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Validation of the Euroscore on Cardiac Surgery Patients in Nairobi

Awori Mark, Mehta Nikita, Mitema Fred, Mwangi Jimmy, Mjahid Hassan, Oloo Paul School of Medicine, University of Nairobi

Correspondence to: Dr. Mark Awori. P.O Box 14677-00800 Nairobi. Email: mnawori@yahoo.com

 Abstract

Background: The Additive Euroscore (AE) predicts outcomes in cardiac surgical procedures performed on cardiopulmonary bypass. It’s been widely used in developed nations but it’s applicability in Kenya is unknown. Our objective was to determine its applicability at Kenyatta National Hospital (Kenya). Methods: A retrospective study was carried out between 1st January 2011 and 31st December 2015. Risk factor prevalence was compared with that of the AE derivation population. The AE was calculated; discrimination was determined by receiver operator curve analysis. Results: Of 109 patients, significant differences (Kenyan vs. AE derivation) were found in the prevalence of pulmonary y hypertension (58.7% vs. 2%) and isolated coronary artery bypass graft surgery (4.6% vs. 65%). Only double valve replacement was a risk factor for operative mortality; odds ratio 5.98 (1.83

 to 19.49). The area under curve (AUC) for the AE was 0.59. Conclusion: The AUC for the AE implies poor discrimination in our population. Significant differences in the risk factor profile between our study population and the AE score derivation population may have contributed to this. Our findings suggest that the AE may not be applicable to patients in Kenya. We recommend that a local risk scoring system be developed.

Key words: Euroscore, Validation, Kenya

Ann Afr Surg. 2017; 14(2):100-103

DOI:http://dx.doi.org/10.4314/aas.v14i2.10

© 2017 Author. This work is licensed under the Creative Commons Attribution 4.0 International License.

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Introduction

The aim of surgery is to improve patient health while minimizing patient exposure to procedure related morbidity and mortality; ‘evidence based medical practice’ (EBMP) is employed to facilitate this (1-3). Crude operative mortality does not take into account the pre-operative mortality risk factor profile of patients; EBMP dictates that ‘risk adjusted operative morality’ be employed to assess surgical outcome (3, 4). The use of risk stratification for the prediction of surgical outcomes is commonly practiced in most surgical disciplines. Risk stratification systems provide information that influences the choice of intervention, facilitates the process of obtaining informed consent and delivers a mechanism to measure surgical performance (5). Preoperative risk factors have been shown to affect surgical outcome in cardiac surgery (6). Risk stratification systems that incorporate only preoperative factors are particularly useful as they facilitate decision making before any intervention has been administered. For instance, by predicting the risk of operative mortality, patient and surgeon can opt for a procedure with a mutually acceptable mortality. Best practice requires that the highest possible surgical outcomes be obtained. In this regard, predicted mortalities using risk stratification systems can be used to determine if the observed mortality lies w