A Risk Stratification Model for Cardiovascular Complications during the 3-Month Period after Major Elective Vascular Surgery

• Main Authors: Mladjan Golubovic, Dragana Stanojevic, Milan Lazarevic, Velimir Peric, Tomislav Kostic, Miodrag Djordjevic, Sasa Zivic, Dragan J. Milic
• Format: Article
• Language: English
• Published: Hindawi Limited 2018-01-01
• Series: BioMed Research International
• Online Access: http://dx.doi.org/10.1155/2018/4381527

Introduction. The Revised Cardiac Risk Index (RCRI) is an extensively used simple risk stratification tool advocated by the European Society of Cardiology and European Society of Anesthesiology (ESC/ESA). Purpose. The aim of this study was to find the best model for predicting 3-month cardiovascular complications in elective major vascular surgical patients using preoperative clinical assessment, calculation of the RCRI and Vascular Physiological and Operative Severity Score for the enumeration of mortality and morbidity (V-POSSUM) scores, and the preoperative levels of N-terminal brain natriuretic peptide (NT pro-BNP), high-sensitivity troponin I (hs TnI), and high-sensitivity C-reactive protein (hs CRP). Materials and Methods. We included 122 participants in a prospective, single-center, observational study. The levels of NT pro-BNP, hs CRP, and hs TnI were measured 48 hours prior to surgery. During the perioperative period and 90 days after surgery the following adverse cardiac events were recorded: myocardial infarction, arrhythmias, pulmonary edema, acute decompensated heart failure, and cardiac arrest. Results. During the first 3 months after surgery 29 participants (23.8%) had 50 cardiac complications. There was a statistically significant difference in the RCRI score between participants with and without cardiac complications. ROC analysis showed that a combination of RCRI with hs TnI has good discriminatory power (AUC 0.909, p<0,001). By adding NT pro-BNP concentrations to the RCRI+hs TnI+V-POSSSUM combination we obtained the model with the best predictive power for 3-month cardiac complications (AUC 0.963, p<0,001). Conclusion. We need to improve preoperative risk assessment in participants scheduled for major vascular surgery by combining their clinical scores with biomarkers. Therefore, it is possible to identify patients at risk of cardiovascular complications who need adequate preoperative diagnosis and treatment.