Yonsei Med J.  2021 May;62(5):417-423. 10.3349/ymj.2021.62.5.417.

Predictive Role of Lung Injury Prediction Score in the Development of Acute Respiratory Distress Syndrome in Korea

Affiliations
  • 1Division of Pulmonology, Department of Internal Medicine, Korea University Ansan Hospital, Ansan, Korea
  • 2Department of Critical Care Medicine, Korea University Ansan Hospital, Ansan, Korea
  • 3Medical Science Research Center, Korea University Ansan Hospital, Ansan, Korea

Abstract

Purpose
Early recognition and therapeutic intervention are important in patients at high risk of acute respiratory distress syndrome (ARDS). The lung injury prediction score (LIPS) has been used to predict ARDS development; however, it was developed based on the previous definition of ARDS. We investigated the predictive role of LIPS in ARDS development according to its Berlin definition in the Korean population.
Materials and Methods
This was a retrospective study that enrolled adult patients admitted to the intensive care unit (ICU) at a single university-affiliated hospital in Korea from September 1, 2018, to August 31, 2019. LIPS at the time of ICU admission and the development of ARDS were evaluated.
Results
Of the 548 enrolled patients, 33 (6.0%) fulfilled the Berlin ARDS definition. The LIPS for non-ARDS and ARDS groups were 4.96±3.05 and 8.53±2.45, respectively (p<0.001); it was significantly associated with ARDS development (odds ratio 1.48, 95% confidence interval, 1.29–1.69; p<0.001). LIPS >6 predicted the development of ARDS with a sensitivity of 84.8% and a specificity of 67.2% [area under the curve (AUC)=0.82]. A modified LIPS model adjusted for age and severity at ICU admission predicted ICU mortality in patients with ARDS (AUC=0.80), but not in those without ARDS (AUC=0.54).
Conclusion
LIPS predicted the development of ARDS as diagnosed by the Berlin definition in the Korean population. LIPS provides useful information for managing patients with ARDS.

Keyword

Acute lung injury; respiratory distress syndrome; respiratory insufficiency; prediction model; critical illness
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