C-Reactive Protein Level: A Key Predictive Marker of Cachexia in Lymphoma and Myeloma Patients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Cachexia is defined as an involuntary loss of weight, characterized by a loss of skeletal muscle mass with or without fat mass loss. It increases mortality risk and decreases quality of life in patients with lymphoma or myeloma. Early markers of cachexia are not identified. The objective of this work was to identify risk factor of cachexia in a cohort of patients with hematological malignancies to develop strategies to prevent cachexia and its consequences. METHODS: Clinical and biological parameters were collected before and at the end of the treatment. Quantification of weight loss during cachexia was performed by the method of Martin. Clinical responses to treatment of patients with lymphoma or myeloma were monitored. RESULTS: Thirty-eight percent of the 145 patients enrolled were cachectic at the end of treatment. Classical prognostic disease scores at the time of diagnosis seemed to be not associated with cachexia observed at the end of treatment. Only C-reactive protein (CRP) > 54 mg/L seemed to be a risk factor of cachexia (P = 0.023, odds ratio (OR): 5.94 (1.55 - 39.14), confidence interval (CI): 1.55 - 39.14). Those results were confirmed by bootstrap analysis. CONCLUSION: This study highlights that high CRP level at diagnosis seems to be a risk factor for cachexia during treatment, permitting to identify patients at risk and in future to implement preventive strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it