Sequential Modeling for Prediction of Periodontal Diseases: an intra-Collaborative Practice-based Research study (ICPRS)
Sequential Modeling for Prediction of Periodontal Diseases: an intra-Collaborative Practice-based Research study (ICPRS)
批准号:
10755010
负责人:
Marisol Tellez Merchan
金额:
$65.28万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-09-13 至 2028-06-30
关键词:
16S ribosomal RNA sequencingAddressAdultAffectAmericanApplications GrantsArtificial IntelligenceAssessment toolBehavioralBiological MarkersBiometryCaringClassificationClinicalClinical Decision Support SystemsClinical ResearchCohort StudiesCollaborationsConsentContinuity of Patient CareCoupledDataData AnalysesData SetDecision MakingDentalDental EducationDental EpidemiologyDental General PracticeDental SchoolsDental StudentsDentistsDevelopmentDiseaseDisease ProgressionDisease modelEarly DiagnosisElectronic Health RecordFacultyFundingGenesGoalsGrantHealthHealth StatusHealthcareIncidenceIndividualKnowledgeLaboratoriesLearningMachine LearningMedicalMedical HistoryMedical RecordsMetagenomicsModelingNested Case-Control StudyNursing FacultyOralOral healthPainPathway interactionsPatient Self-ReportPatientsPennsylvaniaPerformancePeriodontal DiseasesPeriodontitisPhysiciansPopulationPostdoctoral FellowPractice based researchPreventionProspective, cohort studyPublic HealthPublic Health InformaticsQuality of lifeRecordsReportingResearchResearch ActivityResearch Project GrantsResearch SupportResolutionRisk AssessmentRisk FactorsSalivaSalivarySamplingSchool DentistrySchoolsScienceShotgunsStatistical ModelsStudentsTeacher Professional DevelopmentTestingTimeTooth LossTrainingUniversitiescertificate programclinical practicecollegediagnostic accuracydisabilitydisease diagnosisdisorder controldisorder preventiondisorder riskdysbiosisempowermentimprovedindexinginnovationmedical schoolsmeetingsmetagenomic sequencingmicrobialmicrobial signaturemicrobiomemicrobiome analysismultiple data sourcesnovelnovel strategiesoral microbiomepatient oriented researchpotential biomarkerpractice-based research networkpre-doctoralpredictive markerpredictive modelingprogramspsychologicrecruitresearch studyresponserisk prediction modelsaliva sampleskillssocial determinantsstudent mentoringstudent trainingsubgingival microbiometool
中文摘要
总结
的
协同
ICPRS
临床导向
博士前/博士后
施用
发展
目前的提案标题为“用于预测牙周病的顺序建模:一个新的,
根据RFA-DE-23-012开发了基于实践的研究(ICPRS)。的
将努力在4个组成部分中制定各种任务。在组件1中,我们寻求培训10名
坦普尔大学科恩伯格牙科学院(TUKSoD)的教师和10名
学生在应用临床l研究通过提供研究生证书课程
公共卫生学院(CPH)关于促进技能
在以病人为导向的应用研究中,
一
. 15学分证书将重点
.在第二部分,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
用于执行本提案的组件4。我们提出的项目是合作开发的,
具有牙周病学、普通和口腔流行病学、口腔微生物组、健康
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的实时医疗记录到牙周病(PD)的管理
交易所(PA HSX)。在组件3中,我们的目标是扩大以临床为导向的教师参与赠款资助
在年度研究日和国家研究会议上,
教师和学生的指导伙伴关系,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。这一部分的目标如下:
开发临床决策工具,利用来自TUKSoD和PA的匹配医疗-牙科患者数据集
HSX EHR记录。Aim 1a将重点开发医疗连续性护理记录(CCR),
患者的最新医疗健康指标,可用于在牙科学校提供护理。使用
牙科患者的匹配记录,Aim 1b将为PD建立一个AI增强的预测模型。aim 2将构建
根据Aim 1b的发现,评估龈下和唾液微生物组作为额外
PD发病率和进展的预测因素。目标2a将验证一个生态失调指数,适用于两个龈下
在队列研究中,牙菌斑和唾液样本作为PD的预测因子,而Aim 2b将识别潜在的高
通过巢式病例对照研究,确定PD进展的唾液/斑块宏基因组生物标志物。的
拟议的应用建立在TUKSoD先前进行的研究基础上,旨在增加
临床导向的教师和前/博士后牙科学生在学校的研究活动的参与,
再加上包括健康信息学在内的应用临床研究培训,为进一步发展
研究口腔教育以及促进教师专业发展,扩大研究
学术劳动力,并提供机会进行学生指导的实践为基础的研究。
英文摘要
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.
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