INTRODUCTION Panic disorder (PD) is common and defined by recurrent, unexpected panic attacks and persistent concern about additional attacks and their consequences. Anxiety affects declarative memory, which is important for reframing maladaptive thoughts and beliefs and learning healthy coping strategies. METHODS We developed random forest (RF) models to classify the declarative memory profile of PD patients in comparison to a healthy control sample using the Rey Auditory Verbal Learning Test (RAVLT). For this study, a total of 299 patients with PD living in the city of Rio de Janeiro (70.9% females, age 39.9 7.3 years old) were recruited through clinician referrals or self/family referrals. RESULTS Our RF models successfully predicted declarative memory profiles in patients with PD based on RAVLT scores (lowest area under curve of 0.979, for classification; highest root mean squared percentage of 17.2%, for regression) using relatively bias-free clinical data, such as sex, age, and body mass index (BMI). CONCLUSIONS Our findings also suggested that BMI, used as a proxy for diet and exercises habits, plays an important role in declarative memory. Our framework can be extended and used as a prospective tool to classify and examine associations among clinical features and declarative memory in PD patients.

中文翻译：

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恐慌症患者陈述性记忆概况的预测：基于机器学习的方法。

简介 恐慌症 (PD) 很常见，其定义是反复出现、意外的恐慌发作以及对额外发作及其后果的持续担忧。焦虑会影响陈述性记忆，这对于重塑适应不良的思想和信念以及学习健康的应对策略非常重要。方法 我们开发了随机森林 (RF) 模型，使用 Rey 听觉语言学习测试 (RAVLT) 对 PD 患者的陈述性记忆特征进行分类，并与健康对照样本进行比较。本研究通过临床医生推荐或自我/家人推荐招募了 299 名居住在里约热内卢市的 PD 患者（70.9% 为女性，年龄 39.9±7.3 岁）。结果我们的 RF 模型使用相对无偏差的临床数据，根据 RAVLT 评分（用于分类的最低曲线下面积为 0.979；用于回归的最高均方根百分比为 17.2%）成功预测了 PD 患者的陈述性记忆概况，例如性别、年龄和体重指数 (BMI)。结论 我们的研究结果还表明，作为饮食和运动习惯指标的体重指数在陈述性记忆中发挥着重要作用。我们的框架可以扩展并用作前瞻性工具来分类和检查 PD 患者临床特征和陈述性记忆之间的关联。