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Outcomes of Prolonged Mechanical Ventilation

Outcomes of Prolonged Mechanical Ventilation
长期机械通气的结果
批准号:
6419083
负责人:
Shannon S Carson
金额:
$12.52万
依托单位国家:
美国
项目类别:
财政年份:
2002
资助国家:
美国
项目状态:
已结题
起止时间:
2002-01-01 至 2006-11-30

项目摘要

项目成果

Shannon S Carson的其他基金

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中文摘要
翻译
描述(由申请人提供): 香农·卡森博士的职业目标包括成为一名多产的 将进行临床研究和结果的独立调查员 涉及危重病人的研究。为了获得必要的背景知识, 他将参加北卡罗来纳大学的临床研究会议和研讨会 医学院,他将完成北卡罗来纳大学公共学院的课程 与临床流行病学、研究设计、数据分析和 以病人为中心的负责任的研究行为。此外,他还将 在Tim Carey博士的指导下完成一个为期5年的研究项目。 这项研究的主要目标是开发一年的预测模型 生存和功能状态。次要目标将是描述 以患者为导向的长期结果,包括健康状况和质量 生活。需要长时间机械通气的患者占10%至10% 20%的ICU患者,消耗高达总重症监护病房(ICU)的37% 资源。幸存者通常年事已高,离开医院时带着 许多悬而未决的医疗问题。初步数据显示,一年期 存活率低至23%。随着我们年龄的增长,这些患者的数量将会增加 人口继续遇到生命维持疗法的进步。它是 重要的是确定这些先进的疗法是否转化为可接受的 长期结果。本研究的具体目标包括:1)评估一年 需要长期机械治疗的患者的生存和功能状态 急性疾病后的呼吸机。2)确定以下项目的健康状况和质量 生还者的生活。3)开发并验证一年的预测模型 生死存亡。3)开发并验证了独立品牌的预测模型 功能状态。 这项研究将招募200名成年患者的前瞻性队列 在大型三级医疗机构进行至少21天的机械通气 中间。患者将在住院期间和通过 第二年。电话采访将分别进行3个月、6个月和 研究登记后12个月,以确定患者的生存、健康状况、 和感知到的生活质量。使用在第21天测量的变量 机械通风,预测模型将开发一年 生存和独立的功能状态。将对模型进行验证 在100名类似的患者中进行前瞻性研究,医生估计 一年的存活率和功能状态将与模型估计进行比较。 了解这些结果将有助于临床医生在提供咨询时 患者和他们的家人关于适当水平的积极护理 并帮助他们了解资源和支持的类型 需要在出院时进行最佳恢复。此外,这些数据将 通知未来的队列研究和随机对照试验,旨在 改善这一不断增长的患者群体的预后。
英文摘要
DESCRIPTION (provided by applicant): The career goals of Dr. Shannon Carson include becoming a productive independent investigator who will conduct clinical research and outcomes studies involving critically ill patients. To gain the necessary background, he will participate in clinical research conferences and seminars at the UNC School of Medicine, and he will complete courses in the UNC School of Public Health that pertain to clinical epidemiology, study design, data analysis, and the responsible conduct of patient-oriented research. In addition, he will complete a 5-year research project under the mentorship of Dr. Tim Carey. The primary objective of the study is to develop predictive models for one-year survival and functional status. Secondary objectives will be to describe long-term patient oriented outcomes including health status and quality of life. Patients who require prolonged mechanical ventilation account for 10 to 20% of ICU patients and consume up to 37% of total intensive care unit (ICU) resources. Survivors are often of advanced age and leave the hospital with numerous unresolved medical problems. Preliminary data indicate that one-year survival is as low as 23%. These patients will increase in number as our aging population continues to encounter advances in life sustaining therapies. It is important to determine if these advanced therapies translate into acceptable long-term outcomes. Specific Aims of this study include: 1) Assess one-year survival and functional status for patients who require prolonged mechanical ventilation after acute illness. 2) Determine Health Status and Quality of Life for survivors. 3) Develop and validate a prediction model for one-year survival. 3) Develop and validate a prediction model for independent functional status. This study will enroll a prospective cohort of 200 adult patients requiring mechanical ventilation for at least 21 days at a large tertiary care medical center. Patients will be followed during hospitalization and through the subsequent year. Telephone interviews will be conducted 3 months, 6 months and 12 months after study enrollment to determine patient survival, health status, and perceived quality of life. Using variables measured on day 21 of mechanical ventilation, predictive models will be developed for one-year survival and independent functional status. Models will be validated prospectively in a cohort of 100 similar patients, and physician estimates of one-year survival and functional status will be compared to model estimates. Knowledge of these outcomes would be helpful to clinicians as they counsel patients and their families regarding appropriate levels of aggressive care and help them understand the types of resources and support that will be needed for optimal recovery upon discharge. In addition, these data will inform future cohort studies and randomized controlled trials designed to improve outcomes for this growing patient population.
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