Impact of Undergoing Thoracolumbar Surgery on Patient Psychosocial Profiles
Bibliographic record
Abstract
STUDY DESIGN: Prospective cohort study. OBJECTIVE: Investigate the impact of thoracolumbar surgery on patients' psychosocial profiles. METHODS: A prospective cohort study of thoracolumbar surgery patients (N = 177). Measures of interest collected at baseline and 24-months after surgery were: modified Oswestry Disability Index (mODI), Numerical Rating Scores for Back Pain (NRS-B), Leg Pain (NRS-L), Pain Catastrophizing Scale (PCS), Tampa Scale of Kinesiophobia (TSK), Chronic Pain Acceptance Questionnaire-8 (CPAQ-8), Multidimensional Scale of Perceived Social Support (MSPSS), Mental Component Summary (MCS) and patient expectations for surgery impacts on mental well-being. Cohorts were separated based on attaining meaningful change defined as either 30% improvement or minimal scores in NRS-B, NRS-L and mODI. Mixed measures ANOVAs were run (α = .05). RESULTS: Patients who showed meaningful change had significant improvements in PCS, TSK and CPAQ-8 scores but not in MSPSS scores. Patients had improvement in MCS scores over 24-months follow-up, but this change was not significantly different based on attainment of meaningful change. Overall, 75.9% of patients reported their mental well-being expectations were met. Patients who did not achieve meaningful change showed no change on any psychosocial measures with only 55.9% reporting their mental well-being expectations met. CONCLUSION: Thoracolumbar surgery results in significant improvement of psychosocial variables for patients who experienced meaningful change for pain and disability. Worsening of psychosocial health was not evident in patients who did not attain meaningful change.
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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 | 0.001 |
| 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 | 0.001 |
| 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".