65.7 years. Five patients had locally advanced disease and 19 had metastatic disease. The table contains results for handgrip strength, ESAS and aPG-SGA scores. Conclusions: Following baseline assessment and treatment, patients were noted to have a significant improvement in the aPG-SGA total score. Handgrip strength was maintained throughout the follow up period. ESAS appetite and fatigue exhibited a positive trend but did not achieve significance over time. This work suggests the benefits of an interdisciplinary cachexia clinic for the maintenance of nutritional and functional status in patients with cancer cachexia as well as possible improvements in quality of life. [Table: see text]
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".