Detecting and Monitoring Tardive Dyskinesia to Improve Patient Outcomes

迟发性运动障碍(TD)是抗精神病药物使用的一种常见的衰弱副作用。最具特点的 明显表现为面部的不自主运动，如做鬼脸、不自主的嘴唇、嘴巴和舌头 运动和眨眼，TD很难治疗，而且有可能不可逆转。精神病学家和其他 心理健康专业人员敏锐地意识到患者所经历的损害和残疾 发展成TD的人。及早发现TD至关重要，这样才能采取适当的干预措施。 不幸的是，尽管专业人士尽了最大努力，但过程往往为时已晚，而且是不由自主的 运动是永久性的。 2011年抗精神病药物处方超过5000万张，报告的TD发病率在 13%和24%。风险随着年龄的增长、非标签使用和长期接触抗精神病药物而增加。 因此，预防和及早发现是管理TD的关键。然而，当前的方法 监测患者需要在不频繁的亲自探视或自我报告时观察患者 警惕的病人和他们的家人。因此，自动检测具有很强的市场潜力 系统。 这个第一阶段的项目计划利用现有的心灵感应和视频访谈数据收集 商业上可用的技术，可高效收集和分析200个5分钟的视频 对服用抗精神病药物的人的采访。一半的采访将与 确诊为TD的患者和未诊断为TD的患者。本次活动的参与者 将进行研究，以确保女性和男性的平均分布以及种族和 具有种族代表性的样本。 拟议的数据收集战略将提供必要的原始材料，以创建强大的 有监督的机器学习衍生的视频和音频分析工具来检测TD。检测工具将 使用收集的80%的视频数据作为训练集进行创建，并在其余20%的基础上进行验证 保留为控制集。基于其他有监督机器学习的行业经验 训练集和要收集的数据量，我们设定了识别成功率为90%的目标 对照组为TD阳性组和TD阴性组。 一旦检测工具完成，项目将通过将对该工具的访问合并到 现有的智能手机应用程序iRxRMinder，用于收集数据和监测临床试验。 IRxRMinder系统直接将患者与研究人员及其电子记录联系起来。这个 修改后的APP将在实验室进行测试，以确保界面可以轻松使用。在第二阶段 将验证iRxRminder系统在支持自我管理和症状方面的使用 监测慢性精神疾病患者的用药情况。一旦可行性是 ，我们建议一项为期一年的随机对照试验，对参与者进行监测，以便及早发现TD 以及高依从性、改进症状和副作用控制等目标 医疗团队积极而频繁的治疗反应。

Tardive dyskinesia (TD) is a common debilitating side effect of antipsychotic use. Characterized most notably by involuntary facial movements such as grimacing, involuntary lip, mouth, and tongue movements, and eye blinking, TD is difficult to treat and potentially irreversible. Psychiatrists and other mental health professionals are acutely aware of the impairment and disability experienced by patients who develop TD. Early detection of TD is critical so that appropriate interventions can be instituted. Unfortunately, despite professionals’ best efforts, it is often too late in the process and the involuntary movements are permanent. Antipsychotic prescriptions exceeded 50 million in 2011 and the reported incidence of TD is between 13% and 24%. Risk grows with advancing age, off-label uses, and chronic exposure to antipsychotics. Therefore, prevention and early detection are key to managing TD. However, current methods for monitoring patients require observation of patients at infrequent in-person visits or self-reporting by vigilant patients and their families. Therefore strong market potential exists for an automated detection system. This Phase I project proposes to leverage existing telepsychiatry and video interview data gathering technologies available commercially to efficiently collect and analyze two hundred 5-minute video interviews with individuals taking anti-psychotic medications. Half of the interviews will be with individuals living with diagnosed TD and the other without a diagnosis of TD. The participants in the study will be recruited to ensure an equal distribution of females and males as well as an ethnically and racially representative sample. The proposed data gathering strategy will provide the source material necessary to create a powerful supervised machine learning derived video and audio analysis tool to detect TD. The detection tool will be created using 80% of the collected video data as a training set and validated on the remaining 20% reserved as the control set. Based on industry experience with other supervised machine learning training sets and the amount of data to be collected, we set a goal of a 90% success rate in identifying TD positive and TD negative participants in the control set. Once the detection tool is complete the project will conclude by incorporating access to the tool into an existing smartphone app, iRxReminder, that is used for data gathering and monitoring of clinical trials. The iRxReminder system links patients directly to researchers and their electronic records. The modified app will be tested in the laboratory to ensure the interface can be easily used. In Phase II the iRxReminder system will be validated for use in supporting the self-management and symptom monitoring of medication taking by individuals living with chronic mental illnesses. Once feasibility is established, we propose a year-long RCT where participants will be monitored for early detection of TD along with goals for high adherence, improved control of symptoms and side effects, and more aggressive and frequent treatment responses by the healthcare team.