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)

• 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
• 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

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 ICPRS 面向临床 前/博士后 管理 发展 当前的提案，标题为“用于预测牙周疾病的顺序建模： 基于实践的研究（ICPRS）是针对RFA-DE-23-012。 将寻求在4个组件部分中制定各种任务。在组件1中，我们试图训练10 Temple University Kornberg牙科学院（Tuksod）的教职员工ND十 通过提供研究生证书课程的应用临床研究的学生 公共卫生学院（CPH）促进技能 在应用的以患者为导向的研究中 一个 。 15学分证书将集中 。在组件2中，我们旨在加强合作 在Tuksod，CPH和医学院进行教职和学生培训，以及整体研究支持 为执行本提案的组件4。我们提议的项目是由 具有牙周病学背景，一般和口腔流行病学，口腔微生物组的个人 信息学，生物统计学和公共卫生以及将有助于提取医学指标相关的医生 从宾夕法尼亚州健康份额的实时病历中的牙周病管理（PD）管理 Exchange（PA HSX）。在组件3中，我们旨在扩大以临床为导向的教师参加资助的赠款 在年度研究日以及在国家研究会议上的研究活动通过增加的数量 教师学生的心理伙伴关系，以进行小规模的研究项目。最后，在组件4中，我们 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 和微生物组/宏基因组测序策略。该组件具有以下目的：AIM1试图 开发使用Tuksod和PA的临床决策工具，该工具使用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记录（CCR），以提供 患者的最新医疗保健指标可用于在牙科学校提供护理中。使用 牙科患者的匹配记录，AIM1B将为PD建立AI授权的预测模型。 AIM2将构建 关于AIM1B的发现，以评估subgingival和唾液微生物组的潜力 PD发生率和进展的预测因素。 AIM 2A将验证一个可症状指数，应用于两个尺寸 斑块和唾液样品，作为队列研究中PD的预测因子，而AIM2B将识别潜在的高 通过嵌套的病例对照研究的分辨率，唾液/斑块宏基因组生物标志物。这 拟议的申请是基于在Tuksod进行的先前研究的基础，并致力于增加 参与临床导向的教师和学前/博士后牙科学生参加学校的研究活动， 加上应用临床研究的培训，包括健康信息，开辟了一条新的途径 牙科教育研究以及促进教师专业发展，扩大研究 学术劳动力，并提供了开展基于学生的实践研究的机会。