P.228 Pre-operative Surrogates Markers of Frailty and Metastatic Spine Disease: Systematic Review
Bibliographic record
Abstract
Background: Despite the inherent importance of physical reserve and ability to tolerate surgery, pre-operative patient-specific surrogate markers of frailty that may improve accuracy of outcome prognostication following surgery for SMD are not well described. Methods: A systematic review was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. MEDLINE, Scopus, EMBASE, Cochrane Registry of Controlled Trials, CINAHL, and Web of Science were searched. Quality of evidence was scored using the Oxford CEBM Scoring Tool. Results: Forty studies accounted for 8,364 patients. Surgical indications included neurological dysfunction, intractable pain, and spinal instability. Tumor histology varied across and within studies. Age, gender, performance status, neurologic function, comorbidities, and biochemical abnormalities were the most frequently analyzed pre-operative surrogate markers of frailty. The most commonly assessed outcomes were overall and progression-free survival; few studies examined health-related quality of life, peri-operative adverse events, and post-operative complications. Conclusions: This study highlights the need for objective measures of frailty in order to improve risk stratification and outcome prognostication among patients receiving surgery for metastatic spinal disease. Future studies should address identified knowledge gaps pertaining to peri-operative adverse events, post-operative complications, and health-related quality of life outcomes.
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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 | 0.008 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".