中国当代医药2026，Vol.33Issue(12)：4-9,6.DOI:10.3969/j.issn.1674-4721.2026.12.01
机器人辅助脊柱畸形手术中压力性损伤风险预测模型的构建与验证
Construction and verification of a risk prediction model for pressure in-jury in robot-assisted spinal deformity surgery
摘要
Abstract
Objective To construct a risk prediction model for pressure injury in robot-assisted spinal deformity surgery,and to verify its clinical efficacy.Methods The clinical data of 487 patients underwent robot-assisted spinal deformity surgery in the Third People's Hospital of Huizhou from January 2020 to January 2025 were retrospectively analyzed.According to the ratio of 7∶3,they were divided into the training set(341 cases)and the validation set(146 cases).According to the occurrence of pressure injury,the patients in the training set were divided into the injury group and the non-injury group.The clinical data of the two groups were compared.Multivariate logistic regression was used to analyze the influencing factors of pressure injury in robot-assisted spinal deformity surgery.The nomogram model was constructed based on R language,and the effectiveness of the model was evaluated by calibration curve,ROC curve and DCA curve.Results The incidence rates of pressure injury in patients underwent robot-assisted spinal deformity surgery in the training set and the validation set were 14.96%(51/341)and 15.75%(23/146)respectively.The proportions of body mass index(BMI)＜18.5 kg/m2 or≥28 kg/m2,diabetes,malnutrition,operation time≥3 h and intraoperative abnormal body temperature in the injury group were higher than those in the non-injury group,and the number of fusion segments of surgical fixation was more than that of the non-injury group,with statistically significant differences(P＜0.05).Multivariate logistic regres-sion analysis showed that BMI＜18.5 kg/m2 or≥28 kg/m2,diabetes,malnutrition,operation time≥3 h and intraoper-ative abnormal body temperature were all independent risk factors for pressure injury during robot-assisted spinal deformity surgery(P＜0.05).The nomogram prediction model was constructed based on the results of multi-factor regression analysis,while the verification showed that the consistency indexes of the training set and the validation set were 0.841 and 0.827 respectively,and the calibration curve was well fitted with the ideal curve.ROC analysis results showed that the AUC,sensitivity and specificity of the training set and the validation set for predicting pressure injury in robot-assisted spinal deformity surgery were 0.900(95%CI:0.863-0.930),84.31%,86.21%and 0.872(95%CI:0.807-0.922),82.61%,84.55%respectively.The DCA curve showed that the model had a higher net benefit value when the threshold probability of the training set was within 0.13-0.83 and 0.97-1.00,and the threshold probability of the validation set was within 0.11-0.72 and 0.92-0.96.Conclusion BMI,diabetes,malnutrition,operation time and intraoperative body temperature are all risk factors for pressure injury in robot-assisted spinal deformity surgery.The nomogram risk prediction model based on the above influencing factors has good clinical application value.关键词
脊柱畸形/机器人辅助手术/压力性损伤/影响因素/列线图Key words
Spinal deformity/Robot-assisted surgery/Pressure injury/Influencing factors/Nomogram分类
医药卫生引用本文复制引用
邓永清,黄媚,胡世勋..机器人辅助脊柱畸形手术中压力性损伤风险预测模型的构建与验证[J].中国当代医药,2026,33(12):4-9,6.基金项目
广东省惠州市科技计划项目(2022CZ010451). （2022CZ010451）
