ArticleBMC surgery2026
Risk factors and prediction model for recurrence after unilateral dual-channel spinal endoscopy in patients with lumbar disc herniation.
Article in BMC surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveTo explore independent risk factors for recurrence in patients with lumbar disc herniation after unilateral dual-channel spinal endoscopy, and to build an individualized recurrence risk prediction model.
methodsThe clinical data of 181 patients with lumbar disc herniation who underwent UBE surgery in our hospital from January 2023 to September 2024 were retrospectively analyzed. According to whether there was recurrence at 1 year post-operative follow-up, they were divided into recurrence group (n=20) and non-recurrence group (n=161). Independent risk factors for postoperative recurrence were screened through univariate and multivariate Logistic regression analysis, and a nomogram prediction model was constructed based on the screened factors. The receiver operating characteristic curve, calibration curve and decision curve were used to evaluate the discrimination, calibration and clinical practicality of the model.
resultsMultivariate analysis showed that age (OR= 1.116, P =0.034), sagittal range of motion (sROM)(OR= 2.023, P =0.002), and Herniation base width (HBW)(OR= 1.639, P =0.008) were independent risk factors for recurrence after UBE. The predictive model built based on the three showed good predictive power, with an area under the curve of 0.894 in the training cohort. Analysis of both calibration curve and decision curve showed that the model had excellent accuracy and net clinical benefit.
conclusionIncrease in age, sROM and HBW are independent risk factors for recurrence after UBE in patients with lumbar disc herniation. The nomogram model constructed in this study showed good predictive ability for recurrence risk in our internal cohort. It may serve as a potential tool to help clinically identify high-risk patients and guide individualized management, but requires external validation before clinical implementation.
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