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[针灸治疗贝尔面瘫临床预测模型的构建与验证]

[Construction and validation of clinical prediction model of acupuncture and moxibustion for Bell's palsy].

作者信息

Chen Haoran, Zheng Yi, Li Jie, Bao Qi, Li Xiaopeng, Yu Shenlin, Zhu Qingting, Lv Lei, Yu Xiaofei, Xu Donghao, Wang Kejun

机构信息

School of Integrated Chinese and Western Medicine, Binzhou Medical University, Yantai 264003, Shandong Province, China.

Department of Integrated Chinese and Western Medicine, Yantai Yuhuangding Hospital.

出版信息

Zhongguo Zhen Jiu. 2024 May 12;44(5):495-502. doi: 10.13703/j.0255-2930.20230730-k0003.

Abstract

OBJECTIVE

To establish and validate a clinical prediction model of acupuncture and moxibustion for Bell's palsy so as to provide a tool for predicting the effect of acupuncture and moxibustion on Bell's palsy.

METHODS

A total of 269 patients with Bell's palsy were collected from department of acupuncture, moxibustion and tuina, Shengli Oilfield Central Hospital, neurology department, Shenxian County Central Hospital and department of rehabilitation medicine, Dongying Municipal Hospital of TCM from June 2018 to June 2023. All of these cases were treated with acupuncture and moxibustion. Of them, 182 cases, from department of acupuncture, moxibustion and tuina, Shengli Oilfield Central Hospital and neurology department, Shenxian County Central Hospital, were randomized into a training group (128 cases) and an internal validation group (54 cases); 87 cases from department of rehabilitation medicine, Dongying Municipal Hospital of TCM were assigned to an external validation group. The clinical data of all of the cases were extracted from the electronic medical record information platform. Using SPSS25.0 and R4.2.3, through univariate and multivariate Logistic regression analysis, the independent factors influencing the effects of acupuncture and moxibustion on Bell's palsy were identified. By means of internal and external validations, the receiver operating characteristic curve (ROC), the goodness-of-fit curve (GFC) and the decision curve analysis (DCA) were plotted. The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of the model were calculated; and its comprehensive performance was evaluated.

RESULTS

The results of the multivariate Logistic regression analysis showed that the independent factors for the unsatisfactory effect on Bell's palsy were advanced age, severe symptoms before treatment, no use of steroids within 72 h of onset, and lack of acupuncture-moxibustion therapy during the acute phase or single acupuncture-moxibustion protocol (<0.05, <0.01). Based on these factors, nomogram model and online columnar plot prediction tool (https://bmuchen.shinyapps.io/dynnomapp/) were established. The area under the ROC curve of the model was 0.921 (95% : 0.877, 0.966), 0.876 (95% : 0.787, 0.966), and 0.846 (95% : 0.766, 0.926) in the training group, the internal validation group, and the external validation group, respectively, indicating good predictive value. The model showed a satisfactory calibration curve alignment. The decision threshold in the range of 0 to 0.8 provided clinical benefits for participants. The model exhibited the sensitivity from 65.9% to 88.0%, the specificity ranging from 77.3% to 90.7%, the accuracy from 77.8% to 85.9%, the positive predictive value from 83.3% to 90.1%, and the negative predictive value from 70.8% to 78.7%. The comprehensive evaluation indicated a satisfactory clinical application value of the model.

CONCLUSION

The clinical prediction model of acupuncture and moxibustion for Bell's palsy is valuable in its practice and promotion to a certain extent. The predicted results are conductive to clinicians' judgement of the effect of acupuncture and moxibustion for this disease and making effective and high-quality clinical decisions, as well as formulating the optimal therapeutic regimen.

摘要

目的

建立并验证针灸治疗贝尔面瘫的临床预测模型,为预测针灸治疗贝尔面瘫的疗效提供工具。

方法

收集2018年6月至2023年6月胜利油田中心医院针灸推拿科、莘县中心医院神经内科、东营市中医医院康复医学科共269例贝尔面瘫患者,均采用针灸治疗。其中,胜利油田中心医院针灸推拿科和莘县中心医院神经内科的182例患者随机分为训练组(128例)和内部验证组(54例);东营市中医医院康复医学科的87例患者作为外部验证组。所有病例的临床资料均从电子病历信息平台提取。运用SPSS25.0和R4.2.3软件,通过单因素和多因素Logistic回归分析,筛选出影响针灸治疗贝尔面瘫疗效的独立因素。通过内部和外部验证,绘制受试者工作特征曲线(ROC)、拟合优度曲线(GFC)及决策曲线分析(DCA)。计算模型的灵敏度、特异度、准确度、阳性预测值和阴性预测值,并评价其综合性能。

结果

多因素Logistic回归分析结果显示,影响贝尔面瘫针灸疗效不佳的独立因素为年龄较大、治疗前症状较重、发病72 h内未使用糖皮质激素、急性期未采用针灸治疗或针灸方案单一(P<0.05,P<0.01)。基于这些因素,建立了列线图模型及在线柱状图预测工具(https://bmuchen.shinyapps.io/dynnomapp/)。训练组、内部验证组和外部验证组模型的ROC曲线下面积分别为0.921(95%CI:0.877,0.966)、0.876(95%CI:0.787,0.966)和0.846(95%CI:0.766,0.926),提示模型具有良好的预测价值。模型校准曲线拟合良好。决策阈值在0至0.8范围内可为受试者带来临床益处。模型的灵敏度为65.9%至88.0%,特异度为77.3%至90.7%,准确度为77.8%至85.9%,阳性预测值为83.3%至90.1%,阴性预测值为70.8%至78.7%。综合评价表明该模型具有满意的临床应用价值。

结论

针灸治疗贝尔面瘫的临床预测模型具有一定的实践及推广价值。预测结果有助于临床医生判断针灸治疗该病的疗效,做出有效、高质量的临床决策,并制定最佳治疗方案。

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