Timing and Intensity of the Exposures and Attributable Burden of Acute Lung Injury
Status: | Active, not recruiting |
---|---|
Conditions: | Hospital, Pulmonary |
Therapuetic Areas: | Pulmonary / Respiratory Diseases, Other |
Healthy: | No |
Age Range: | 18 - Any |
Updated: | 2/7/2019 |
Start Date: | December 2008 |
End Date: | December 2020 |
Identifying Patients at Risk of Developing Acute Lung Injury at the Time of Hospital Admission:Toward the Prevention of Acute Lung Injury (ALI)
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.
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 (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.
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.
Inclusion Criteria:
- All Olmsted County residents more than 18 years of age who were admitted to the two
Mayo Clinic Rochester hospitals
Exclusion Criteria:
- Denied the use of medical records for research
- Acute lung injury or pulmonary edema already present at the time of hospital admission
- Admitted for comfort or hospice care only
- Children
- Hospital readmission
- Patients admitted for cardiac telemetry, coronary care unit, low risk elective
surgeries, labor and delivery
We found this trial at
1
site
Rochester, Minnesota 55905
Principal Investigator: Ognjen Gajic, M.D.
Phone: 507-255-6051
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