The Relationship between Preoperative Expectations and the Short-Term Postoperative Satisfaction and Functional Outcome in Lumbar Spine Surgery: A Systematic Review
Bibliographic record
Abstract
Study Design Systematic review. Objective To examine the relationship between the patient's preoperative expectations and short-term postoperative satisfaction and functional outcome in lumbar spine surgery. Methods The Medline, Embase, and Cochrane databases were queried using a predefined search algorithm to identify all lumbar spine studies analyzing the influence of preoperative expectations on postoperative satisfaction and functional outcome. Two independent reviewers and a third independent mediator reviewed the literature and performed study screening, selection, methodological assessment, and data extraction using an objective protocol. Results Of 444 studies identified, 13 met the inclusion criteria. Methodological quality scores ranged from 59 to 100% with the greatest variability in defining patient characteristics and the methods of assessing patient expectations. Patient expectations were assessed in 22 areas, most frequently back and leg pain expectations and general expectations. Functional outcome was assessed by 13 tools; the most common were the visual analog scale, Oswestry Disability Index (ODI), and Short Form Health Survey (SF-36). Positive expectations for symptomatology, activity, general health, and recovery correlated with satisfaction. General expectations correlated with higher SF-36 Physical Subcomponent scores, better global function, and lower ODI outcome. Conclusions on the influence of the expectations for pain were limited due to the study heterogeneity, but the evidence suggests a positive correlation between the expectation and outcome for back and leg pain. Conclusions Positive expectations correlated significantly with short-term postoperative satisfaction and functional outcome, including higher SF-36 scores, earlier return to work, and decreased ODI scores. Future expectation-based investigations will benefit from implementation of the standardized methods of expectation, satisfaction, and outcome analysis discussed herein.
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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 | 0.017 | 0.073 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".