Developing an App-Based Voice Clinical Decision Support Tool to Augment the Sensitivity of the Bedside Swallow Evaluation in Older Adults

项目总结/摘要 Rameau博士的Beeson应用程序的首要目标是（1）开发一个易于使用的，高度 使用分析确定老年人吞咽功能障碍的准确床边临床决策支持工具 他们录制的声音，咳嗽和讲话的特点，（2）成为新生领域的领导者， 老年耳鼻喉科，重点关注老年人的言语和吞咽问题， 阿尔茨海默病和相关痴呆（AD/ADRD）。 候选人：申请人Anaïs Rameau博士是威尔康奈尔医学院（WCMC）的耳鼻喉科医生 who在老年耳鼻喉科，特别是在以下领域， 老年吞咽困难患者的护理。拉莫博士的长期职业目标是成为一名独立的 老年吞咽困难研究者和学术带头人。她已经为此奠定了重要的基础 目标，发展密切的导师关系，获得广泛的研究，临床，管理和领导 技能和经验，作为PI的多个机构和基金会赠款。 导师：为了实现她的目标，Rameau博士聘请了一个特殊的跨学科团队， 导师，他们是非常成功的，NIH资助的研究人员和公认的领导者和专家， 各自领域她的导师团队包括世界基督教医学会联合主任Mark Lachs博士， 老年病学，迈克尔·斯图尔特博士，WCM耳鼻咽喉-头颈外科系主任， 博士Sara Czaja，WCM老龄化和行为研究中心主任。 研究：与康奈尔鸟类学实验室的生物声学家合作，我们的研究，无论是在一个 切除的狗模型和人类试点研究表明，传统的声音声学指标和 有和没有吸入风险的患者之间咳嗽声的重要方式不同。这些特点 可以作为吞咽困难的生物标志物，以及对患者数字记录的声音进行声学分析， 咳嗽具有有效区分正常和异常吞咽的潜力。包括多 特征，如那些专门评估口腔脆弱，并结合结果可能会增加 吞咽功能障碍识别的准确性，特别是在更容易发生吞咽障碍的AD/ADRD老年人中 沉默的渴望。将非线性方法和机器学习添加到传统的声学分析可以 也提高了准确性。Rameau博士建议使用这些技术来开发临床决策支持 一种工具，它结合了对患者记录的语音和咳嗽的多个特征的分析，以确定 的野心风险。为了增加在床边使用这个工具的可能性，她将修改它以进行录音 作为移动的应用程序的一部分。完成本研究后，她计划提交R 01 为了前瞻性地检查临床决策支持工具在大型多中心RCT中的性能， 不同的老年人群体。

PROJECT SUMMARY/ABSTRACT The over-arching goals of Dr, Rameau's Beeson application are (1) to develop an easy-to-use, highly accurate bedside clinical decision support tool to identify swallowing dysfunction in older adults using analysis of features of their recorded voice, cough and speech, and (2) to become a leader in the nascent field of geriatric otolaryngology with a focus on management of speech and swallowing issues in older adults with Alzheimer's disease and related dementias (AD/ADRD). Candidate: The applicant, Dr. Anaïs Rameau, is an otolaryngologist at Weill Cornell Medical College (WCMC) who has demonstrated significant research ability and clinical interest in geriatric otolaryngology, especially in the care of older adults with dysphagia. Dr. Rameau's long-term career goal is to become an independent researcher and academic leader in geriatric dysphagia. She already laid significant foundations towards this goal, developing close mentorship relationships, gaining broad research, clinical, management and leadership skills, and experience as PI on multiple institutional and foundation grants. Mentors: To achieve her objectives, Dr. Rameau has engaged an exceptional, transdisciplinary team of mentors, who are highly successful, NIH-funded investigators and well-recognized leaders and experts in their respective fields. Her mentorship team includes Dr. Mark Lachs, Co-Director of the WCMC Division of Geriatrics, Dr. Michael Stewart, Chair of the WCM Department of Otolaryngology – Head & Neck Surgery, and Dr. Sara Czaja, Director of the Center on Aging and Behavioral Research at WCM. Research: In collaboration with bio-acousticians at the Cornell Lab of Ornithology, our research, both in an excised canine model and a human pilot study, has suggested that conventional acoustic metrics of voice and cough sound differ in important ways between patients with and without aspiration risk. These characteristics may serve as biomarkers of dysphagia, and acoustic analysis of the patient's digitally recorded voice and cough has the potential to effectively differentiate between normal and abnormal swallowing. Including multiple characteristics, such as those specifically evaluating oral frailty, and combining the results may increase accuracy of swallowing dysfunction identification, especially in older adults with AD/ADRD who are more prone to silent aspiration. Adding non-linear methods and machine learning to conventional acoustic analysis may also improve accuracy. Dr. Rameau proposes to use these techniques to develop a clinical decision support tool that incorporates analysis of multiple characteristics of a patient's recorded voice and cough to determine their aspiration risk. To increase the potential for use of this tool at the bedside, she will modify it for recordings on a smartphone as part of a mobile application. Upon completion of this research, she plans to submit an R01 to prospectively examine the performance of the clinical decision support tool in a multi-site RCT in large, diverse cohort of older adults.