INTRODUCTION Real-time symptom reporting during ambulatory reflux monitoring plays a key role in the evaluation of esophageal symptoms, although the underlying processes are poorly understood. We aim to identify the psychological and physiological factors associated with real-time reflux symptom reporting and symptom-reflux association parameters. METHODS Adult patients with refractory reflux symptoms completed psychosocial questionnaires and standard 24-hour pH-impedance monitoring. A hurdle-Poisson model evaluated the association between psychological and physiological (proton pump inhibitor [PPI] use, total number of reflux episodes) variables on real-time symptom frequency, assessed through a button press within 2 minutes of experiencing a symptom. Logistic regression assessed the variables associated with symptom association probability (SAP) and symptom index classification (positive/negative). Complementary machine learning analyses with 8-fold cross-validation further identified variables associated with symptom frequency and sought to optimize SAP classification performance. RESULTS Both psychological (pain-related anxiety, depressive symptoms, trait anxiety) and physiological (total number of reflux episodes, off PPI during testing) variables were associated with symptom frequency. The total number of reflux episodes and being studied off PPI were significantly associated with a higher likelihood of being classified as SAP or symptom index positive. The best-performing model in the machine learning analysis demonstrated a poor job of correctly classifying patients as SAP positive/negative (misclassification rate = 41.4%). DISCUSSION Real-time reflux symptom reporting is a multifactorial process, with both psychological and physiological processes contributing to different aspects of the reflux disease experience. Findings build on questionnaire-based research to underscore the importance of including psychological processes in our understanding of esophageal symptom reporting.

中文翻译：

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生理和心理因素有助于难治性反流患者的实时食管症状报告。


简介 动态反流监测期间的实时症状报告在食管症状评估中发挥着关键作用，尽管其基本过程尚不清楚。我们的目标是确定与实时反流症状报告和症状反流关联参数相关的心理和生理因素。方法 患有难治性反流症状的成年患者完成心理社会调查问卷和标准 24 小时 pH 阻抗监测。跨栏泊松模型评估了心理和生理（质子泵抑制剂 [PPI] 使用、反流发作总数）变量与实时症状频率之间的关联，通过在出现症状后 2 分钟内按下按钮进行评估。逻辑回归评估了与症状关联概率 (SAP) 和症状指数分类（阳性/阴性）相关的变量。具有 8 倍交叉验证的补充机器学习分析进一步确定了与症状频率相关的变量，并寻求优化 SAP 分类性能。结果心理（疼痛相关焦虑、抑郁症状、特质焦虑）和生理（反流发作总数、测试期间 PPI 关闭）变量均与症状频率相关。反流发作的总数和正在研究的 PPI 与被分类为 SAP 或症状指数阳性的可能性显着相关。机器学习分析中表现最好的模型在将患者正确分类为 SAP 阳性/阴性方面表现不佳（错误分类率 = 41.4%）。 讨论 实时反流症状报告是一个多因素的过程，心理和生理过程都会影响反流疾病经历的不同方面。研究结果以基于问卷的研究为基础，强调了将心理过程纳入我们对食管症状报告的理解的重要性。