Derivation of a Lung Injury Prediction Score (LIPS) To Identify Patients at High Risk of ARDS at the Time of Hospital Admission.

Cartin‐Ceba, Rodrigo; Trillo-Alvarez, CA; Li, G; Kashyap, Rahul; Kojičić, Marija; Dong, Ying; Poulose, JT; Herasevich, Vitaly; Cabello-Garza, Javier; Shari, G; Malinchoc, Michael; Hubmayr, Rolf D.; Gajic, Ognjen

doi:10.1164/ajrccm-conference.2009.179.1_meetingabstracts.a4653

Cited by 4 publications

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“…To facilitate enrollment of patients into mechanistic and outcome studies as well as future ALI prevention trials, we have recently developed an ALI prediction model (Lung Injury Prediction Score: LIPS, Table 1 )[ 22 ]. LIPS incorporates demographic, and clinical characteristics at the time of, and before, hospital admission.…”

Section: Methodsmentioning

confidence: 99%

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Towards the prevention of acute lung injury: a population based cohort study protocol

et al. 2010

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BackgroundAcute lung injury (ALI) is an example of a critical care syndrome with limited treatment options once the condition is fully established. Despite improved understanding of pathophysiology of ALI, the clinical impact has been limited to improvements in supportive treatment. On the other hand, little has been done on the prevention of ALI. Olmsted County, MN, geographically isolated from other urban areas offers the opportunity to study clinical pathogenesis of ALI in a search for potential prevention targets.Methods/DesignIn this population-based observational cohort study, the investigators identify patients at high risk of ALI using the prediction model applied within the first six hours of hospital admission. Using a validated system-wide electronic surveillance, Olmsted County patients at risk are followed until ALI, death or hospital discharge. Detailed in-hospital (second hit) exposures and meaningful short and long term outcomes (quality-adjusted survival) are compared between ALI cases and high risk controls matched by age, gender and probability of developing ALI. Time sensitive biospecimens are collected for collaborative research studies. Nested case control comparison of 500 patients who developed ALI with 500 matched controls will provide an adequate power to determine significant differences in common hospital exposures and outcomes between the two groups.DiscussionThis population-based observational cohort study will identify patients at high risk early in the course of disease, the burden of ALI in the community, and the potential targets for future prevention trials.

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Section: Methodsmentioning

confidence: 99%

“…LIPS points were determined based on parameter estimates from the logistic regression model, taking into consideration results from our previous studies. The model accurately discriminated between the patients who did and did not develop ALI with an area under the receiver operating curve of 0.85 (95% CI 0.80 to 0.89) [ 22 ].…”

Section: Methodsmentioning

confidence: 99%