Pain Ther:机器学习预测带状疱疹患者带状疱疹后神经痛

2021-09-14 从医路漫漫 MedSci原创

带状疱疹后神经痛(PHN)是一种继发于带状疱疹的神经性疼痛。研究表明,早期疼痛干预可以降低PHN的发生率或疼痛强度。

简介:带状疱疹后神经痛(PHN)是一种继发于带状疱疹的神经性疼痛。研究表明,早期疼痛干预可以降低PHN的发生率或疼痛强度。

目的是预测急性疱疹性神经痛患者是否会发展PHN,并帮助临床医生做出更好的决定。

方法:对520例带状疱疹患者进行回顾性分析。通过单因素分析确定与PHN相关的危险因素。使用Logistic回归和随机森林算法进行机器学习,然后比较两种算法的预测准确率,选择较优的算法预测接下来的60个新病例。

结果:年龄、NRS评分、皮疹部位、Charlson合并症指数(CCI)评分、抗病毒治疗及免疫抑制与PHN的发生有关。NRS评分是最密切相关因素,重要性为0.31。在准确率方面,随机森林的准确率为96.24%,优于logistic回归的准确率92.83%。随后,应用随机森林模型预测60例新诊断的带状疱疹患者,准确率为88.33%,95%置信区间(CI)为77.43-95.18%。

表1 logistic回归结果

图 各因素的重要性

表2 随机森林与logistic回归的比较

表3 预测结果和实际结果

结论:本研究提供了一种思路和方法,通过对既往病例数据的分析,我们可以建立一种预测模型来预测带状疱疹患者是否会发展PHN。

原文出处

Wang XX,  Zhang Y,  Fan BF,Predicting Postherpetic Neuralgia in Patients with Herpes Zoster by Machine Learning: A Retrospective Study.Pain Ther 2020 Dec;9(2)

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    2021-09-16 贵阳
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