Livia Guadagnoli, Sophie Abber, Annelies Geeraerts, Hannelore Geysen, Ans Pauwels, Jan Tack, Lukas Van Oudenhove, Tim Vanuytsel
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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.</p><p><strong>Results: </strong>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%).</p><p><strong>Discussion: </strong>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.</p>","PeriodicalId":7608,"journal":{"name":"American Journal of Gastroenterology","volume":" ","pages":"344-352"},"PeriodicalIF":8.0000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Physiological and Psychological Factors Contribute to Real-Time Esophageal Symptom Reporting in Patients With Refractory Reflux.\",\"authors\":\"Livia Guadagnoli, Sophie Abber, Annelies Geeraerts, Hannelore Geysen, Ans Pauwels, Jan Tack, Lukas Van Oudenhove, Tim Vanuytsel\",\"doi\":\"10.14309/ajg.0000000000003033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>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. 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引用次数: 0
摘要
背景:非卧床反流监测期间的实时症状报告在食管症状评估中起着关键作用,但对其基本过程却知之甚少。我们旨在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填写心理社会调查问卷,并进行标准的 24 小时 pH 值阻抗监测。飓风-泊松模型评估了心理和生理(质子泵抑制剂(PPI)使用情况、反流发作总次数)变量与实时症状频率之间的关联,实时症状频率是在出现症状后两分钟内按下按钮进行评估的。逻辑回归评估了与症状关联概率(SAP)和症状指数(SI)分类(阳性/阴性)相关的变量。采用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,并试图优化SAP分类性能:心理(疼痛相关焦虑、抑郁症状、特质焦虑)和生理(反流发作总次数、测试期间未使用 PPI)变量均与症状频率相关。反流发作总次数和停用 PPI 进行研究与被归类为 SAP 或 SI 阳性的可能性较高密切相关。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(误分类率=41.4%):实时反流症状报告是一个多因素过程,心理和生理过程对反流疾病体验的不同方面都有影响。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中的重要性。
Physiological and Psychological Factors Contribute to Real-Time Esophageal Symptom Reporting in Patients With Refractory Reflux.
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.
期刊介绍:
Published on behalf of the American College of Gastroenterology (ACG), The American Journal of Gastroenterology (AJG) stands as the foremost clinical journal in the fields of gastroenterology and hepatology. AJG offers practical and professional support to clinicians addressing the most prevalent gastroenterological disorders in patients.