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

牙周病预测的序列模型：基于内部协作实践的研究 (ICPRS)

基本信息

批准号：
10755010
负责人：
Marisol Tellez Merchan
金额：
$ 65.28万
依托单位：
TEMPLE UNIV OF THE COMMONWEALTH
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-09-13 至 2028-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10755010
关键词：
16S ribosomal RNA sequencing Address Adult Affect American Applications Grants Artificial Intelligence Assessment tool Behavioral Biological Markers Biometry Caring Classification Clinical Clinical Decision Support Systems Clinical Research Cohort Studies Collaborations Consent Continuity of Patient Care Coupled Data Data Analyses Data Set Decision Making Dental Dental Education Dental Epidemiology Dental General Practice Dental Schools Dental Students Dentists Development Disease Disease Progression Disease model Early Diagnosis Electronic Health Record Faculty Funding Genes Goals Grant Health Health Status Healthcare Incidence Individual Knowledge Laboratories Learning Machine Learning Medical Medical History Medical Records Metagenomics Modeling Nested Case-Control Study Nursing Faculty Oral Oral health Pain Pathway interactions Patient Self-Report Patients Pennsylvania Performance Periodontal Diseases Periodontitis Physicians Population Postdoctoral Fellow Practice based research Prevention Prospective, cohort study Public Health Public Health Informatics Quality of life Records Reporting Research Research Activity Research Project Grants Research Support Resolution Risk Assessment Risk Factors Saliva Salivary Sampling School Dentistry Schools Science Shotguns Statistical Models Students Teacher Professional Development Testing Time Tooth Loss Training Universities certificate program clinical practice college diagnostic accuracy disability disease diagnosis disorder control disorder prevention disorder risk dysbiosis empowerment improved indexing innovation medical schools meetings metagenomic sequencing microbial microbial signature microbiome microbiome analysis multiple data sources novel novel strategies oral microbiome patient oriented research potential biomarker practice-based research network pre-doctoral predictive marker predictive modeling programs psychologic recruit research study response risk prediction model saliva sample skills social determinants student mentoring student training subgingival microbiome tool

项目摘要

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.

概括这协作性 ICPRS 临床导向博士前/博士后管理的发展目前的提案题为“牙周病预测的序列模型：一种内部模型” 基于实践的研究（ICPRS）”是根据 RFA-DE-23-012 制定的。将寻求在 4 个组成部分中开发各种任务在第 1 部分中，我们寻求培训 10 名。天普大学科恩伯格牙科学院 (TUKSoD) 的十名教师通过提供研究生证书课程来从事应用临床研究的学生由公共卫生学院 (CPH) 颁发的促进技能以患者为导向的应用研究一个 .15个信用证书将重点在第二部分中，我们的目标是加强合作。 TUKSoD、CPH 和医学院之间的教师和学生培训以及整体研究支持用于执行本提案的第 4 部分。具有牙周病学、普通和口腔流行病学、口腔微生物组、健康背景的个人信息学、生物统计学和公共卫生以及协助提取相关医疗指标的医生从宾夕法尼亚州健康共享中的实时医疗记录到牙周病 (PD) 的管理交流 (PA HSX) 在第 3 部分中，我们的目标是扩大以临床为导向的教师参与资助的情况。通过增加研究活动、年度研究日和国家研究会议的数量最后，在第四部分中，我们建立了师生指导伙伴关系来开展小型研究项目。将使用机器学习方法开发 PD 发病率和进展的纵向预测模型该组件具有以下目标： Aim1 旨在开发利用 TUKSoD 和 PA 匹配的医疗牙科患者数据集的临床决策工具 HSX EHR 记录 Aim1a 将专注于开发医疗连续性护理记录 (CCR)，以提供患者的最新医疗健康指标可用于在牙科学校提供护理。牙科患者的匹配记录，Aim1b 将为 Aim2 构建一个人工智能赋能的 PD 预测模型。根据 Aim1b 的研究结果评估龈下和唾液微生物组作为额外的潜力目标 2a 将验证应用于龈下的菌群失调指数。牙菌斑和唾液样本作为队列研究中 PD 的预测因子，而 Aim2b 将识别潜在的高通过巢式病例对照研究解决 PD 进展的唾液/牙菌斑宏基因组生物标志物。拟议的应用程序建立在 TUKSoD 先前进行的研究的基础上，旨在增加临床教师和博士前/博士后牙科学生参与学校的研究活动，加上包括健康信息学在内的应用临床研究培训，开辟了进一步发展的新途径牙科教育研究以及促进教师专业发展，扩大研究范围学术人员，并提供进行学生指导的基于实践的研究的机会。