Faculty of Computer Science, Otto von Guericke University Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany.
Tinnitus Center, Charité Universitaetsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
Sci Rep. 2020 Oct 2;10(1):16411. doi: 10.1038/s41598-020-73402-8.
Chronic tinnitus is a complex, multi-factorial symptom that requires careful assessment and management. Evidence-based therapeutic approaches involve audiological and psychological treatment components. However, not everyone benefits from treatment. The identification and characterisation of patient subgroups (or "phenotypes") may provide clinically relevant information. Due to the large number of assessment tools, data-driven methods appear to be promising. The acceptance of these empirical results can be further strengthened by a comprehensive visualisation. In this study, we used cluster analysis to identify distinct tinnitus phenotypes based on self-report questionnaire data and implemented a visualisation tool to explore phenotype idiosyncrasies. 1228 patients with chronic tinnitus from the Charité Tinnitus Center in Berlin were included. At baseline, each participant completed 14 questionnaires measuring tinnitus distress, -loudness, frequency and location, depressivity, perceived stress, quality of life, physical and mental health, pain perception, somatic symptom expression and coping attitudes. Four distinct patient phenotypes emerged from clustering: avoidant group (56.8%), psychosomatic group (14.1%), somatic group (15.2%), and distress group (13.9%). Radial bar- and line charts allowed for visual inspection and juxtaposition of major phenotype characteristics. The phenotypes differed in terms of clinical information including psychological symptoms, quality of life, coping attitudes, stress, tinnitus-related distress and pain, as well as socio-demographics. Our findings suggest that identifiable patient subgroups and their visualisation may allow for stratified treatment strategies and research designs.
慢性耳鸣是一种复杂的、多因素的症状,需要仔细评估和管理。循证治疗方法包括听力学和心理学治疗成分。然而,并非每个人都能从治疗中受益。确定和描述患者亚组(或“表型”)可以提供临床相关信息。由于评估工具数量众多,基于数据的方法似乎很有前途。通过全面的可视化,可以进一步加强对这些经验结果的接受程度。在这项研究中,我们使用聚类分析根据自我报告问卷数据识别出不同的耳鸣表型,并实施了可视化工具来探索表型特征。来自柏林 Charité 耳鸣中心的 1228 名慢性耳鸣患者纳入研究。在基线时,每位参与者完成了 14 份问卷,测量耳鸣困扰、-响度、频率和位置、抑郁、感知压力、生活质量、身心健康、疼痛感知、躯体症状表达和应对态度。聚类分析得出了四个不同的患者表型:回避组(56.8%)、身心组(14.1%)、躯体组(15.2%)和困扰组(13.9%)。径向条形图和折线图允许直观检查和比较主要表型特征。这些表型在临床信息方面存在差异,包括心理症状、生活质量、应对态度、压力、耳鸣相关困扰和疼痛,以及社会人口统计学特征。我们的研究结果表明,可识别的患者亚组及其可视化可能允许分层治疗策略和研究设计。