Predicting and analysing of the unfavourable outcomes of early applicated percutaneous endoscopic interlaminar discectomy for lumbar disc herniation: development and validation based nomogram

• Published in: European spine journal Vol. 33; no. 3; pp. 906 - 914
• Main Authors: Huang, Huiyu, Yang, Min, Fu, Zhaojun, Hu, Haigang, Wu, Chao, Tan, Lun
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2024; Springer Nature B.V
• Subjects: Calcification; Diskectomy, Percutaneous - methods; Endoscopy; Endoscopy - methods; Humans; Hyperplasia; Intervertebral Disc Displacement - etiology; Intervertebral Disc Displacement - surgery; Intervertebral discs; Lumbar Vertebrae - surgery; Medicine; Medicine & Public Health; Neurosurgery; Nomograms; Original Article; Patients; Prediction models; Retrospective Studies; Risk factors; Surgical Orthopedics; Treatment Outcome; Unfavourable outcome; Percutaneous endoscopic interlaminar discectomy; Lumbar disc herniation; Nomogram
• ISSN: 0940-6719; 1432-0932
• DOI: 10.1007/s00586-024-08141-9

Objective To predict and analyse the unfavourable outcomes of early applicated percutaneous endoscopic interlaminar discectomy for lumbar disc herniation. Methods Information of 426 patients treated by early applicated percutaneous endoscopic interlaminar discectomy (PEID) for lumbar disc herniation (LDH) at our hospital from June 2017 to October 2021 in addition to 17 other features was collected. The risk factors were selected by the least absolute shrinkage and selection operator method (LASSO) regression. Then, a prediction model (nomogram) was established to predict the unfavourable outcomes of using the risk factors selected from LASSO regression. Bootstrap ( n  = 1000) was used to perform the internal validation, and the performance of the model was assessed by the concordance index (C-index), receiver operating characteristic curve, and calibration curve. The decision curve analysis (DCA) and clinical impact curve (CIC) were used to assess the clinical utility of the model, respectively. Results Finally, 53 of 426 patients showed unfavourable outcomes. Five potential factors, Modic change, Calcification, Lumbar epidural steroid injection preoperative, Articular process hyperplasia and cohesion, and Laminoplasty technique, were selected according to the LASSO regression, that identified the predictors to establish nomogram model. Meanwhile, the C-index of the prediction nomogram was 0.847, the area under the receiver operating characteristic curve value was 0.847, and the interval bootstrapping ( n  = 1000) validation C-index was 0.809. The model has good practicability for clinics according to the DCA and CIC. Conclusion This nomogram model has good predictive performance and clinical practicability, which could provide a certain basis for predicting unfavourable outcomes of early applicated PEID for LDH.