Otitis Media Diagnosis and Treatment

中耳炎的诊断和治疗

• 批准号: 10532376
• 负责人: Stephen A Boppart
• 金额: $ 55.27万
• 依托单位: MEDICAL COLLEGE OF WISCONSIN
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10532376
• 关键词: Acute; Affect; Ambulatory Care Facilities; Antibiotics; Audiology; Child; Childhood; Chronic; Clinic; Data; Data Set; Decision Making; Developmental Delay Disorders; Diagnosis; Disease; Ear; Earache; Education; Health Expenditures; Image; Infection; Informed Consent; Life; Medical; Microbial Biofilms; Morbidity - disease rate; Operative Surgical Procedures; Optical Coherence Tomography; Otitis Media; Otitis Media with Effusion; Otolaryngologist; Otolaryngology; Otoscopy; Pathology; Patient observation; Patients; Prevalence; Prevention; Primary Care; Public Health; Recording of previous events; Research; Resolution; Resources; Speech; Technology; Time; Tympanic membrane; Tympanometry; United States; accurate diagnosis; antimicrobial; automated algorithm; childhood hearing loss; clinical decision-making; comparative; cost; diagnostic accuracy; diagnostic algorithm; diagnostic tool; ear infection; effusion; image processing; improved; machine learning algorithm; middle ear; new technology; pediatric patients; pediatrician; primary care clinic; ultrasound; Acute; Affect; Ambulatory Care Facilities; Antibiotics; Audiology; Child; Childhood; Chronic; Clinic; Data; Data Set; Decision Making; Developmental Delay Disorders; Diagnosis; Disease; Ear; Earache; Education; Health Expenditures; Image; Infection; Informed Consent; Life; Medical; Microbial Biofilms; Morbidity - disease rate; Operative Surgical Procedures; Optical Coherence Tomography; Otitis Media; Otitis Media with Effusion; Otolaryngologist; Otolaryngology; Otoscopy; Pathology; Patient observation; Patients; Prevalence; Prevention; Primary Care; Public Health; Recording of previous events; Research; Resolution; Resources; Speech; Technology; Time; Tympanic membrane; Tympanometry; United States; accurate diagnosis; antimicrobial; automated algorithm; childhood hearing loss; clinical decision-making; comparative; cost; diagnostic accuracy; diagnostic algorithm; diagnostic tool; ear infection; effusion; image processing; improved; machine learning algorithm; middle ear; new technology; pediatric patients; pediatrician; primary care clinic; ultrasound

PROJECT SUMMARY/ABSTRACT Otitis media (OM) is the most common diagnosis in pediatric patients seen for illness in the United States (1,2), affects 90% of all children (3,4) and is the most common indication for antimicrobial therapy and surgery (5) in young children. Despite many attempts to improve diagnosis, treatment, and prevention, OM continues its highly prevalent impact on children and substantial ongoing morbidity (1,3,6-30). OM continues as the most common cause of hearing loss (HL) in children and leads to speech, educational and other developmental delays (31-37). OM causes life-threatening complications (22,27) and is expensive, resulting in over $5 billion annually in U.S. health care expenditures (3,38). Despite the prevalence and difficulties with OM, diagnostic accuracy to allow appropriate treatment is lacking, leading to misplaced resources in treating OM. This proposal builds on our central hypothesis that enhanced diagnostic tools, specifically, optical coherence tomography (OCT), will yield improved diagnosis and lead to reduced need for antibiotics to treat acute OM, reduced surgical interventions for chronic otitis media, and overall fewer complications and cost associated with this disease. In this proposal we will explore three specific aims. The first aim, part A, we will perform a comparative assessment of middle ear (ME) pathology using pneumatic otoscopy (PO) and optical coherence tomography (OCT) in pediatric patients that present to a primary care clinic with complaints of otalgia (ear pain) or OM, with the hypothesis that OCT added to standard PO will improve diagnostic accuracy and reduce overall antibiotic prescriptions. In part B of this aim, a comparative assessment of ME pathology using PO along with audiology/tympanometry (TY) and OCT will be performed in pediatric patients that present to the pediatric otolaryngology clinic with a referral for chronic otitis media with effusion (OME), with the hypothesis that OCT added to standard PO and TY will improve diagnostic accuracy and reduce overall need for surgery in patients with OME. In the second aim, using the OCT images captured in the previous aim, we will develop image processing and machine learning algorithms for automated identification of effusions and biofilms in OCT image data to augment OM diagnosis for medical decision making. Finally, using the OCT images captured previously, along with our machine learning algorithms, we will establish OCT B-mode and M-mode image-based features that predict the resolution or persistence of middle ear effusions over time. Collectively, this project will demonstrate how these advances in diagnostic tools and algorithms will improve diagnosis and provide added information for clinical decision making in the management of OM.

项目摘要/摘要 中耳炎（OM）是美国疾病患儿科患者中最常见的诊断（1,2）， 影响所有儿童的90％（3,4），是抗菌治疗和手术的最常见指征（5） 孩子们。尽管有许多尝试改善诊断，治疗和预防的尝试，但OM仍在继续 对儿童的普遍影响和持续的发病率（1,3,6-30）。 OM继续是最常见的原因 儿童听力损失（HL），并导致言论，教育和其他发展延迟（31-37）。 om 引起威胁生命的并发症（22,27），价格昂贵，每年在美国卫生中产生超过50亿美元 护理支出（3,38）。尽管OM的流行率和困难，但诊断准确性以允许适当 缺乏治疗，导致在治疗OM方面的资源放错了位置。该建议建立在我们的中央 假设增强的诊断工具，特别是光学相干断层扫描（OCT），将产生 改善诊断并导致抗生素治疗急性OM的需求减少，减少手术 慢性中耳炎的干预措施以及与该疾病有关的总体并发症和成本较少。 在此提案中，我们将探讨三个具体目标。第一个目的是A部分，我们将进行比较 使用气动耳镜（PO）和光学相干断层扫描评估中耳（ME）病理 （OCT）在儿科患者中，出现在初级保健诊所中，有耳痛（耳痛）或OM， OCT添加到标准PO的假设将提高诊断准确性并降低总体抗生素 处方。在此目标的B部分中，使用PO对ME病理学的比较评估以及 听力学/鼓膜法（TY）和OCT将在儿科患者中进行 耳鼻喉科诊所，带有慢性中耳炎的转诊（OME），并假设OCT 添加到标准PO和TY中可以提高诊断准确性并减少患者的总体手术需求 与ome。在第二个目标中，使用上一个目标中捕获的OCT图像，我们将开发图像 在OCT图像中自动鉴定积液和生物膜的加工和机器学习算法 数据以增强OM诊断以进行医疗决策。最后，使用之前捕获的OCT图像， 与我们的机器学习算法一起，我们将建立OCT B模式和基于M模式的功能 这可以预测中耳积液随时间的分辨率或持续性。总体而言，这个项目将 证明这些诊断工具和算法中这些进步如何改善诊断并提供添加的诊断 有关OM管理中临床决策的信息。