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A Mobile Outside-in Technique of Transforaminal Lumbar Endoscopy for Lumbar Disc Herniations
Published on: August 7, 2018
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Nomogram Development and Validation for Predicting Postoperative Recurrent Lumbar Disc Herniation Based on Paraspinal
Ming Tang1,2, Siyuan Wang1,2, Yiwen Wang1
1Department of Interventional Vascular Medicine, Hefei Hospital Affiliated to Anhui Medical University, The Second People's Hospital of Hefei, Hefei City, Anhui Province, People's Republic of China.
Journal of Pain Research
|June 19, 2024
Summary
Paraspinal muscle skeletal muscle index (SMI) predicts recurrent lumbar disc herniation after surgery. A Nomogram model accurately assesses patient risk for postoperative recurrent lumbar disc herniation (PRLDH) following percutaneous endoscopic transforaminal discectomy (PETD).
Area of Science:
- Spine Surgery
- Orthopedics
- Radiology
Background:
- Paraspinal muscles are crucial for spinal stability.
- Postoperative recurrent lumbar disc herniation (PRLDH) is a common complication after lumbar disc herniation surgery.
- Percutaneous endoscopic transforaminal discectomy (PETD) is a minimally invasive surgical technique.
Purpose of the Study:
- To evaluate the predictive value of paraspinal muscles for PRLDH after PETD.
- To develop a predictive model for identifying patients at high risk of PRLDH.
Main Methods:
- Retrospective analysis of 232 patients who underwent PETD.
- Lasso and multivariable logistic regression to identify risk factors.
- Development and validation of a Nomogram predictive model.
- Assessment of model accuracy using Area Under the ROC Curve (AUC) and calibration curves.
- Clinical utility evaluated using Decision Curve Analysis (DCA) and Clinical Impact Curve (CIC).
Main Results:
- Diabetes, Modic changes, and ipsilesional multifidus muscle skeletal muscle index (SMI) were identified as independent predictors of PRLDH (P<0.05).
- The Nomogram model demonstrated high predictive accuracy with AUC values of 0.921 (training) and 0.900 (validation).
- The model showed good calibration and significant clinical net benefit across various risk thresholds.
Conclusions:
- The developed Nomogram model, incorporating paraspinal muscle parameters, effectively predicts PRLDH risk after PETD.
- This tool aids in personalized risk assessment and clinical decision-making for patients undergoing PETD.
