Decision support tool for early differential diagnosis of acute lung injury and cardiogenic pulmonary edema in medical critically ill patients.
BACKGROUND
At the onset of acute hypoxic respiratory failure, critically ill patients with acute lung injury (ALI) may be difficult to distinguish from those with cardiogenic pulmonary edema (CPE). No single clinical parameter provides satisfying prediction. We hypothesized that a combination of those will facilitate early differential diagnosis.


METHODS
In a population-based retrospective development cohort, validated electronic surveillance identified critically ill adult patients with acute pulmonary edema. Recursive partitioning and logistic regression were used to develop a decision support tool based on routine clinical information to differentiate ALI from CPE. Performance of the score was validated in an independent cohort of referral patients. Blinded post hoc expert review served as gold standard.


RESULTS
Of 332 patients in a development cohort, expert reviewers (κ, 0.86) classified 156 as having ALI and 176 as having CPE. The validation cohort had 161 patients (ALI = 113, CPE = 48). The score was based on risk factors for ALI and CPE, age, alcohol abuse, chemotherapy, and peripheral oxygen saturation/Fio(2) ratio. It demonstrated good discrimination (area under curve [AUC] = 0.81; 95% CI, 0.77-0.86) and calibration (Hosmer-Lemeshow [HL] P = .16). Similar performance was obtained in the validation cohort (AUC = 0.80; 95% CI, 0.72-0.88; HL P = .13).


CONCLUSIONS
A simple decision support tool accurately classifies acute pulmonary edema, reserving advanced testing for a subset of patients in whom satisfying prediction cannot be made. This novel tool may facilitate early inclusion of patients with ALI and CPE into research studies as well as improve and rationalize clinical management and resource use.
Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC), Mayo Clinic, Rochester, MN; University Witten-Herdecke, Witten, Germany. Electronic address: cschmickl83@gmail.com.
Christopher N
CN
Schmickl
Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC), Mayo Clinic, Rochester, MN.
Khurram
K
Shahjehan
Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC), Mayo Clinic, Rochester, MN; Pulmonary Division, Department of Guang'anmen Hospital, China Academy of Chinese Medical Science, Beijing, China.
Guangxi
G
Li
Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC), Mayo Clinic, Rochester, MN; Department of Pulmonary and Critical Care Medicine, Lahey Clinic, Burlington, MA.
Rajanigandha
R
Dhokarh
Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC), Mayo Clinic, Rochester, MN.
Rahul
R
Kashyap
Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC), Mayo Clinic, Rochester, MN.
Christopher
C
Janish
Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC), Mayo Clinic, Rochester, MN.
Anas
A
Alsara
Division of Cardiology, Mayo Clinic, Rochester, MN.
Allan S
AS
Jaffe
Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN.
Rolf D
RD
Hubmayr
Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC), Mayo Clinic, Rochester, MN.
Ognjen
O
Gajic
D055371:Acute Lung Injury / Q000175:diagnosis* / Q000209:etiology; D000368:Aged; D000369:Aged, 80 and over; D016638:Critical Illness; D020000:Decision Support Systems, Clinical / Q000706:statistics & numerical data*; D003661:Decision Support Techniques; D003937:Diagnosis, Differential; D042241:Early Diagnosis; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D008875:Middle Aged; D011654:Pulmonary Edema / Q000175:diagnosis* / Q000209:etiology; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012307:Risk Factors; D012770:Shock, Cardiogenic / Q000150:complications* / Q000175:diagnosis