Preoperative psychological health impacts pain and disability outcomes following anterior cervical discectomy and fusion for cervical radiculopathy
Bibliographic record
Abstract
This study aimed to estimate the effects of preoperative psychological health on postoperative outcomes in patients undergoing surgery for cervical spondylotic radiculopathy. This retrospective cohort study included data from patients enrolled in the Canadian Spine Outcomes and Research Network who underwent anterior cervical discectomy and fusion for radiculopathy. Preoperative psychological health was measured with the Patient Health Questionnaire-8 (PHQ-8), and depression and severe psychological symptomology were measured with the Mental Component Score of the Short Form Survey-12 (MCS). Surgical outcomes comprised trajectory subgroups for neck pain and arm pain (numeric rating scales) and disability (neck disability index) measured preoperatively and 3, 12, and 24 months after surgery. For each outcome, patients were dichotomized as following either a poor or a fair-to-excellent trajectory. Average treatment effects were estimated with doubly robust propensity score models using inverse probability of treatment weights accounting for multiple confounders. We included data from 352 patients (43.8% female). Approximately half (52.1%) of patients were identified as depressed based on the PHQ-8, while 61.8% and 33.1% were classified as experiencing depression or severe psychological symptomology, respectively, on the MCS. In fully adjusted models, patients with PHQ-8-measured depression were at increased risk of poor postoperative outcomes for disability (risk ratio[95% CI] = 6.73[1.85 to 24.45]) and neck pain (RR[95% CI] = 1.90[1.09 to 3.32]). Patients with MCS-measured depression were at elevated risk of a poor disability outcome (RR[95% CI] = 2.77[1.30 to 5.90]). Patients reporting severe psychological symptomatology had an increased likelihood of poor disability, neck pain, and arm pain outcomes (RR[95% CI] = 1.82 [1.17 to 2.82] to 2.84[1.58 to 5.09]). These findings highlight the high prevalence of negative psychological features and their impacts on neck surgery outcomes. Future research should prioritize the development and evaluation of preoperative interventions to optimize psychological well-being and improve surgical outcomes in this population.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".