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Received Nov 29, 2017; Revised Apr 12, 2018; Accepted Apr 16, 2018
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
1. Introduction
Acute respiratory distress syndrome (ARDS) is a critical illness characterized by noncardiogenic pulmonary edema and refractory hypoxemia [1]. Although great progress has been made in the methods used to improve the clinical prognosis of ARDS (such as the use of protective mechanical ventilation [2–4] and fluid balance therapy [5]), the morbidity and mortality of ARDS remain largely unchanged. Thus, early prediction and early therapy for ARDS will be helpful for reducing morbidity and mortality [6].
Unfortunately, although a variety of ARDS studies have been conducted, there is no favorable prediction model for ARDS. The multicenter study by Gajic et al. included more than 5000 cases, and the investigators constructed a predictor of ARDS: the lung injury prediction score (LIPS) [7, 8]. However, the positive predictive value (PPV) of the LIPS was only 0.18, thereby limiting its clinical application. Other predictors of ARDS (such as early acute lung injury (ALI) and surgical lung injury prediction models) are not validated in clinical practice [9, 10].
ARDS is an uncontrollable pulmonary inflammation characterized by neutrophil activation and endothelial injury [11–13]. Plasma interleukin-6 (IL-6) and interleukin-8 (IL-8) in ARDS patients are significantly higher than those in patients without ARDS [14–16]. Plasma angiopoietin-2 (ANG-2) is a proinflammatory cytokine that can regulate endothelial permeability [17]. Serum ANG-2 level is significantly increased in ARDS patients [18, 19], and ANG-2 displays predictive value for ARDS [19, 20]. However, numerous other factors also affect the outcomes of ARDS, and no single biomarker has been found to predict ARDS onset.
We hypothesized that the combined use of two or more parameters would be better than using only one factor in predicting ARDS. Thus, in the present study, the predictive value for ARDS by combining LIPS with one or more of 4 biomarkers was investigated.
2. Materials and Methods
2.1. Study Population
In this prospective study, 254 Han Chinese patients with risk factors for ARDS were recruited from the Respiratory Intensive Care Unit (RICU) and Emergency Intensive Care Unit (EICU) of Xinqiao...