Improving the Differential Diagnosis of Pneumonia and Congestive Heart Failure Us

改善肺炎和充血性心力衰竭的鉴别诊断

• 批准号: 7434091
• 负责人: RAYMOND L H MURPHY
• 金额: $ 15万
• 依托单位: STETHOGRAPHICS, INC.
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-01 至 2009-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7434091
• 关键词: Acoustics; Algorithms; Antibiotics; Area; Asthma; Biological Neural Networks; Breathing; Categories; Chronic Obstructive Airway Disease; Classification; Computer software; Condition; Congenital Heart Defects; Congestive Heart Failure; Count; Crackles; Data; Databases; Development; Diagnosis; Diagnostic; Differential Diagnosis; Disease; Diuretics; Electronics; Equipment; Expert Systems; Goals; Grant; Heart Sounds; Heart failure; Heart murmur; Home environment; Hospital Nursing; Intensive Care Units; Lead; Legal patent; Lung; Lung diseases; Medical; Methods; Nurses; Nursing Homes; Oils; Patient Care; Patient Monitoring; Patients; Pattern Recognition; Personal Digital Assistant; Phase; Physicians' Offices; Pneumonia; Public Health; Pulmonary Fibrosis; Pulmonary Heart Disease; Rate; Research; Rhonchus; Risk; Shipping; Ships; Source; Specificity; Stethoscopes; System; Techniques; Technology; Telemedicine; Uncertainty; United States; United States Food and Drug Administration; Visiting Nurse; Wheezing; base; clinically significant; computerized; improved; interstitial; noninvasive diagnosis; patient home care; sensor; sound; telemetering; transmission process

DESCRIPTION (provided by applicant): Stethographics has developed automated lung and heart sound products, based on 3 granted U.S. patents and 2 FDA approvals. Our Pocket PC based system gathers sounds via a contact sensor in a simple and practical way. The system automatically detects and quantifies crackles, wheezes, rhonchi, squawks and heart murmurs. 3M Littmann, the world} s largest stethoscope company, bundles all E4000 electronic stethoscopes with our Sound Analysis Software. We propose a research plan that will lead to development of a} smart} stethoscope. In addition to extracting sound features like crackle count, wheeze rate, and heart murmur grade, the incorporated neural network algorithms will provide a probable cause of these abnormal sounds such as pneumonia, congestive heart failure, or heart abnormality. We expect the smart stethoscope to find its applications in many settings: in physician's offices, hospitals, nursing homes - essentially everywhere the stethoscope is used. In addition, new areas of exploitation include settings where doctoral expertise or stationary medical equipment is not always available, and nurse is the main source of medical help: on the ships, oil rigs, embassies and home care by visiting nurses. The diagnostic information provided by the smart stethoscope can be used locally or telemetered. We have initiated this research by tackling two common illnesses: pneumonia (PN) and congestive heart failure (CHF). It is estimated that 5 million people in the United States have CHF. Although in many instances the diagnosis of these conditions is easily made, it is not uncommon, particularly in the Intensive Care Unit setting, for it to be unclear as to which illness a patient has. In cases of doubt the patient is often treated for both. Yet diuretics are likely not good for patients with pneumonia in the absence of coexisting heart failure and it is not good practice to subject patients to the risk of antibiotics unnecessarily. Our preliminary results in 151 patients with 2 or more crackles per breath (CHF=70; PN=81) indicate that the crackles differ significantly in these two conditions. Classification algorithms based on crackles features were able to separate the two disorders with a sensitivity of 0.91 and specificity of 0.82. In Phase I we plan to retrospectively study the database of over 1,000 patients using pattern recognition methods in order to develop the expert system that can differentiate PN, CHF, interstitial pulmonary fibrosis (IPF), and normal patients. In Phase II we will expand the system to include diagnosis of asthma, COPD, and cardiac murmurs. In Phase III we will incorporate the expert system into a smart stethoscope. PUBLIC HEALTH RELEVANCE: This research is expected to provide new medical diagnostic software that can be incorporated into a smart stethoscope. The use of the smart stethoscope will be particularly relevant in settings where doctoral expertise or stationary medical equipment is not always available and nurse is the main source of medical help. Automated diagnostics with the smart stethoscope can simplify and improve care for patients in nursing homes, especially by detecting early signs of pneumonia and home monitoring of patients with cardiopulmonary disorders.

描述（由申请人提供）：基于3项授予的美国专利和2次FDA批准，其发明术开发了自动化的肺和心脏声音产品。我们的基于PIC PC的系统以简单且实用的方式通过联系传感器收集声音。该系统会自动检测和量化裂纹，喘息，鼠尾草，尖叫声和心脏杂音。 3M Littmann是世界上最大的听诊器公司，将所有E4000电子听诊器捆绑在我们的声音分析软件中。我们提出了一项研究计划，该计划将导致smart}听诊器的发展。除了提取诸如裂纹计数，喘息率和心脏杂音等级之类的声音功能外，融合的神经网络算法还将提供这些异常声音的可能原因，例如肺炎，充血性心力衰竭或心脏异常。我们希望智能听诊器能够在许多情况下找到其应用：在医师的办公室，医院，疗养院中 - 本质上都在使用听诊器。此外，剥削的新领域包括并非总是可用的博士专业知识或固定医疗设备的设置，护士是医疗帮助的主要来源：在船上，石油钻机，使馆和家庭护理中，拜访护士。智能听诊器提供的诊断信息可在本地使用或遥测。我们通过解决两种常见疾病来开始这项研究：肺炎（PN）和充血性心力衰竭（CHF）。据估计，美国有500万人有瑞士法郎。尽管在许多情况下，这些疾病的诊断很容易做出，但并不少见，尤其是在重症监护病房的设置中，以至于尚不清楚患者患哪种疾病。在有疑问的情况下，患者经常对两者进行治疗。然而，在没有共存心力衰竭的情况下，利尿剂可能对肺炎患者不利，并且不必要地使患者遭受抗生素的风险并不是一个好习惯。我们的初步结果导致151例每次呼吸2个或更多裂纹的患者（CHF = 70; Pn = 81）表明，在这两种情况下，裂纹差异很大。基于裂纹特征的分类算法能够以0.91的灵敏度分离两种疾病，特异性为0.82。在第一阶段，我们计划使用模式识别方法回顾性研究1000多名患者的数据库，以开发可以区分PN，CHF，间质肺纤维化（IPF）和正常患者的专家系统。在第二阶段，我们将扩展系统，包括诊断哮喘，COPD和心脏杂音。在第三阶段，我们将将专家系统纳入智能听诊器。公共卫生相关性：预计这项研究将提供可以纳入智能听诊器的新医学诊断软件。在博士专业知识或固定医疗设备并非总是可用的，护士是医疗帮助的主要来源的环境中，智能听诊器的使用将特别重要。使用智能听诊器自动诊断可以简化和改善疗养院患者的护理，尤其是通过发现肺炎的早期迹象和对心肺疾病患者的家庭监测。