A Nomogram model to predict low back pain for patients with lumbar spinal stenosis after lower decompression and fusion
10.3760/cma.j.cn115530-20240909-00362
- VernacularTitle:腰椎管狭窄症患者减压融合术后腰痛Nomogram预测模型的构建
- Author:
Yuguo ZHAO
1
;
Xiangyang YE
;
Sheng CHENG
Author Information
1. 河南省南阳市中心医院骨科一病区，南阳 473000
- Keywords:
Spinal stenosis;
Spinal fusion;
Low back pain;
Nomogram;
Prediction model
- From:
Chinese Journal of Orthopaedic Trauma
2024;26(10):905-910
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the influencing factors for low back pain after decompression and fusion in patients with lumbar spinal stenosis and to construct a Nomogram prediction model.Methods:A retrospective study was conducted to analyze the 132 patients with lumbar spinal stenosis who had been treated at Department of Orthopedics, Nanyang Central Hospital from May 2021 to March 2022. The patients were divided into 2 groups according to their visual analog scale (VAS) pain score: a back pain-free group (104 cases with VAS ≤ 2) and a back pain group (28 cases with VAS > 2). Univariate and multiple logistic regression analyses were employed to identify the influencing factors for occurrence of lower back pain and a Nomogram prediction model for the risk of lower back pain was constructed in patients with lumbar spinal stenosis after decompression and fusion. The accuracy of the model was assessed using the receiver operating characteristic (ROC) curve. Furthermore, the model accuracy was pre-tested using an external validation model which included 66 illegible patients with lumbar spinal stenosis treated at Department of Orthopedics, Nanyang Central Hospital from May 2022 to March 2023. A comparison was made between the outcomes predicted by the model and the actual outcomes observed. The fit of the model was evaluated through the Hosmer-Lemeshow test.Results:The results of the multifactorial analysis indicated that interleukin (IL-1 β), postoperative aseptic inflammation in the vertebral canal, and intraoperative blood loss were independent influencing factors for the occurrence of lower back pain (all P < 0.05). A risk Nomogram prediction model was thus established based on these factors. The area under the curve (AUC) was 0.975, the sensitivity 92.90%, the specificity 91.30%, and the Youden index 0.842. External validation of the model showed an overall accuracy of 99.80%. The Hosmer-Lemeshow test demonstrated good model fit ( χ2=3.512, P=0.898). Conclusions:IL-1 β, postoperative aseptic inflammation in the vertebral canal, and intraoperative blood loss may be the primary influencing factors for the occurrence of lower back pain in patients with lumbar spinal stenosis after decompression fusion surgery. The Nomogram prediction model based on these influencing factors demonstrates excellent predictive efficacy for lower back pain.
