Acute Respiratory Distress Syndrome Prediction Score: Derivation and Validation

Author:

Huang Lixue1,Song Man2,Liu Yan3,Zhang Wenmei4,Pei Zhenye5,Liu Nan6,Jia Ming7,Hou Xiaotong8,Zhang Haibo9,Li Jinhua10,Cao Xiangrong11,Zhu Guangfa12

Affiliation:

1. Lixue Huang is a clinician, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.

2. Man Song is a clinician, Department of Infectious Disease, Beijing Anzhen Hospital, Capital Medical University.

3. Yan Liu is a clinician, Department of Infectious Disease, Beijing Anzhen Hospital, Capital Medical University.

4. Wenmei Zhang is a clinician, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.

5. Zhenye Pei is a clinician, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.

6. Nan Liu is a professor, Surgical Intensive Care Unit, Beijing Anzhen Hospital, Capital Medical University.

7. Ming Jia is a professor, Surgical Intensive Care Unit, Beijing Anzhen Hospital, Capital Medical University.

8. Xiaotong Hou is a professor, Surgical Intensive Care Unit, Beijing Anzhen Hospital, Capital Medical University.

9. Haibo Zhang is a professor, Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University.

10. Jinhua Li is a professor, Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University.

11. Xiangrong Cao is a professor, Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University.

12. Guangfa Zhu is a professor, Department of Pulmonary and Critical Care Medicine, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, China.

Abstract

Background Despite advances in treatment strategies, acute respiratory distress syndrome (ARDS) after cardiac surgery remains associated with high morbidity and mortality. A method of screening patients for risk of ARDS after cardiac surgery is needed. Objectives To develop and validate an ARDS prediction score designed to identify patients at high risk of ARDS after cardiac or aortic surgery. Methods An ARDS prediction score was derived from a retrospective derivation cohort and validated in a prospective cohort. Discrimination and calibration of the score were assessed with area under the receiver operating characteristic curve and the Hosmer-Lemeshow goodness-of-fit test, respectively. A sensitivity analysis was conducted to assess model performance at different cutoff points. Results The retrospective derivation cohort consisted of 201 patients with and 602 patients without ARDS who had undergone cardiac or aortic surgery. Nine routinely available clinical variables were included in the ARDS prediction score. In the derivation cohort, the score distinguished patients with versus without ARDS with area under the curve of 0.84 (95% CI, 0.81-0.88; Hosmer-Lemeshow P = .55). In the validation cohort, 46 of 1834 patients (2.5%) had ARDS develop within 7 days after cardiac or aortic surgery. Area under the curve was 0.78 (95% CI, 0.71-0.85), and the score was well calibrated (Hosmer-Lemeshow P = .53). Conclusions The ARDS prediction score can be used to identify high-risk patients from the first day after cardiac or aortic surgery. Patients with a score of 3 or greater should be closely monitored. The score requires external validation before clinical use.

Publisher

AACN Publishing

Subject

Critical Care,General Medicine

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