Risk factors for postoperative complications after UBE surgery for thoracic spinal stenosis and construction of a nomogram predictive model
BackgroundThis study aimed to develop and validate the first nomogram model for predicting postoperative complications in thoracic spinal stenosis (TSS) patients undergoing unilateral biportal endoscopy (UBE), integrating multidimensional risk factors to provide a quantitative basis for preoperative...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-08-01
|
| Series: | Frontiers in Neurology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fneur.2025.1616590/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | BackgroundThis study aimed to develop and validate the first nomogram model for predicting postoperative complications in thoracic spinal stenosis (TSS) patients undergoing unilateral biportal endoscopy (UBE), integrating multidimensional risk factors to provide a quantitative basis for preoperative risk evaluation and individualized treatment planning.MethodsPatients were divided into a retrospective training cohort (n = 375) and a prospective validation cohort (n = 100). Baseline clinical data [age, diabetes, preoperative Japanese Orthopaedic Association (JOA) score], radiographic parameters (Spinal cord/canal area (SC/ECA) ratio, intramedullary high signal, thoracic kyphosis (TK) angle), and surgical variables (intraoperative blood loss, number of lesion segments, dural adhesion, etc.) were collected. Independent risk factors were identified using logistic regression analysis, and a nomogram model was constructed. Model performance was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).ResultsIn the training cohort, 30 patients experienced postoperative complications (37 total events), while 10 patients in the validation cohort had complications (19 total events). Major complications included cerebrospinal fluid leakage, neurological deterioration, poor wound healing, and epidural hematoma. Multivariate logistic regression analysis revealed that diabetes, SC/ECA ≥ 55%, intramedullary high signal, TK angle ≥ 45 °, dural adhesion, multisegment lesion, increased intraoperative blood loss, and prolonged hospitalization were independent risk factors, whereas a higher preoperative JOA score was protective. The nomogram demonstrated excellent discrimination (AUC = 0.964 for training cohort; 0.846 for validation cohort) and good calibration in both cohorts. DCA indicated significant clinical net benefit when the threshold probability exceeded 10%, especially for identifying high-risk patients (threshold > 40%). Risk weight analysis showed that multisegment lesion (25 points) and SC/ECA ≥ 55% (20 points) contributed most to complication risk, followed by intramedullary high signal (15 points) and TK angle (15 points).ConclusionThis study successfully established a predictive nomogram for postoperative complications following UBE in TSS patients. The model demonstrated high accuracy and clinical utility, providing valuable guidance for preoperative risk stratification and perioperative management, thereby promoting precision in minimally invasive thoracic spine surgery. |
|---|---|
| ISSN: | 1664-2295 |