Article Abstract

A modified acute respiratory distress syndrome prediction score: a multicenter cohort study in China

Authors: Jianfeng Xie, Ling Liu, Yi Yang, Wenkui Yu, Maoqin Li, Kaijiang Yu, Ruiqiang Zheng, Jie Yan, Xue Wang, Guolong Cai, Jianguo Li, Qin Gu, Hongsheng Zhao, Xinwei Mu, Xiaochun Ma, Haibo Qiu


Background: Early recognition of the risks of acute respiratory distress syndrome (ARDS) and prevention of the development of ARDS may be more effective in improving patient outcomes. We performed the present study to determine the ARDS risk factors in a Chinese population and validate a score to predict the development of ARDS.
Methods: This was an observational multicenter cohort study performed in 13 tertiary hospitals in China. Patients admitted into participating intensive care units (ICUs) from January 1 to January 31, 2012, and from January 1 to January 10, 2013, were enrolled in a retrospective derivation cohort and a prospective validation cohort, respectively. In the derivation cohort, the potential risk factors of ARDS were collected. The confirmed risk factors were determined with univariate and multivariate logistic regression analyses, and then the modified ARDS prediction score (MAPS) was established. We prospectively enrolled patients to verify the accuracy of MAPS.
Results: A total of 479 and 198 patients were enrolled into the retrospective derivation cohort and the prospective validation cohort, respectively. A total of 93 (19.4%) patients developed ARDS in the derivation cohort. Acute pancreatitis, pneumonia, hypoalbuminemia, acidosis, and high respiratory rate were the risk factors for ARDS. The MAPS discriminated patients who developed ARDS from those who did not, with an area under the curve (AUC) of 0.809 [95% confidence interval (CI), 0.758−0.859, P<0.001]. In the prospective validation cohort, performance of the MAPS was similar to the retrospective derivation cohort, with an AUC of 0.792 (95% CI, 0.717−0.867, P<0.001). The lung injury prediction score (LIPS) showed a predicted value of an AUC of 0.770 (95% CI, 0.728−0.812, P<0.001) in our patients, which was significantly lower than our score (P<0.046).
Conclusions: The MAPS based on risk factors could help the clinician to predict patients who will develop ARDS.
Trial registration: NCT01666834