Application of EuroSCORE II and STS score for risk assessment in Indian patients—are they useful?

Author(s):  
Praveen Kerala Varma
2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
S Gharacholou ◽  
C.B Ball ◽  
F.D.C Del-Carpio Munoz ◽  
P.Y.T Takahashi ◽  
P.A.P Pellikka ◽  
...  

Abstract Background Older adults with severe aortic stenosis (AS) are at high risk of mortality unless surgical or transcatheter aortic valve replacement (AVR) is performed. Risk stratification often becomes complicated in frail elders with multi-morbidity, and time constraints limit thorough evaluation of geriatric comorbidities in the outpatient clinic setting. Purpose Utilization of an automated administratively-derived electronic health record (EHR) tool may aid in risk stratification of AS patients undergoing AVR. Methods We reviewed patients with severe AS undergoing AVR at our hospital program and cross-referenced with the Elder Risk Assessment (ERA) score. The ERA score is an administratively abstracted score derived on adults >60 years old followed by general medicine clinic. It contains the following variables: marital status, age, hospitalized days in preceding 2 years, diabetes, coronary disease, heart failure, stroke, pulmonary disease, cancer, and dementia; higher scores indicate greater risk for adverse outcomes. Kaplan-Meier method was used to estimate survival by ERA score tertile. Cox regression was used to test the association of ERA with survival. Results There were 97 patients with severe AS undergoing AVR with ERA scores. Mean age was 80.6 (±6.6) years, 37% were female, average Society of Thoracic Surgery (STS) score was 3.6% (± 2.6), and 7% had transcatheter AVR. Co-morbidities were prevalent and included atrial fibrillation (41%), chronic renal failure (16%), stroke (14%), and diabetes (35%). Over a mean follow-up of 68 months (± 37.9 months), there were 62 deaths. Elevated ERA score was associated with worse long term survival (p=0.016 by log-rank) (Figure 1), with only 49% surviving at 5 years in the highest ERA tertile vs 68% in the lowest ERA tertile. Cox regression demonstrated that the relative risk of death per 6 unit increase in ERA score was 1.54 (95% CI 1.21–1.96, P<0.001) in single variable analysis and 1.43 (95% CI 1.11–1.84, P=0.006) after adjusting for STS score. Conclusions Patients undergoing AVR for severe AS are often co-morbid older adults. An automated EHR derived ERA score was independently associated with survival after accounting for STS score and may streamline and improve risk assessment in these patients. Figure 1 Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): Mayo Clinic


Author(s):  
Azad Abdul Salam ◽  
T. Govindan Unni ◽  
Bino Benjamin ◽  
Prasanna C. K. ◽  
Manoj Ravi

Background: Cardiovascular diseases (CVD) are the main cause of mortality and disability in India. Early and sustained exposure to behavioral risk factors leads to development of CVD. The present study was conducted to compare different cardiovascular calculators for CVD risk assessment models in young Indian patients presenting with myocardial infarction.Methods: This study included 85 patients with myocardial infarction (MI). Their predicted 10-year risk of CVD was calculated using three clinically most relevant risk assessment models viz. Framingham Risk score (RiskFRS), American College of Cardiology/American Heart Association (RiskACC/AHA) and the 3rd Joint British Societies risk calculator (RiskJBS).Results: RiskFRS recognized the highest number of patients (15.4%) at high CVD risk while RiskACC/AHA and RiskJBS calculators provided inferior risk assessment but statistically significant relationship. RiskFRS and RiskACC/AHA (Pearson's r 0.870, p<0.001).Conclusions: RiskFRS seems to be as most useful CVD risk assessment model in young Indian patients. RiskFRS is likely to identify the number of patients at ‘high-risk’ as compared to RiskJBS and RiskACC/AHA.


1998 ◽  
Vol 62 (10) ◽  
pp. 756-761 ◽  
Author(s):  
CW Douglass
Keyword(s):  

2006 ◽  
Vol 175 (4S) ◽  
pp. 531-532
Author(s):  
Matthew R. Cooperberg ◽  
Stephen J. Freedland ◽  
David J. Pasta ◽  
Eric P. Elkin ◽  
Joseph C. Presti ◽  
...  

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