Timing and Intensity of the Exposures and Attributable Burden of Acute Lung Injury (LIPS)
The purpose of the study is to identify the patients at high risk of developing Acute Lung Injury (ALI) at the time of hospital admission, and before intensive care unit admission.
Aim 1- To validate the prediction model (Lung Injury Prediction Score) in a population based sample of hospitalized patients.
Aim 2- To determine the significance of health-care related ALI risk modifiers in a population based sample.
Aim 3- To compare the short and long term outcomes between patients at high risk who do, and do not develop ALI.
Acute Lung Injury
Acute Respiratory Distress Syndrome
|Study Design:||Observational Model: Cohort
Time Perspective: Prospective
|Official Title:||Identifying Patients at Risk of Developing Acute Lung Injury at the Time of Hospital Admission:Toward the Prevention of Acute Lung Injury (ALI)|
- Development of ALI [ Time Frame: During the hospital stay (before discharge and maximum of 30 days) ] [ Designated as safety issue: No ]
- Quality adjusted survival [ Time Frame: 6 months ] [ Designated as safety issue: No ]
Biospecimen Retention: Samples With DNA
|Study Start Date:||December 2008|
|Estimated Study Completion Date:||December 2017|
|Estimated Primary Completion Date:||December 2017 (Final data collection date for primary outcome measure)|
At risk for Acute Lung Injury
Controls-High risk patients at risk of Acute Lung Injury(ALI) but do not develop ALI
Cases-High risk patients that do develop Acute Lung Injury
Acute lung injury (ALI) is an example of a critical care syndrome with limited treatment options once the condition is fully established.Not surprisingly, many treatments targeting the mechanisms identified in preclinical studies have failed to improve patient outcomes.The most likely reason could be due to inadequate and delayed recognition of patients at risk and the subsequent development of the full blown syndrome.ALI/ARDS usually develops during the first hours of ICU admission, and often is the very reason for ICU admission.
Clinical prediction models have been extensively used in the clinical practice to identify patients at high risks who may benefit from specific interventions. However, no such tool exists to predict the development of ALI in patients at risk. We have recently developed an ALI prediction model (Lung Injury Prediction Score:LIPS)which incorporates demographic, environmental and clinical characteristics at the time of, and before, hospital admission. If validated, this model will serve to find the population of patients at high risk of ALI in whom future prevention trials will be conducted. By determining not only patients at high risk but also the attributable burden of ALI/ARDS in contemporary cohorts of patients at risk, our findings will facilitate the prioritization of preventive strategies and future clinical trials.
Please refer to this study by its ClinicalTrials.gov identifier: NCT00980915
|Contact: Ognjen Gajic, M.D.||email@example.com|
|United States, Minnesota|
|Rochester, Minnesota, United States, 55905|
|Contact: Ognjen Gajic, M.D. 507-255-6051 firstname.lastname@example.org|
|Contact: Gregory A Wilson, B.S 507-255-6832 email@example.com|
|Principal Investigator: Ognjen Gajic, M.D.|
|Principal Investigator:||Ognjen Gajic, M.D.||Mayo Clinic|