Quality of Life in Surgical Treatment of Metastatic Spine Disease
Bibliographic record
Abstract
STUDY DESIGN: Overall quality of life after surgical management of metastatic disease of the spine was prospectively assessed using a validated global health status quality-of-life instrument-the Edmonton Symptom Assessment Scale. OBJECTIVES: To prospectively evaluate the efficacy of surgery in patients with metastatic spinal disease with respect to quality of life. SUMMARY OF BACKGROUND DATA: Management of spinal metastases is palliative and is aimed at improving quality of life at an acceptable risk. Although previous studies have evaluated physical outcomes, improvements in pain, and neurologic function after surgery, a multidimensional assessment of quality of life is more relevant in the palliative patient. METHODS: Twenty-five consecutive patients undergoing surgery for spinal metastases were prospectively evaluated. Pre- and postoperative assessments were performed using the Edmonton Symptom Assessment Scale. The surgical procedure consisted of decompression and instrumented stabilization. RESULTS: After surgery, the largest improvement was noted in the domain of pain (P < 0.00001). There were also significant improvements noted in the domains of tiredness (P = 0.004), nausea (P = 0.01), anxiety (P = 0.006), drowsiness (P = 0.044), appetite (P = 0.02), and well-being (P = 0.004). CONCLUSIONS: The current study demonstrates that in the appropriate patient, surgical management brings about a positive effect on the overall quality of life in patients with spinal metastases. The greatest benefit occurred in the reduction of a patient's level of pain.
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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 | 0.001 | 0.002 |
| 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) | 0.002 | 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".