Clinical and Surgical Predictors of Complications Following Surgery for the Treatment of Cervical Spondylotic Myelopathy
Bibliographic record
Abstract
BACKGROUND: Surgery for cervical spondylotic myelopathy (CSM) is generally safe and effective. Nonetheless, complications occur in 11% to 38% of patients. Knowledge of important predictors of complications will help clinicians identify high-risk patients and institute prevention and management strategies. OBJECTIVE: To identify clinical and surgical predictors of perioperative complications in CSM patients. METHODS: Four hundred seventy-nine surgical CSM patients were enrolled in the prospective CSM-International study at 16 sites. A panel of physicians reviewed all adverse events and classified each as related or unrelated to surgery. Univariate analyses were performed to determine differences between patients who experienced a perioperative complication and those who did not. A complication prediction rule was developed using multiple logistic regression. RESULTS: Seventy-eight patients experienced 89 perioperative complications (16.25%). On univariate analysis, the major clinical risk factors were ossification of the posterior longitudinal ligament (OPLL) (P = .055), number of comorbidities (P = .002), comorbidity score (P = .006), diabetes mellitus (P = .001), and coexisting gastrointestinal (P = .039) and cardiovascular (P = .046) disorders. Patients undergoing a 2-stage surgery (P = .002) and those with a longer operative duration (P = .001) were at greater risk of perioperative complications. A final prediction model consisted of diabetes mellitus (odds ratio [OR] = 1.96, P = .060), number of comorbidities (OR = 1.20, P = .069), operative duration (OR = 1.07, P = .002), and OPLL (OR = 1.75, P = .040). CONCLUSION: Surgical CSM patients have a higher risk of perioperative complications if they have a greater number of comorbidities, coexisting diabetes mellitus, OPLL, and a longer operative duration. Surgeons can use this information to discuss the risks and benefits of surgery with patients, to plan case-specific preventive strategies, and to ensure appropriate management in the perioperative period. ABBREVIATIONS: BMI, body mass indexCSM, cervical spondylotic myelopathymJOA, modified Japanese Orthopaedic AssociationOPLL, ossification of the posterior longitudinal ligament.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".