Sequential Modeling for Prediction of Periodontal Diseases: an intra-Collaborative Practice-based Research study (ICPRS)

摘要 这个 协作性 ICPRS 以临床为导向 博士后/博士后 管理的 发展 当前的提案题为“用于牙周病预测的序贯建模：一个I NTRA- 以实践为基础的研究性学习“是根据RFA-DE-23-012制定的。这个 将寻求制定4个组成部分的各种任务。在组件1中，我们寻求培训10个 坦普尔大学科恩伯格牙科学院(TUKSoD)和十名教师 应用临床专业研究生毕业证书制对L的研究 由公共卫生学院(CPH)介绍促进技能 在以患者为中心的应用研究中 一个 。15个学分证书将集中于 。在组件2中，我们的目标是加强协作 TUKSoD、CPH和医学院之间的教职员工培训和整体研究支持 执行本提案的构成部分4。我们提议的项目是由 有牙周学、普通和口腔流行病学、口腔微生物组、健康等专业背景的个人 信息学、生物统计学和公共卫生，以及将协助提取相关医疗指标的医生 从宾夕法尼亚健康共享的实时医疗记录到牙周病(PD)的管理 交换(PA HSX)。在组成部分3中，我们的目标是扩大以临床为导向的教员参与助学金资助的范围 研究活动，在年度研究日和国家研究会议上，增加 师生指导伙伴关系，以开展小规模研究项目。最后，在组件4中，我们 将使用机器学习方法开发帕金森病发生和进展的纵向预测模型 和微生物组/元基因组测序策略。这一构成部分有以下目标：AIM1寻求 开发临床决策工具，利用来自TUKSoD和PA的匹配的医疗-牙科患者数据集 HSX EHR记录。Aim1a将专注于开发医疗连续性护理记录(CCR)，该记录将提供 患者的最新医疗健康指标，可用于提供牙科学校的护理。vbl.使用 牙科患者的匹配记录，Aim1b将为PD构建AI赋能预测模型。AIM2将构建 关于Aim1b的发现，以评估作为补充的龈下和唾液微生物群的潜力 帕金森病发生和进展的预测因素。Aim 2a将验证一项适用于两个牙龈下的生物失调指数 斑块和唾液样本在一项队列研究中作为帕金森病的预测因子，而Aim2b将确定潜在的高风险 通过嵌套式病例对照研究，PD进展的分辨率、唾液/斑块元基因组生物标记物。这个 拟议的应用程序建立在TUKSoD进行的先前研究的基础上，旨在提高 面向临床的教师和牙科博士后/博士后学生参与学校的研究活动， 再加上包括卫生信息学在内的应用临床研究培训，开辟了一条新的途径，以进一步 研究牙科教育以及促进教师专业发展，扩大研究 教师队伍，并提供机会进行学生指导的实践性研究。

SUMMARY The Collaborative ICPRS clinically-oriented predoctoral/postdoctoral administered development current proposal titled “Sequential Modeling for Prediction of Periodontal Disea ses: An I ntra- Practice-Based Research Study ( ICPRS)” is developed in response to RFA-DE-23-012 . The will seek to develop various tasks in 4 component sections. In Component 1 , we seek to train 10 faculty from Temple University Kornberg School of Dentistry (TUKSoD) nd ten students in Applied Clinica l Research by offering a graduate certificate program by the College of Public Health (CPH) on facilitating skills in applied patient-oriented research a . The 15-credit certificate will focus . In Component 2, we aim to strengthen collaborations between TUKSoD, CPH and the Medical School for faculty and student training, and overall research support for the execution of Component 4 of this proposal. Our proposed project was collaboratively developed by individuals with backgrounds in Periodontology, General and Oral Epidemiology, Oral Microbiome, Health Informatics, Biostatistics and Public Health, and Physicians who will assist in extracting medical metrics relevant to management of periodontal diseases (PD) from real-time medical records in the Pennsylvania Health Share Exchange (PA HSX). In Component 3, we aim to expand clinically-oriented faculty participation in grant funded research activities, in the annual research day, and in national research meetings by increasing the number of faculty-student mentoring partnerships to conduct small-scale research projects. Finally, in Component 4, we will develop longitudinal predictive models of PD incidence and progression using machine learning approaches and microbiome/metagenomic sequencing strategies. This component has the following aims: Aim1 seeks to develop clinical decision tools that utilize matched medical-dental patient datasets from TUKSoD and the PA HSX EHR records. Aim1a will focus on developing a Medical Continuity of Care Record (CCR) that will provide patients' up-to-date medical health metrics that can be used in the provision of care at the dental school. Using dental patient's matched records, Aim1b will build an AI Empowered Prediction Model for PD. Aim2 will build on findings from Aim1b to assess the potential of the subgingival and salivary microbiomes as additional predictors of PD incidence and progression. Aim 2a will validate a dysbiosis index, applied to both subgingival plaque and saliva samples, as a predictor of PD in a cohort study, while Aim2b will identify potential high resolution, salivary/plaque metagenomic biomarkers of PD progression via a nested case-control study. The proposed application builds on prior research conducted at TUKSoD and is directed towards increasing participation of clinically-oriented faculty and pre/postdoctoral dental students in the school's research activities, coupled with training in Applied Clinical Research including health informatics, opening a new pathway to further research in dental education as well as promote faculty professional development, expand the research academic workforce, and provide opportunities to conduct student-mentored practice-based research.