Psychological distress does not predict decisional regret in patients undergoing spinal reconstruction for adult spinal deformity
Bibliographic record
Abstract
PURPOSE: The study aimed to assess the link between preoperative psychological distress and postoperative decisional regret in adult spinal deformity (ASD) surgery patients. We hypothesized that greater pre-surgery distress would correlate with higher post-surgery regret. This evaluation was based on a retrospective case series from an institution with standardized surgical guidelines for ASD. METHODS: This IRB-approved retrospective study analyzed our institution's ASD database from 2014 to 2020. Eligible patients had a minimum two-year post-op follow-up and preoperative psychological distress assessment. Patients were grouped based on psychological distress levels: green, yellow, and yellow minus. Regret post-surgery was assessed using the Decision Regret Scale and SRS-22 Question 22. Logistic regression evaluated the impact of distress levels on regret, controlling for age and sex. RESULTS: Out of 167 eligible patients, 112 responded and were analyzed. No significant demographic differences were observed between responders and non-responders. Using the Decision Regret Scale, 41% expressed no regret, while 63% expressed no regret with the SRS-22 questionnaire's Single-Item scale. Only the yellow minus group showed significant regret difference based on osteotomy, with non-recipients more likely to express regret. CONCLUSION: This study found no significant link between psychological distress and post-operative regret in adult spinal deformity surgery after a minimum 2-year follow-up. Although nearly 60% exhibited some post-surgery regret, predicting regret based on psychological burden or demographics remains challenging. Further research is essential to identify factors contributing to post-operative regret in spinal deformity surgery patients.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".