Malnutrition in Spine Oncology: Where Are We and What Are We Measuring?
Bibliographic record
Abstract
STUDY DESIGN: Scoping review. OBJECTIVE: To identify which markers are used as surrogates for malnutrition in metastatic spine disease and which are the most studied outcomes associated with it. METHODS: A scoping review was performed by searching the PubMed/Medline, EMBASE, and Web of Science databases up to July 2022. We searched for articles exploring markers of malnutrition in spine oncology patients including but not limited to albumin, body weight, weight loss, and nutrition indices. A narrative synthesis was performed. RESULTS: A total of 61 articles reporting on 31,385 patients met inclusion criteria. There were 13 different surrogate markers of nutrition, with the most common being albumin in 67% of studies (n = 41), body weight/BMI in 34% (n = 21), and muscle mass in 28% (n = 17). The most common studied outcomes were survival in 82% (n = 50), complications in 28% (n = 17), and length of stay in 10% (n = 6) of studies. Quality of life and functional outcomes were assessed in 2% (n = 1) and 3% (n = 2) of studies, respectively. Out of 61 studies, 18% (n = 11) found no association between the examined markers and outcome. CONCLUSION: Assessment of nutritional status in patients with spinal metastases is fundamental. However, there is lack of a comprehensive and consistent way of assessing malnutrition in oncologic spine patients and therefore inconsistency in its relationship with outcomes. A consensus agreement on the assessment and definition of malnutrition in spine tumor patients is needed.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".