Adult Spinal Deformity Surgery and Frailty: A Systematic Review
Bibliographic record
Abstract
STUDY DESIGN: Systematic review. OBJECTIVES: Adult spinal deformity (ASD) can be a debilitating condition with a profound impact on patients' health-related quality of life (HRQoL). Many reports have suggested that the frailty status of a patient can have a significant impact on the outcome of the surgery. The present review aims to identify all pre-operative patient-specific frailty markers that are associated with postoperative outcomes following corrective surgery for ASD of the lumbar and thoracic spine. METHODS: A systematic review of the literature was performed to identify findings regarding pre-operative markers of frailty and their association with postoperative outcomes in patients undergoing ASD surgery of the lumbar and thoracic spine. The search was performed in the following databases: PubMed, Embase, Cochrane and CINAHL. RESULTS: An association between poorer performance on frailty scales and worse postoperative outcomes. Comorbidity indices were even more frequently employed with similar patterns of association between increased comorbidity burden and postoperative outcomes. Regarding the assessment of HRQoL, worse pre-operative ODI, SF-36, SRS-22 and NRS were shown to be predictors of post-operative complications, while ODI, SF-36 and SRS-22 were found to improve post-operatively. CONCLUSIONS: The findings of this review highlight the true breadth of the concept of "frailty" in ASD surgical correction. These parameters, which include frailty scales and various comorbidity and HRQoL indices, highlight the importance of identifying these factors preoperatively to ensure appropriate patient selection while helping to limit poor postoperative 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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".