Addition of biomarker panel improves prediction performance of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: a pilot study
- 133 Downloads
Number of elderly patients subjected to extensive surgical procedures in the presence of cardiovascular morbidities is increasing every year. Therefore, there is a need to make preoperative diagnostics more accurate.
To evaluate the usefulness of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator as a predictive tool in preoperative assessment of cardiovascular risk in elderly patients.
This prospective pilot study included 78 patients who were being prepared for extensive non-cardiac surgeries under general anaesthesia. Their data have been processed on the interactive ACS NSQIP calculator. Blood sampling has been performed 7 days prior to surgery, and serum has been separated. Clinical, novel, and experimental biomarkers [hsCRP, H-FABP, and Survivin (BIRC5)] have been measured in specialized laboratories.
Mean age of included patients was 71.35 ± 6.89 years. In the case of heart complications and mortality prediction, hsCRP and ACS NSQIP showed the highest specificity and sensitivity with AUC, respectively, 0.869 and 0.813 for heart complications and 0.883 and 0.813 for mortality. When combined with individual biomarkers AUC of ACS NSQIP raised, but if we combined all three biomarkers with ACS NSQIP, AUC reached as much as 0.920 for heart complications and 0.939 for mortality.
ACS NSQIP proved to reduce inaccuracy in preoperative assessment, but it cannot be used independently, which has already been proved by other authors.
Our results indicate that ACS NSQIP represents an accurate tool for preoperative assessment of elderly patients, especially if combined with cardiac biomarkers.
KeywordsPeriod Preoperative; survivin protein Human; H-FABP Human; hsCRP Human
We would like to thank Miodrag Krstić, Master Engineer of Electrical Engineering and Computer Science, for his assistance in statistical analyses of data.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
All included patients signed the informed consent.
- 1.The Joint Task Force on non-cardiac surgery: cardiovascular assessment and management of the European Society of Cardiology (ESC) and the European Society of Anaesthesiology (ESA) (2014) 2014 ESC/ESA Guidelines on non-cardiac surgery: cardiovascular assessment and management. Eur Heart J 35:2383–2431CrossRefGoogle Scholar
- 2.Kim SW, Han HS, Jung HW et al (2014) Multidimensional frailty score for the prediction of postoperative mortality risk. JAMA Surg 149:633–640Google Scholar
- 8.Kirkhus L, Jordhøy M, Šaltytė Benth J et al (2016) Comparing comorbidity scales: Attending physician score versus the Cumulative Illness Rating Scale for Geriatrics. J Geriatr Oncol 7:90–98Google Scholar
- 16.Klingenberg R, Aghlmandi S, Räber L et al (2016) Improved risk stratification of patients with acute coronary syndromes using a combination of hsTnT, NT-proBNP and hsCRP with the GRACE score. Eur Heart J Acute Cardiovasc Care. doi: 10.1177/2048872616684678
- 18.Janković RJ, Marković DZ, Sokolović DT et al (2016) Clinical indices and biomarkers for perioperative cardiac risk stratification: an update. Minerva Anestesiol. doi: 10.23736/S0375-9393.16.11545-7
- 20.Lee PJH, Rudenko D, Kuliszewski MA et al (2014) Survivin gene therapy attenuates left ventricular systolic dysfunction in doxorubicin cardiomyopathy by reducing apoptosis and fibrosis. Cardiovsc Res 101:423–433Google Scholar
- 22.Marković D, Jevtović-Stoimenov T, Golubović M et al (2016) Significance of survivin (BIRC5) as a cardiac biomarker for the assessment of preoperative cardiovascular risk in nin-cardiac surgeries- surviving (BIRC5) as a novel cardiac biomarker. SJAIT 38:201–212Google Scholar
- 30.Marinkovic I, Radivojevic B (2016) Mortality trends and depopulation in Serbia. Geogr Pannonica 20:220–226Google Scholar
- 31.Urošević J, Odović G, Rapaić D et al (2015) Quality of life of the elderly in urban and rural areas in Serbia Kvalitet života starih u urbanoj i ruralnoj sredini u Srbiji. Vojnosanit Pregl 72: 968–974Google Scholar
- 32.Republic of Serbia, Ministry of Health (2014) Results of the national health survey of the Republic of Serbia 2013. Belgrade, Serbia, pp 91–93Google Scholar
- 42.Harris C, Kim S, Groban L (2015) How well does the NSQIP surgical calculator predict early adverse outcomes in plder non-cardiac surgical patients with self-reported limitations in mobility? Gerontologist 55:192Google Scholar
- 43.Marković D, Stošić B, Savić S et al (2016) Improtance of biomarkers in preoperative evaluation of cardiovascular risk. Acta Med Med 55:70–75Google Scholar
- 47.Vaid S, Bell T, Grim R et al (2012) Predicting risk of death in general surgery patients on the basis of preoperative variables using American College of Surgeons National Surgical Quality Improvement Program Data. Perm J 16:10–17Google Scholar
- 49.Basta MN, Bauder AR, Kovach S et al (2016) Assessing the predictive accuracy of the ACS NSQIP surgical risk calculator in open ventral hernia repair. Plast Reconstr Surg Glob Open 4:115Google Scholar
- 52.Chung PJ, Carter TI, Burack JH et al (2015) Predicting the risk of death following coronary artery bypass graft made simple: a retrospective study using the American College of Surgeons National Surgical Quality Improvement Program database. J Cardiothorac Surg 10:62CrossRefPubMedPubMedCentralGoogle Scholar
- 53.Blankenberg S, McQueen MJ, Smieja M et al (2006) Comparative impact of multiple biomarkers and N-terminal pro-brain natriuretic peptide in the context of conventional risk factors for the prediction of recurrent cardiovascular events in the heart outcomes prevention evaluation (HOPE) study. Circulation 114:201–208CrossRefPubMedGoogle Scholar