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. 2023 May;98(5):736-747.
doi: 10.1016/j.mayocp.2022.11.021. Epub 2022 Dec 30.

Development and Validation of an Acute Respiratory Distress Syndrome Prediction Model in Coronavirus Disease 2019: Updated Lung Injury Prediction Score

Aysun Tekin  1 , Shahraz Qamar  2 , Mayank Sharma  1 , Romil Singh  1 , Michael Malinchoc  3 , Vikas Bansal  4 , Neha Deo  5 , Marija Bogojevic  4 , Diana J Valencia-Morales  1 , Simon Zec  4 , Nika Zorko-Garbajs  6 , Nikhil Sharma  7 , Amos Lal  4 , Devang K Sanghavi  8 , Rodrigo Cartin-Ceba  9 , Syed A Khan  10 , Abigail T La Nou  11 , Anusha Cherian  12 , Igor B Zabolotskikh  13 , Vishakha K Kumar  14 , Rahul Kashyap  1 , Allan J Walkey  15 , Juan P Domecq  7 , Hemang Yadav  4 , Ognjen Gajic  4 , Yewande E Odeyemi  16 ; Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study (VIRUS): COVID-19 Registry Investigator Group
Affiliations

Development and Validation of an Acute Respiratory Distress Syndrome Prediction Model in Coronavirus Disease 2019: Updated Lung Injury Prediction Score

Aysun Tekin et al. Mayo Clin Proc. 2023 May.

Abstract

Objective: To develop and validate an updated lung injury prediction score for coronavirus disease 2019 (COVID-19) (c-LIPS) tailored for predicting acute respiratory distress syndrome (ARDS) in COVID-19.

Patients and methods: This was a registry-based cohort study using the Viral Infection and Respiratory Illness Universal Study. Hospitalized adult patients between January 2020 and January 2022 were screened. Patients who qualified for ARDS within the first day of admission were excluded. Development cohort consisted of patients enrolled from participating Mayo Clinic sites. The validation analyses were performed on remaining patients enrolled from more than 120 hospitals in 15 countries. The original lung injury prediction score (LIPS) was calculated and enhanced using reported COVID-19-specific laboratory risk factors, constituting c-LIPS. The main outcome was ARDS development and secondary outcomes included hospital mortality, invasive mechanical ventilation, and progression in WHO ordinal scale.

Results: The derivation cohort consisted of 3710 patients, of whom 1041 (28.1%) developed ARDS. The c-LIPS discriminated COVID-19 patients who developed ARDS with an area under the curve (AUC) of 0.79 compared with original LIPS (AUC, 0.74; P<.001) with good calibration accuracy (Hosmer-Lemeshow P=.50). Despite different characteristics of the two cohorts, the c-LIPS's performance was comparable in the validation cohort of 5426 patients (15.9% ARDS), with an AUC of 0.74; and its discriminatory performance was significantly higher than the LIPS (AUC, 0.68; P<.001). The c-LIPS's performance in predicting the requirement for invasive mechanical ventilation in derivation and validation cohorts had an AUC of 0.74 and 0.72, respectively.

Conclusion: In this large patient sample c-LIPS was successfully tailored to predict ARDS in COVID-19 patients.

Trial registration: ClinicalTrials.gov NCT04323787.

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Conflict of interest statement

Dr Kashyap has received funding from the National Institutes of Health/National Heart, Lung and Blood Institute: R01HL 130881, UG3/UH3HL 141722, Gordon and Betty Moore Foundation, and Janssen Research & Development, LLC; and has received royalties from Ambient Clinical Analytics. Inc. These funding organizations had no influence on the acquisition, analysis, interpretation, and reporting of pooled data for this manuscript. Dr Walkey has received funding from the National Institutes of Health/National Heart, Lung and Blood Institute grants R01HL151607, R01HL139751, R01HL136660, Agency of Healthcare Research and Quality, R01HS026485, and Boston Biomedical Innovation Center/NIH/NHLBI 5U54HL119145-07; and has received royalties from UpToDate. Dr Yadav has received funding from the National Heart, Lung, and Blood Institute: K23HL151671. Dr Gajic has received funding from the Agency of Healthcare Research and Quality R18HS 26609-2, National Institutes of Health/National Heart, Lung and Blood Institute: R01HL 130881, UG3/UH3HL 141722, Department of Defense DOD W81XWH, and the American Heart Association Rapid Response Grant – COVID-19; and has received royalties from Ambient Clinical Analytics. Inc. The remaining authors report no potential competing interests. The supplemental material lists collaborating coauthors.

Figures

Figure 1
Figure 1
Flowchart for the identification of study patients. ARDS, acute respiratory distress syndrome; COVID-19, coronavirus disease-2019; VIRUS, Viral Infection and Respiratory Illness Universal Study.
Figure 2
Figure 2
Receiver operating characteristic curves for the lung injury prediction score (LIPS) and coronavirus disease 2019 lung injury prediction score (c-LIPS) for classification of acute respiratory distress syndrome in derivation and validation cohorts. A, LIPS in the development cohort. The area under the receiver operating characteristic curve (AUC) was 0.74 (95% CI, 0.72 to 0.76). B, c-LIPS in the derivation cohort. The AUC was 0.79 (95% CI, 0.77 to 0.81). C, LIPS in the validation cohort. The AUC was 0.68 (95% CI, 0.66 to 0.7). D, c-LIPS in the validation cohort. The AUC was 0.74 (95% CI, 0.73 to 0.76).
Figure 3
Figure 3
The frequency of patients who developed acute respiratory distress syndrome for different coronavirus disease 2019 lung injury prediction score levels. A, Derivation cohort. B, Validation cohort. ARDS, acute respiratory distress syndrome; c-LIPS, coronavirus disease 2019 lung injury prediction score; LIPS, lung injury prediction score.
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