Adverse Events in Surgically Treated Cervical Spondylopathic Myelopathy
Bibliographic record
Abstract
In Brief Study Design. Prospective observational study. Objective. Using validated tools to accurately identify and quantify incidence of and risks for inpatient adverse events (AEs) associated with surgical management of cervical spondylopathic myelopathy (CSM) with the goal of assisting physicians and patients in decision making. To identify patient-/disease-/technique-specific, independent risk factors for developing AEs perioperatively and affecting length of stay for patients treated surgically for CSM. Summary of Background Data. Previous studies have reported an overall perioperative complication rate between 15.6% and 18.52%. Methods. A total of 104 patients underwent surgery for CSM in our academic quaternary referral center. The average age was 60.3 years (range, 34–86 yr) with a male preponderance (n = 77, 74%). The severity of myelopathy and significant comorbidities was measured and was in keeping with previously assessed populations. Surgical approach was anterior-alone (39.4%), posterior-alone (55.8%), or combined (4.8%) surgery. Inpatient AE data were collected in a rigorous, contemporaneous fashion using the previously validated Spine Adverse Events Severity System (SAVES) tool. Results. A total AE rate of 42.3% was documented in surgically managed patients with CSM (intraoperative = 13.5%, postoperative = 37.5%). Statistically significant risk factors for postoperative AEs were identified, including number of comorbidities (P = 0.012), anterior surgical approach (P = 0.003), and number of levels operated on (P = 0.031). Multiple risk factors for length of stay were also identified, including number of AEs (P < 0.0001), Nurick Score (P < 0.0001), number of levels operated on (P = 0.006), and occurrence of deep wound infection (P < 0.0001). Conclusion. We report higher perioperative AE rates than previously recognized, due to the use of a validated, rigorous data collection tool. Multiple novel patient/disease severity/surgical factors with high statistical significance on perioperative AEs have been identified. Level of Evidence: 3 This study examines the perioperative outcome demographics of cervical spondylopathic myelopathy with respect to medical comorbidities. Rigorous data collection and statistical analysis has yielded a higher than previously reported rate of adverse events. Overall perioperative adverse events were statistically associated with increased number of surgical levels, number of comorbidities, and anterior surgical approach.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".