Prediction of Functional Outcomes from Chronic Critical Illness
慢性危重疾病功能结果的预测
基本信息
- 批准号:9158069
- 负责人:
- 金额:$ 66.07万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-09-26 至 2021-07-31
- 项目状态:已结题
- 来源:
- 关键词:AccountingAcuteAddressBiological MarkersCaringCessation of lifeChronicChronic CareClinicalCognitiveCohort StudiesCritical CareCritical IllnessDataDecision AidDecision MakingDependenceEconomic BurdenEconomic FactorsEconomicsEmotionalEnrollmentFamilyFunctional disorderFundingFutureGoalsHealth Care CostsHealth StatusHealthcare SystemsHospitalsImpaired cognitionInjuryInpatientsInterventionInterviewKnowledgeLifeMeasuresMechanical ventilationMedicalMedical RecordsMedical centerMedicineMethodsModelingMulticenter StudiesNatural HistoryOrgan failureOutcomePatientsPhysical FunctionPhysically HandicappedPopulationPsyche structureResearchResearch InfrastructureResourcesRespiratory physiologyRisk FactorsSeveritiesSurvivorsSyndromeTherapeutic InterventionUnited States National Institutes of HealthVital Statusbrain dysfunctionclinical practicecognitive disabilitycognitive functioncohortcopingdisabilityeconomic impactexpectationexperiencefrailtyfunctional declinefunctional disabilityfunctional outcomeshigh riskimprovedindexinginnovationmeetingsmortalityneuromuscularoutcome forecastoutcome predictionpredictive modelingprognosticprospectiveshared decision makingsocialsurrogate decision makersurvival outcomesurvival predictiontool
项目摘要
ABSTRACT
A substantial number of critically ill patients experience persistent organ failure leading to chronic critical illness
(CCI). The majority of these patients die within a year, and many survivors must cope with long-term physical
and cognitive limitations that are often severe. Survival with severe physical and cognitive dysfunction is a
significant clinical, emotional, and economic burden in this population, but little is known about which patients
are at highest risk for physical and cognitive dysfunction. Moreover, although long-term mortality in CCI can be
reliably estimated with a validated mortality prediction model, there is currently no validated method to predict
long-term functional disability for purposes of shared decision making and resource planning. In order to
address these gaps in knowledge, we will conduct the first multicenter prospective cohort study that measures
risk factors for long-term physical and cognitive dysfunction in CCI. Using these risk factors, we will construct a
useful and innovative multi-outcome prognostic model to facilitate shared decision making and resource
planning. Specific aims for the project are as follows:
1. Identify risk factors for long-term physical and cognitive dysfunction for patients with CCI.
2. Develop and validate an innovative multi-dimensional clinical prediction model to predict the combined
outcome of long-term survival and physical and cognitive function in patients with CCI.
We will accomplish these aims by prospectively enrolling 800 patients from 5 diverse medical centers who
have required 7 days of mechanical ventilation after acute illness or injury, and we will follow them for up to 1
year. On day 7 of mechanical ventilation we will collect data on lung function, neuromuscular weakness, acute
brain dysfunction, and other selected clinically available biomarkers. Premorbid functional decline including
validated frailty indices, and social and environmental variables will be obtained from medical records and
family interviews. For the first aim these variables will be evaluated as independent risk factors for severe
physical and cognitive dysfunction at one-year, focusing first on clinical variables and then on social and
economic factors. For the second aim we will construct and validate a single multi-outcome model using a
single set of variables to predict survival with severe physical disability, survival with severe cognitive disability,
survival with physical and cognitive disability, survival with normal function, and death. This project is important
because it will directly provide new tools for patients and clinicians to understand CCI, informing bedside
decision making and future medical and resource interventions for this extremely high-risk patient group.
摘要
项目成果
期刊论文数量(0)
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{{ truncateString('Shannon S Carson', 18)}}的其他基金
Prediction of Functional Outcomes from Chronic Critical Illness
慢性危重疾病功能结果的预测
- 批准号:
9535489 - 财政年份:2016
- 资助金额:
$ 66.07万 - 项目类别:
Informing Decisions in Chronic Critical Illness: An RCT
慢性危重疾病的知情决策:随机对照试验
- 批准号:
8055052 - 财政年份:2010
- 资助金额:
$ 66.07万 - 项目类别:
Informing Decisions in Chronic Critical Illness: An RCT
慢性危重疾病的知情决策:随机对照试验
- 批准号:
7781300 - 财政年份:2010
- 资助金额:
$ 66.07万 - 项目类别:
Informing Decisions in Chronic Critical Illness: An RCT
慢性危重疾病的知情决策:随机对照试验
- 批准号:
8328593 - 财政年份:2010
- 资助金额:
$ 66.07万 - 项目类别:
Informing Decisions in Chronic Critical Illness: An RCT
慢性危重疾病的知情决策:随机对照试验
- 批准号:
8636915 - 财政年份:2010
- 资助金额:
$ 66.07万 - 项目类别:
Informing Decisions in Chronic Critical Illness: An RCT
慢性危重疾病的知情决策:随机对照试验
- 批准号:
8250848 - 财政年份:2010
- 资助金额:
$ 66.07万 - 项目类别:
Informing Decisions in Chronic Critical Illness: An RCT
慢性危重疾病的知情决策:随机对照试验
- 批准号:
8461062 - 财政年份:2010
- 资助金额:
$ 66.07万 - 项目类别:
Validation of a Mortality Prediction Model for Prolonged Mechanical Ventilation
长时间机械通气死亡率预测模型的验证
- 批准号:
7924829 - 财政年份:2009
- 资助金额:
$ 66.07万 - 项目类别:
Validation of a Mortality Prediction Model for Prolonged Mechanical Ventilation
长时间机械通气死亡率预测模型的验证
- 批准号:
7739858 - 财政年份:2009
- 资助金额:
$ 66.07万 - 项目类别:
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