Development of a Model for Predicting the Effectiveness of Pulsed Radiofrequency on Zoster-Associated Pain

建立预测脉冲射频治疗带状疱疹相关疼痛疗效的模型

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Abstract

INTRODUCTION: Zoster-associated pain (ZAP), which may cause anxiety, depression, and sleep disorders and reduce quality of life, is often refractory to current standard treatments. Studies have shown that pulsed radiofrequency (PRF) can alleviate ZAP and reduce the incidence of postherpetic neuralgia (PHN). This study aimed to explore the clinical characteristics associated with PRF responsiveness, develop a model for identifying risk factors of inadequate PRF management, and help clinicians make better decisions. METHODS: Patients who underwent PRF for ZAP between January 2017 and October 2020 in our hospital were included in this study. Patients were evaluated using the numerical rating scale (NRS), Insomnia Severity Index, Patient Health Questionnaire-9, and 36-Item Short Form Health Survey (SF-36) before and 3 months after the procedure. Patient demographic data and blood test results were also collected. We defined the effectiveness of PRF for ZAP as relief of > 50% in NRS scores compared to pre-PRF. Least absolute shrinkage and selection operator (LASSO) regression analyses were subsequently performed to identify factors related to the therapeutic effect of PRF in patients with ZAP. The performance of the prediction model was assessed by the area under the receiver operating characteristic curve (AUC). RESULTS: The effectiveness of PRF in patients with ZAP was 69.6% (total 313 patients) after 3 months. LASSO regression analysis extracted the seven most powerful features in the developed prediction model: sex, stage of herpes zoster (HZ), pregabalin dose, bodily pain indicators of SF-36, lymphocyte count, and low-density lipoprotein cholesterol (LDLC) and complement C4 in peripheral blood. Model = 1.586 + 0.148 × lymphocyte + (-0.001) × bodily pain indicators of SF-36 + (-0.001) × pregabalin dose + 0.028 × LDLC + 0.001 × C4 + (-0.508) × sex + (-0.128) × stage of HZ. We generated the ROC curve for the prediction model, and the final AUC was 0.701. The sensitivity, specificity, and overall accuracy of the model were 90%, 33%, and 73%, respectively. CONCLUSIONS: Seven factors were significantly associated with poor PRF outcome: male sex, advanced stage of HZ, higher pregabalin dose, higher bodily pain indicators of SF-36, and lower lymphocyte count, LDLC, and complement C4 in the peripheral blood. PRF should be applied to patients with ZAP as early as possible to achieve satisfactory outcomes.

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