A Retrospective, Nested Case-Control Study to Develop a Biomarker-Based Model for ARDS Diagnostics
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Background:
Several biomarkers could be intercalated with traditional measures to improve ARDS diagnostics.
Methods:
There were 211 ICU patients enrolled in this retrospective, nested case-control study. Participants were divided into an ARDS (n = 79) and non-ARDS (n = 132) groups, according to the Berlin criteria. Patient characteristics, vital signs, and laboratory tests were collected within three hours of admission. CC16, Ang-2, sRAGE, HMGB1, and SPD were measured within three hours and again at 24 hours, after admission to ICU. Receiver Operating Characteristic curves and multivariate logistic regression analyses were applied for predictive purposes.
Results:
C-reactive protein (CRP), NT-proBNP, and pH values were intercalated with five established ARDS indicators, and the PaO2/FiO2 ratio. Only four potential indicators were analyzed, with CRP having high diagnostic value. Areas under curve (AUC) were as follows: CC16 (AUC: 0.752; 95% CI 0.680 - 0.824), Ang-2 (AUC: 0.695; 95% CI 0.620 - 0.770), HMGB1 (AUC: 0.668; 95% CI 0.592 - 0.744), sRAGE (AUC: 0.665; 95% CI 0.588 - 0.743), CRP (AUC: 0.701; 95% CI 0.627 - 0.776). No single indicator improved upon the PaO2/FiO2 ratio which had an AUC: 0.844 (95% CI 0.789 - 0.898). However, when the binary logistic model was transformed and the model was constructed, the AUC increased from 0.647 (95% CI 0.568 - 0.726) to 0.911 (95% CI 0.864 - 0.946). Among the combinations tested, PaO2/FiO2 + CRP + Ang-2 + CC16 + HMGB1 resulted in the highest AUC of 0.910 (95% CI 0.863 - 0.945), although there are other factors which must be considered.
Conclusions:
A combination of biomarkers could enhance ARDS diagnostics, which has obvious ramifications for patient care and prognosis. It may be possible to develop a predictive ARDS nomogram; however, of the combinations tested here, we tentatively recommend PaO2/FiO2 + CRP + Ang-2 + CC16 + HMGB1. This is because of the cost implications in contrast with benefit involved in utilizing the more elaborate model. Further health economics research is required to consider the opportunity cost for emergency care policy.
