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Am J Emerg Med. 2016 Mar;34(3):370-4. doi: 10.1016/j.ajem.2015.10.052. Epub 2015 Nov 10.

Inflammatory biomarkers predicting prognosis in patients with acute dyspnea.

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The Department of Clinical Sciences Malmo, Faculty of Medicine, Lund University, Lund, Sweden. Electronic address:
Department of Internal Medicine and Emergency Medicine, Skane University Hospital, Malmo, Sweden.
The Department of Clinical Sciences Malmo, Faculty of Medicine, Lund University, Lund, Sweden.



The objective was to identify inflammatory biomarkers that predict risk of 90-day mortality in patients with acute dyspnea.


We analyzed 25 inflammatory biomarkers, in plasma, in 407 adult patients admitted to the emergency department (ED) with acute dyspnea and related them to risk of 90-day mortality using Cox proportional hazard models adjusted for age, sex, oxygen saturation, respiratory rate, C-reactive protein, and Medical Emergency Triage and Treatment System-Adult score.


Fifty patients (12%) died within 90 day from admission. Two strong and independent biomarker signals were detected: The hazard ratio (95% confidence interval) for 90-day mortality per 1-SD increment of interleukin-8 (IL-8) was 2.20 (1.67-2.90) (P = 2.5 × 10(-8)) and for growth differentiation factor-15 (GDF-15) was 3.45 (2.18-5.45) (P = 1.3 × 10(-7)) A Biomarker Mortality Risk Score (BMRS) summing standardized and weighted values of IL-8 and GDF-15 revealed that of patients belonging to quartile 1 (Q1) of the BMRS, only 1 patient died, whereas 32 patients died among those belonging to quartile 4. Each 1-SD increment of the BMRS was associated with a hazard ratio of 3.79 (2.50-5.73) (P = 2 × 10(-10)) for 90-day mortality, and the point estimate was 13 times higher in Q4 as compared with Q1 of the BMRS (P(trend) over quartiles = 2 × 10(-6)).


Interleukin-8 and GDF-15 are strongly and independently related to risk of 90-day mortality in unselected patients admitted to the ED because of acute dyspnea, suggesting that they may guide first-line physicians at the ED in risk assessment which in turn could lead to more accurate level of care and treatment intensity.

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