Assessment of Agreement between Pretest Probability Score and Summed Stress Score of Myocardial Perfusion Imaging in Coronary Artery Disease
Objectives: Cardiovascular diseases are considered an important cause of mortality & morbidity in many developing countries including Bangladesh. The first step in evaluating a patient with Coronary Artery Disease (CAD) is the clinical assessment of pretest probability. American Heart Association/ American College of Cardiology (AHA/ACC) guidelines recommend the use of Diamond and Forrester Method (DFM) or Duke Clinical Score (DCS) for calculating Pretest Probability Score (PPS). Myocardial Perfusion study (MPI) can calculate the Summed Stress Score (SSS), an index obtained by adding the individual scores derived from the 17 segments. This study was performed to assess the agreement between the established PPS with SSS so that it can help in risk stratification.
Patients and Methods: This cross-sectional observational study was carried out in National Institute of Nuclear Medicine & Allied Science (NINMAS), BSMMU from July 2016 to June 2017. A total of 89 suspected or known CAD patients were included in this study. PPS was calculated by Duke clinical scoring from brief clinical history. SSS was calculated by nuclear medicine software while performing Myocardial Perfusion Imaging (MPI). Statistical analyses were carried out by using the IBM Statistical Package for Social Sciences (SPSS) version 20.0.0 (IBM Corporation Software Group Somers, NY). Pearson correlation and Bland & Altman analyses were applied for assessing correlation and agreement between PPS and SSS. Degree of relation between variables is expressed by ‘r’ (Pearson’s correlation coefficient).
Results: The mean of PPS was found 14.73 ± 3.35 and that of SSS was found 16 ± 14.01. A positive correlation (r=0.108; p=0.312) between PPS and SSS. With Bland and Altman analysis, it was observed that mean difference of PPS and SSS was -1.27 ± 14.045. The limit of agreement ranged from -28.798 to 26.259. There was a positive correlation between PPS and SSS. Mean difference between the two scores was small. The bias between the scores was not significant. The differences within mean ± 1.96 SD were not statistically significant.
Conclusion: This study shows PPS and SSS can be used interchangeably. This analysis of agreement between PPS and SSS can further enhance prediction of CAD and upgrade the utilization of SSS for risk stratification in CAD patients, which will influence therapeutic management of the patients and play a major role to reduce cardiovascular mortality and morbidity.
Bangladesh J. Nuclear Med. 21(2): 73-76, July 2018