Prognostic Value of GDF-15 in Predicting Prolonged Intensive Care Stay following Cardiac Surgery: A Pilot Study

Introduction. Predicting intensive care unit length of stay and outcome following cardiac surgery is currently based on clinical parameters. Novel biomarkers could be employed to improve the prediction models. Materials and Methods. We performed a qualitative cytokine screening array to identify highly expressed biomarkers in preoperative blood samples of cardiac surgery patients. After identification of one highly expressed biomarker, growth differentiation factor 15 (GDF-15), a quantitative ELISA was undertaken. Preoperative levels of GDF-15 were compared in regard to duration of intensive care stay, cardiopulmonary bypass time, and indicators of organ dysfunction. Results. Preoperatively, GDF-15 was highly expressed in addition to several less highly expressed other biomarkers. After qualitative analysis, we could show that preoperatively raised levels of GDF-15 were positively associated with prolonged ICU stay exceeding 48 h (median 713 versus 1041 pg/ml, <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"><a:mi>p</a:mi><a:mo>=</a:mo><a:mn>0.003</a:mn></a:math> ). It was also associated with prolonged mechanical ventilation and rates of severe sepsis but not with dialysis rates or cardiopulmonary bypass time. In univariate regression, raised GDF-15 levels were predictive of a prolonged ICU stay (OR 1.01, 95% confidence interval 1–1.02, and <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" id="M2"><c:mi>p</c:mi><c:mo>=</c:mo><c:mn>0.029</c:mn></c:math> ). On ROC curves, GDF-15 was found to predict prolonged ICU stay ( <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" id="M3"><e:mtext>AUC</e:mtext><e:mo>=</e:mo><e:mn>0.86</e:mn></e:math> , 95% confidence interval 0.71–0.99, and <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" id="M4"><g:mi>p</g:mi><g:mo>=</g:mo><g:mn>0.003</g:mn></g:math> ). Conclusion. GDF-15 showed potential as predictor of prolonged intensive care stay following cardiac surgery, which might be valuable for risk stratification models.