Assessment and Prediction of Functional Status

功能状态的评估和预测

• 批准号: 7176809
• 负责人: JOHN TORREY BERGER
• 金额: $ 61.52万
• 依托单位: CHILDREN'S RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-05-01 至 2009-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7176809
• 关键词: Accounting; Activities of Daily Living; Adaptive Behaviors; Address; Admission activity; Adult; Age; Blood Coagulation Disorders; Blood Glucose; Cardiac; Cardiovascular system; Case Mixes; Cerebrum; Cessation of life; Child; Childhood; Chronic; Classification; Clinical; Critical Care; Data; Databases; Development; Diagnosis; Economics; Follow-Up Studies; Functional disorder; Future; Hospitalization; Hospitals; Individual; Infant; Injury; Intensive Care; Intracranial Hemorrhages; Kidney; Logistics; Measures; Medicine; Metabolic; Methods; Modeling; Morbidity - disease rate; National Institute of Child Health and Human Development; Nervous System Trauma; Neurologic; None or Not Applicable; Outcome; Outcome Measure; Outcome Study; Patients; Pediatrics; Performance; Physiological; Quality of Care; Regression Analysis; Relative (related person); Risk; Risk Adjustment; Secondary to; Severities; Severity of illness; Social Impacts; Telephone; Time; Validation; age group; base; bone healing; cost; design; disability; follow-up; functional disability; functional status; improved; instrument; mortality; neonatal hypoxic-ischemic brain injury; respiratory; success; tool

DESCRIPTION (provided by applicant): This proposal addresses two major needs of Pediatric Intensive Care. A). PICUs need a reliable, rapid, and quantitative assessment of functional status for large morbidity studies. Current methods are too time consuming and/or not applicable to infants and young children. Aim 1 is to validate a rapid and reliable measure of functional status applicable to all PICU ages and suitable for large morbidity studies. The Functional Disability Scale (FDS), a new assessment tool (10 domains with 42 objective, quantitative, easily & rapidly assessed items) has excellent pilot data. The FDS will be validated against the Vineland Adaptive Behavior Scale (VABS) and revised to better represent the relative severity of the individual items Linear regression analysis will utilize 364 patients for estimation and 121 for validation. Classification matrices will be used to choose a cutpoint for low functional status for use in Aim 2. 200 of these patients will have 6-month and 12-month telephone follow-up for FDS determination, enabling us to examine the relationship between hospital discharge status and 6 and 12 month status. B) PICUS have excellent severity measures calibrated to mortality, but there have been no serious efforts to relate ICU physiologi instability to morbidity development. Aim 2 is to develop a predictor of 3 PICU outcome states: death, survival with low functional status, and survival with adequate functional status. This will enable long-term functional status studies and costs, new quality assessments methods, and improved risk adjustment. Pilot data is very encouraging. This method would be a paradigm shift in severity of illness studies. Trichotomous logistic regression analysis will be used to develop the predictor (3800 for estimation, 1267 for validation). Independent variables include PRISM III, diagnoses, and other case-mix variables. Performance assessment will include overall performance assessment, AUC's, goodness-of-fit, and classification matrices.

描述（由申请人提供）： 该提案解决了小儿重症监护的两个主要需求。一个）。 Picus需要对大型发病率研究的功能状态进行可靠，快速和定量的评估。当前的方法过于耗时和/或不适用于婴儿和幼儿。目的1是验证适用于所有PICU年龄的功能状态的快速可靠度量，适用于大型发病率研究。功能障碍量表（FDS）是一种新的评估工具（10个具有42个目标，定量，易于评估的项目的域）具有出色的试点数据。 FD将对Vineland自适应行为量表（VABS）进行验证，并修订以更好地表示单个项目线性回归分析的相对严重性，将利用364名患者进行估算，而121患者进行验证。分类矩阵将用于为AIM 2使用低功能状态的切口。这些患者中有200个将进行6个月和12个月的电话随访，以进行FDS确定，从而使我们能够检查医院出院状态与6个月和12个月状态之间的关系。 b）PICU具有校准死亡率的极好的严重程度措施，但是没有做出严重的努力将ICU Physiologi不稳定与发病发展联系起来。目标2是开发3个PICU结果状态的预测因子：死亡，功能较低的生存以及具有足够功能状态的生存。这将使长期功能状态研究和成本，新的质量评估方法以及改善风险调整。飞行员数据非常令人鼓舞。这种方法将是疾病研究严重程度的范式转移。二元逻辑回归分析将用于开发预测变量（估计为3800，验证1267）。自变量包括Prism III，诊断和其他病例混合变量。绩效评估将包括整体绩效评估，AUC，拟合度和分类矩阵。