Skip to main content
Download PDF
  • Research article
  • Open access
  • Published:

2-Dimensional Speckle Tracking Echocardiography predicts severe coronary artery disease in women with normal left ventricular function: a case-control study

BMC Cardiovascular Disorders volume 17, Article number: 231 (2017) Cite this article

Abstract

Background

Women who have coronary artery disease (CAD) often present with atypical symptoms that may lead to misdiagnosis. We assessed strain, systolic strain rate and left ventricular dyssynchrony with 2- dimensional- speckle tracking echocardiography to evaluate its use as a non-invasive method for detecting CAD in women with normal ejection fraction compared with healthy women controls with a normal angiogram.

Methods

We included 35 women with CAD confirmed by coronary angiography and a positive exercise stress echocardiography and 35 women in a control group with a low pretest probability of CAD, normal angiogram and a normal stress echocardiography with normal EF.

Results

Statistically significant 2D-STE findings for the CAD vs control groups were as follows for the mean of: global circumferential strain (CS) (−19.4% vs −22.4%, P = .02); global radial S (49% vs 34%, P = .03); global radial SR (2.4 s−1 vs 1.9 s−1, P = .05); global longitudinal LV S (GLS) (−14.3% vs −17.2%, P < .001). For mechanical dyssynchrony, SD of the GLS time-to-peak (TTP) was computed (99 vs 33 ms, P < .001). The receiver operating characteristic and area under the curve (AUC) were calculated. A cutoff value of 45 ms for 1 SD of the longitudinal S TTP had 97% sensitivity and 89% specificity (AUC, 0.96). GLS cutoff value of −15.87% had 71% sensitivity and 74% specificity; AUC, 0.74 in differentiating CAD and control groups. The combined GLS, CS, and SD of the longitudinal S TTP had an AUC of 0.96 (sensitivity 97%, specificity 86%). Interclass correlations of the GLS segment and GLS TTP measurements were 0.49 (95% CI, 0.227-0.868) and 0.74 (95% CI, 0.277-0.926), respectively.

Conclusion

In women with a normal echocardiogram and LVEF, CAD can be identified by dyssynchrony and abnormal strain values, as evidenced by 2D-STE.

Peer Review reports

Background

Cardiovascular disease is the leading cause of morbidity and mortality throughout most of the world today, representing 31% of all deaths [1]. Significant advances have been made in the diagnosis and treatment of cardiovascular disease, but most have been tailored to the recognition and treatment of the disease in men [2]. Substantially less research has been done to study the growing issue of the disease in women [3]. Women tend to present with atypical symptoms and experience coronary artery disease (CAD) later in life than men. They also have a higher incidence of morbidity and mortality when CAD does occur, including myocardial infarction and sudden death [4]. Women also have a different atherosclerotic profile than men, primarily composed of microvascular disease without substantial obstructive CAD on imaging [5]. Because of this finding, it has been suggested that CAD in women be referred to as “female specific ischemic heart disease” [5,6,7].

Echocardiography is an important noninvasive method for assessing cardiovascular function and mechanics [8]. Two-dimensional–speckle tracking echocardiography (2D-STE) has proven to be an important recent advance [8, 9]. 2D-STE software tracks groups of intramyocardial speckles to derive myocardial deformation in 3 imaging planes, allowing measurement of parameters such as strain (S) and systolic strain rate (SRs) of the myocardium [10]. Measurements of S and SRs are more sensitive than standard echocardiographic parameters for assessing left ventricular (LV) function of many clinical conditions, including cardiomyopathy and CAD [11,12,13,14]. 2D-STE has been validated as an accurate, angle-independent, noninvasive method for evaluating cardiac mechanical function [15]. Furthermore, STE by velocity vector imaging (VVI) has been confirmed as an accurate method to measure S and SRs and to quantify myocardial function regionally and globally [16].

The aim of this study was to assess 2D-STE parameters of S, SRs, and time-to-peak (TTP) measurements, as well as LV dyssynchrony in healthy women to define normal values and then to compare these to values of women with known CAD. By so doing, we hoped to demonstrate that 2D-STE can be used to predict CAD in women with a normal ejection fraction (EF).

Methods

Study population

We reviewed electronic health records of women who underwent an exercise stress echocardiography, followed by cardiac angiography that showed severe CAD. Severe CAD was classified as stenosis of more than 50% in 1 or more vessels and was further sub-classified depending on the number of affected vessels [17]. This classification was based on current practice guidelines which place patients with higher than 50% stenosis at high risk for adverse cardiac events [18,19,20,21]. All tests were performed at Mayo Clinic from January 1, 2006, through December 31, 2006, and coronary angiography had to be completed within 6 months of the treadmill test. Patients were excluded if they had a resting LVEF less than 50%, a contrast computed tomography scan, atrial fibrillation, more than moderate valvular disease, or studies with poor image quality. The control group comprised women with a low probability of CAD, ie, normal EF and a normal stress echocardiogram and coronary angiogram performed at Mayo Clinic from 2009 through 2010. The Mayo Clinic Institutional Review Board approved the study, and all patients provided written consent to allow review of their electronic clinical records and images.

Standard echocardiographic examination

Echocardiographic imaging was performed by a registered diagnostic cardiac sonographer using a standardized protocol in the Mayo Clinic echocardiography laboratory. Three commercial echocardiographic systems were used: 1) Sequoia C512 (Siemens AG, Munich, Germany) with a 4 V1 transducer (1-4 MHz); 2) Vivid 7 (General Electric Co, Fairfield, Connecticut) with an M4S transducer (1.5-4.3 MHz); and 3) iE33 (Royal Philips Electronics, Amsterdam, The Netherlands) with an S5-1 transducer (1-5 MHz). The Sequoia C512 was used for all women in the control group. Images were obtained at a mean (SD) frame rate of 41 (5) MHz in the CAD group.

Speckle tracking imaging

Three-beat cine-loop clips were selected from the parasternal short-axis views at the papillary muscle level and from 3 apical views (2-chamber, 3-chamber, and 4-chamber). These images were exported and then analyzed offline with syngo VVI software (Siemens Medical Solutions USA, Inc., Malvern, Pennsylvania). The process began with manual endocardial to mid-wall tracing of a single frame at end systole by a point-click approach, with a region of interest that covers at least 90% of the myocardial wall thickness. The periodic displacement of the tracing was automatically tracked in subsequent frames. Tissue velocity was determined by the software, according to a shift of the points divided by time between B-mode frames. The software automatically calculated S and SRs from the velocity. The TTP of S and SRs was measured automatically by the software, with the beginning of the QRS complex as a reference. The SD of longitudinal S for 16 segments was calculated. LV dyssynchrony was defined according to the method proposed by Yu et al. [22], described below. VVI data were exported into an Excel 2003 spreadsheet (Microsoft Corp, Redmond, Washington) for further analysis (Fig. 1).

Fig. 1
figure 1

Left ventricular deformation. a Normal pattern left ventricular deformation. b Coronary artery disease. These images were exported and then analyzed offline with syngo VVI (velocity vector imaging) software

Full size image

Reproducibility

Interobserver variability was assessed in 10 randomly selected patients for whom 2D-STE examinations were independently performed by 2 investigators (S.B.G., J.A.K.) 4 to 8 weeks after the initial analysis. The intra-subject reproducibility of data was evaluated with the intra-class correlation coefficient, which measured the strength of the association between the measured parameters [23,24,25].

Statistical analysis

Data are presented as mean (SD) for continuous variables and as percentages for categorical variables. Differentiation between the CAD and control groups was performed with univariate and multivariate logistic regression. Each global and segmental S and SRs value was assessed as a predictor of the CAD group in a model. Diagnostic accuracy of S and SRs values was evaluated using receiver operating characteristic (ROC) analysis. We used the concordance correlation coefficient (CCC) for interobserver variability and calculated the absolute difference and the percentage difference between the 2 observers. A P value of less than .05 was considered statistically significant. JMP 9.0.1 statistical software (SAS Institute Inc., Cary, North Carolina) was used to perform the statistical analysis.

Results

Participant characteristics

The mean (SD) values for the CAD and control groups (35 women in each group), respectively, were as follows: age, 70 (8) vs 35 (13) years (P < .001); body mass index, 27 (5) vs 26 (7) kg/m2 (P = .23); heart rate, 76 (12) vs 75 (11) beats per minute (P = .94); systolic blood pressure, 137 (19) vs 110 (15) mm Hg (P < .001); diastolic blood pressure, 74 (10) vs 65 (10) mm Hg (P = .004); PR interval, 165 (21) vs 143 (17) ms (P < .001); and QRS duration, 84 (10) vs 88 (12) ms (P = .17). CAD was classified as follows: mild disease (<50% occlusion), 8.6% (3 patients); and severe 1-vessel disease, 31.4% (11 patients); 2-vessel disease, 31.4% (11 patients); and 3-vessel disease, 29% (10 patients). The most common indications for further diagnostic studies in the CAD group were fatigue and substantial comorbidities or risk factors for CAD. Only 3% of controls had comorbidities, such as hypertension and hyperlipidemia. Other clinical characteristics of the groups are shown in Table 1.

Table 1 Group characteristics
Full size table

Standard echocardiographic data

The mean (SD) 2D echocardiographic findings for the CAD group vs the control group, respectively, were as follows: EF, 60%(5) vs 63% (4) (P = .02); LV systolic dimension, 29 mm (5) vs 30 mm (3) (P = .52); early mitral inflow velocity (E) wave, 0.76 (0.25) m/s vs 0.84 (0.23) m/s (P = .16); and early diastolic mitral annular tissue velocity (e′), 0.09 (0.14) m/s vs 0.12 (0.03) m/s; (P < .001). Variables with higher (mean [SD]) values in the CAD group were the E/e′ ratio (11.9 [1] vs 7.8 [1]; P = .002); peak velocity of late transmitral flow (0.89 [0.19] m/s vs 0.54 [0.22] m/s; P<.001); tricuspid regurgitation velocity (2.73 [0.76] vs 2.22 [0.25]; P = .002); Right ventricular systolic pressure (33.5 [8] vs 25.0 [6]; P < .001); left atrial volume index (29 [10] vs 26 [13]; P = .01); and left ventricular diastolic dimension (46.4 [6] mm vs 46.3 [4] mm; P = .95).

Global longitudinal, circumferential and radial S and SRs

Values in the CAD group vs the control group (mean [SD]) were as follows: global longitudinal strain (GLS) (average, 16 segments) (−14.3% [4] vs −17.2% [3]; P < .001); global longitudinal SRs (−0.92 s−1 [0.2] vs −0.99 s−1 [0.1]; P = .07); global circumferential strain (CS) (−19.4% [6] vs −22.4% [4]; P = .02) and global circumferential SRs (−1.3 s−1 [0.4] vs −1.4 s−1 [0.3]; P = .16) Values (mean [SD]) were higher in the CAD group than in the control group for the following: global radial S (49% [37] vs 34% [16]; P = .03); global radial SRs (2.4 s−1 [1.5] vs 1.9 s−1 [0.7]; P = .05); and SD global longitudinal LV S TTP (99 ms [43] vs 33 ms [17]; P < .001) (Fig. 2, Table 2). The differences in global radial S, global radial SR, and 1 SD of the GLS TTP remained significant after adjustment for heart rate, blood pressure, LVEF, and body mass index in a multivariate model (odds ratio [OR], 5.4 [95% CI, 1.9-54.0]; P<.001), as well as for global longitudinal SRs (OR, 10 [95% CI, 2.5-203.9]; P < .001). In addition, we acquired data for the left ventricular mass index (LVMi) in order to classify patients with a value of >95 g/m2 as having left ventricular hypertrophy. According to this classification, six patients in the CAD group had left ventricular hypertrophy. However, the mean LVMi was 92 g/m2 (SD 31 g/m2) in the CAD group and 74 g/m2 (SD 15 g/m2). When we added LVMi to the multivariate model, dyssynchrony remained significant with a p value <0.01. Age proved to be a strong predictor (OR 1.25 [95% CI, 1.14-1.49]; P < .001); however, dyssynchrony continued to remain significant after adjusting for this variable. The cutoff value of −15.87% for GLS had 71% sensitivity and 74% specificity in differentiating the CAD group from the control group, with a ROC area under the curve (AUC) of 0.74 Table 3). The cutoff value of −21.31% for CS had 60% sensitivity and 60% specificity for differentiating the CAD group from the control group, with an AUC of 0.64 (Table 3).

Fig. 2
figure 2

Differences between the coronary artery disease and control groups. a Global LV longitudinal strain (P < .001). b dyssynchrony (P < .001). c Global radial S (P = .03). d Global circumferential strain (P = .02). LV indicates left ventricle; TTP, time-to-peak

Full size image
Table 2 Longitudinal and circumferential strain, systolic strain rate, and dyssynchrony
Full size table
Table 3 Data for receiver operating characteristic curves
Full size table

LV dyssynchrony

To assess mechanical dyssynchrony, the SD of GLS TTP was computed for the CAD and control groups, respectively (99 [43] ms vs 33 [17] ms; P < .001) (Table 2). To standardize for these differences, we followed the method described by Yu et al. (22). In brief, the mean of the SD plus 2 SDs for the control group were calculated from the GLS TTP. With this method, 65.87 ms was the cutoff value; 1 patient (3%) in the control group and 23 (66%) in the CAD group were above that value (P < .001). Values for longitudinal dyssynchrony for the control group and CAD group were significantly different (P < .001) (Fig. 2b). In addition, by using a cutoff of 45 ms for 1 SD LV longitudinal TTP, we were able to detect CAD in women with a sensitivity of 97% and specificity of 89%, with an AUC of 0.96 (Fig. 3a, Table 3). When we combined GLS, CS, and the SD of the LV longitudinal TTP, the sensitivity to detect CAD was 97% and specificity was 86% (Fig. 3b, Table 3).

Fig. 3
figure 3

a By using a cutoff value of 45 ms, for dyssynchrony, we were able to detect CAD in women with a sensitivity of 97% and specificity of 89%, with an AUC of 0.96. b By combining global longitudinal strain, CS and longitudinal dyssynchrony, the AUC was 0.96, with 97% sensitivity and 86% specificity. AUC indicates area under the curve; CAD, coronary artery disease; CS, circumferential strain; long, longitudinal; LV, left ventricular; lin1 (3), combination of global longitudinal S, CS, and SD long TTP LV; S, strain; TTP, time-to-peak

Full size image

Feasibility and reproducibility of S and systolic TTP measurements

STE tracking accuracy was assessed visually by one of the authors (R.T.H.). Measurements of S and TTP with acceptable tracking were feasible in 94.3% of the segments of the CAD group and in 97.1% of the segments in the control group. The intraobserver mean (SD) differences in longitudinal S and TTP variability were 8% (4%) and 7% (6%), respectively. The mean differences in CS and SRs variability were 6% (5%) and 10% (18%), respectively. The interobserver mean (SD) differences in variability for longitudinal S and SRs were 9% (8%) and 9% (5%), respectively. The CCC was calculated from 10 patients to compare reproducibility between the 2 examiners (J.A.K., S.B.G.). The CCC values for global longitudinal S and longitudinal S TTP were 0.922 (95% CI, 0.723-0.979) and 0.79 (95% CI, 0.446-0.931), respectively. Analysis was done using MedCalc software, version 14.10.2 (MedCalc, Ostend, Belgium).

Discussion

We performed a retrospective study to evaluate the clinical and echocardiographic variables of patients with documented CAD and compared them to patients with no CAD [26]. To our knowledge, this is the first study to measure S, SRs, TTP, and dyssynchrony in a population of women with known CAD. Our main findings were a significant reduction in longitudinal and CS and dyssynchrony in the CAD group compared with the control group. These findings were consistent in all longitudinal views (2-, 3-, and 4-chamber) and globally. The differences remained significant after adjusting for other clinical variables, such as heart rate, LVEF, left ventricular hypertrophy, blood pressure, body mass index, body surface area, and hyperlipidemia in a multivariate model analysis.

In addition, we were able to predict CAD using dyssynchrony with 97% sensitivity and 89% specificity and an AUC, 0.96. The results clearly show that GLS, longitudinal TTP, and CS were reduced, even though right ventricular S remained normal; this finding suggests that longitudinal S and TTP impairment occur early in response to insults that might result from CAD.

Other noninvasive methods have been used to evaluate the risk for CAD in women, including measurements of high-sensitivity C-reactive protein (HsCRP) and coronary artery calcium scoring [27]. The role of HsCRP has not been fully elucidated in studies to date. However, in women with metabolic syndrome, high levels of HsCRP have been found to correlate with a doubled risk of future cardiovascular events when women with this condition are compared with women who have metabolic syndrome but low levels of HsCRP [27]. In the MESA trial (Multi-Ethnic Study of Atherosclerosis), the coronary artery calcium score was shown to be a more sensitive risk-prediction tool than even the Framingham risk score for congestive heart disease and CAD in low-risk populations, demonstrating that the presence of any coronary calcium was associated with a 6-fold increased risk of CAD [28]. Although more studies of HsCRP and coronary artery calcium are needed, these methods represent advances being made in the noninvasive detection and risk assessment of CAD in women [29]. The MESA study particularly shows a relative inadequacy of the Framingham risk score for predicting CAD in women and highlights the need for better assessment of women in the low-risk category. We present our study as an adjunctive approach to the novel assessment of CAD risk [30].

CAD is an increasing concern in women, and as described earlier, more novel methods are needed to better predict its presence and severity. As women present to the clinic with nonspecific symptoms of CAD, clinicians need feasible diagnostic procedures to assess risk and likelihood of disease in order to better approach patient care. The findings of our study have the potential to greatly impact the advances in early detection and risk stratification of CAD in women, which could lead to preservation of cardiac function and a decrease in overall morbidity and mortality [22].

On the basis of our research, we believe that S and dyssynchrony parameters, measured by 2D-STE, could predict CAD in a population of symptomatic and asymptomatic women with normal EF. Our current study validates the need for a larger longitudinal study in women to determine the initial decline in S and systolic SR and to determine how this noninvasive method can project the overall decline in cardiac function and the early signs of ischemic insult. Such noninvasive measurements could allow a more aggressive approach for patients with these characteristics.

Limitations

This study was retrospective and limited by its small size. This resulted from the need to have a normal angiogram in all the controls. Our population was older because younger women were less likely to have an indication for stress echocardiography. Furthermore, it was challenging to find patients for the control group in the same age range as the study population because of the higher prevalence of cardiac issues in patients older than 70 years. Although our study population comprised older women with known CAD, which placed them in the high-risk Framingham category, our results confirm another useful, noninvasive method for stratifying patients who may have equivocal risk factors for CAD to better determine the need for aggressive medical management.

Conclusion

LV dyssynchrony measurements and longitudinal, circumferential, and radial S shown on 2D-STE can predict severe CAD in women with normal LVEF. This new technique should be incorporated into the diagnostic algorithm when there is suspicion that a woman might have CAD.

Abbreviations

2D-STE:

2-dimensional–speckle tracking echocardiography

AUC:

Area under the curve

CAD:

Coronary artery disease

CCC:

Concordance correlation coefficient

CS:

Circumferential strain

E:

Early mitral inflow velocity

e′:

Early diastolic mitral annular tissue velocity

EF:

Ejection fraction

GLS:

Global longitudinal strain

HsCRP:

High-sensitivity C-reactive protein

ICC:

Interclass correlation

LV:

Left ventricular

LVEF:

Left ventricular ejection fraction

MESA:

Multi-Ethnic Study of Atherosclerosis

OR:

Odds ratio

ROC:

Receiver operating coefficient

S:

Strain

SR:

Systolic strain rate

TTP:

Time-to-peak

VVI:

Velocity vector imaging

References

  1. McAloon CJ, Boylan LM, Hamborg T, Stallard N, Osman F, Lim PB, et al. The changing face of cardiovascular disease 2000-2012: an analysis of the World Health Organisation Global Health estimates data. Int J Cardiol. 2016;224:256–64.

    Article  PubMed  Google Scholar 

  2. Crendal E, Dutheil F, Naughton G, McDonald T, Obert P. Increased myocardial dysfunction, dyssynchrony, and epicardial fat across the lifespan in healthy males. BMC Cardiovasc Disord. 2014;14:95.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Kawamoto KR, Davis MB, Duvernoy CS. Acute coronary syndromes: differences in men and women. Curr Atheroscler Rep. 2016;18(12):73.

    Article  PubMed  Google Scholar 

  4. Simmons A, Pimentel R, Lakkireddy D. Sudden cardiac death in women. Rev Cardiovasc Med. 2012;13(1):e37–42.

    PubMed  Google Scholar 

  5. Regitz-Zagrosek V, Kararigas G. Mechanistic pathways of sex differences in cardiovascular disease. Physiol Rev. 2017;97(1):1–37.

    Article  PubMed  Google Scholar 

  6. Harvey RE, Coffman KE, Miller VM. Women-specific factors to consider in risk, diagnosis and treatment of cardiovascular disease. Womens Health (Lond). 2015;11(2):239–57.

    Article  CAS  Google Scholar 

  7. Kelly JP, Gupta N, Ayers C, Das SR, Berry JD, McGuire DK, et al. Characteristics of those with significant subclinical atherosclerosis without traditional risk factors: the Dallas heart study. J Am Coll Cardiol. 2011;57(14 Suppl):E881.

    Article  Google Scholar 

  8. Favot M, Courage C, Ehrman R, Khait L, Levy P. Strain echocardiography in acute cardiovascular diseases. West J Emerg Med. 2016;17(1):54–60.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Cai Q, Ahmad M. Left ventricular dyssynchrony by three-dimensional echocardiography: current understanding and potential future clinical applications. Echocardiography. 2015;32(8):1299–306.

    Article  PubMed  Google Scholar 

  10. Kleijn SA, Brouwer WP, Aly MF, Russel IK, de Roest GJ, Beek AM, et al. Comparison between three-dimensional speckle-tracking echocardiography and cardiac magnetic resonance imaging for quantification of left ventricular volumes and function. Eur Heart J Cardiovasc Imaging. 2012;13(10):834–9.

    Article  PubMed  Google Scholar 

  11. Feigenbaum H, Mastouri R, Sawada S. A practical approach to using strain echocardiography to evaluate the left ventricle. Circ J. 2012;76(7):1550–5.

    Article  PubMed  Google Scholar 

  12. Barros-Gomes S, Williams B, Nhola LF, Grogan M, Maalouf JF, Dispenzieri A, Pellikka PA, Villarraga HR. Prognosis of light chain amyloidosis with preserved LVEF: added value of 2D speckle-tracking echocardiography to the current prognostic staging system. JACC Cardiovasc Imaging. 2017;10(4):398–407.

    Article  PubMed  Google Scholar 

  13. Hsiao JF, Koshino Y, Bonnichsen CR, Yu Y, Miller FA Jr, Pellikka PA, et al. Speckle tracking echocardiography in acute myocarditis. Int J Cardiovasc Imaging. 2013;29(2):275–84.

    Article  PubMed  Google Scholar 

  14. Bakhoum S, Taha HS, Abdelmonem YY, Fahim M. Value of resting myocardial deformation assessment by two dimensional speckle tracking echocardiography to predict the presence, extent and localization of coronary artery affection in patients with suspected stable coronary artery disease. Egypt Heart J. 2016;3(68):171–9.

    Article  Google Scholar 

  15. Ryczek R, Krzesinski P, Krzywicki P, Smurzynski P, Cwetsch A. Two-dimensional longitudinal strain for the assessment of the left ventricular systolic function as compared with conventional echocardiographic methods in patients with acute coronary syndromes. Kardiol Pol. 2011;69(4):357–62.

    PubMed  Google Scholar 

  16. Fine NM, Topilsky Y, Oh JK, Hasin T, Kushwaha SS, Daly RC, et al. Role of echocardiography in patients with intravascular hemolysis due to suspected continuous-flow LVAD thrombosis. JACC Cardiovasc Imaging. 2013;6(11):1129–40.

    Article  PubMed  Google Scholar 

  17. Gould KL, Lipscomb K. Effects of coronary stenoses on coronary flow reserve and resistance. Am J Cardiol. 1974;34(1):48–55.

    Article  CAS  PubMed  Google Scholar 

  18. Arbab-Zadeh A, Fuster V. The risk continuum of atherosclerosis and its implications for defining CHD by coronary angiography. J Am Coll Cardiol. 2016;68(22):2467–78.

    Article  PubMed  Google Scholar 

  19. Fihn SD, Blankenship JC, Alexander KP, Bittl JA, Byrne JG, Fletcher BJ, Fonarow GC, Lange RA, Levine GN, Maddox TM, Naidu SS, Ohman EM, Smith PK, Anderson JL, Halperin JL, Albert NM, Bozkurt B, Brindis RG, Curtis LH, DeMets D, Guyton RA, Hochman JS, Kovacs RJ, Ohman EM, Pressler SJ, Sellke FW, Shen WK, American College of Cardiology/Americal Heart Association Task Force on Practice Guidelines; American Association for Thoracic Surgery; Preventive Cardiovascular Nurses Association; Society for Cardiovascular Angiography and Interventions; Society of Thoracic Surgeons. 2014 ACC/AHA/AATS/PCNA/SCAI/STS focused update of the guideline for the diagnosis and management of patients with stable ischemic heart disease: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines, and the American Association for Thoracic Surgery, Preventive Cardiovascular Nurses Association, Society for Cardiovascular Angiography and Interventions, and Society of Thoracic Surgeons. J Thorac Cardiovasc Surg. 2015;149(3):e5–23.

    Article  PubMed  Google Scholar 

  20. Rumberger JA. Coronary artery disease: a continuum, not a threshold. Mayo Clin Proc. 2017;92(3):323–6.

    Article  PubMed  Google Scholar 

  21. Wang ZJ, Zhang LL, Elmariah S, Han HY, Zhou YJ. Prevalence and prognosis of nonobstructive coronary artery disease in patients undergoing coronary angiography or coronary computed tomography angiography: a meta-analysis. Mayo Clin Proc. 2017;92(3):329–46.

    Article  PubMed  Google Scholar 

  22. Yu Y, Villarraga HR, Saleh HK, Cha SS, Pellikka PA. Can ischemia and dyssynchrony be detected during early stages of dobutamine stress echocardiography by 2-dimensional speckle tracking echocardiography? Int J Cardiovasc Imaging. 2013;29(1):95–102.

    Article  PubMed  Google Scholar 

  23. McGraw KO, Wong SP. Forming inferences about some intraclass correlation coefficients. Psych Methods. 1996;1(1):30–46.

    Article  Google Scholar 

  24. Shrout PE, Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psychol Bull. 1979;86(2):420–8.

    Article  CAS  PubMed  Google Scholar 

  25. Giavarina D. Understanding bland Altman analysis. Biochem Med (Zagreb). 2015;25(2):141–51.

    Article  Google Scholar 

  26. Kocabay G, Muraru D, Peluso D, Cucchini U, Mihaila S, Padayattil-Jose S, et al. Normal left ventricular mechanics by two-dimensional speckle-tracking echocardiography: reference values in healthy adults. Rev Esp Cardiol (Engl Ed). 2014;67(8):651–8.

    Article  Google Scholar 

  27. Manson JE, Bassuk SS. Biomarkers of cardiovascular disease risk in women. Metabolism. 2015;64(3 Suppl 1):S33–9. Epub 2014 Oct 30

    Article  CAS  PubMed  Google Scholar 

  28. Lakoski SG, Greenland P, Wong ND, Schreiner PJ, Herrington DM, Kronmal RA, et al. Coronary artery calcium scores and risk for cardiovascular events in women classified as “low risk” based on Framingham risk score: the multi-ethnic study of atherosclerosis (MESA). Arch Intern Med. 2007;167(22):2437–42.

    Article  PubMed  Google Scholar 

  29. Phillips LM, Mieres JH. Noninvasive assessment of coronary artery disease in women: what’s next? Curr Cardiol Rep. 2010;12(2):147–54.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Sharma K, Gulati M. Coronary artery disease in women: a 2013 update. Glob Heart. 2013;8(2):105–12.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

There was no external funding.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Author information

Authors and Affiliations

  1. Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, MN, USA

    Ryan T. Hubbard

  2. Department of Cardiovascular Diseases, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA

    Maria C. Arciniegas Calle, Sergio Barros-Gomes, Patricia A. Pellikka, Rajiv Gulati & Hector R. Villarraga

  3. Department of Orthopedic Research, Mayo Clinic, Rochester, MN, USA

    Joyce A. Kukuzke

Authors
  1. Ryan T. Hubbard
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maria C. Arciniegas Calle
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sergio Barros-Gomes
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Joyce A. Kukuzke
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Patricia A. Pellikka
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Rajiv Gulati
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hector R. Villarraga
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

HV conceived the study and it’s design. RH, JK, SB and MA worked on acquisition of data and analysis. HV, RH and MA worked on interpretation of data and drafting of the manuscript. RG and PP revised the manuscript critically. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Hector R. Villarraga.

Ethics declarations

Ethics approval and consent to participate

The Mayo Clinic Institutional Review Board approved the study, and all patients provided written consent to access their clinical electronic records and images.

Consent for publication

All patients provided written consent.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hubbard, R.T., Arciniegas Calle, M.C., Barros-Gomes, S. et al. 2-Dimensional Speckle Tracking Echocardiography predicts severe coronary artery disease in women with normal left ventricular function: a case-control study. BMC Cardiovasc Disord 17, 231 (2017). https://doi.org/10.1186/s12872-017-0656-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12872-017-0656-5

Keywords

BMC Cardiovascular Disorders

ISSN: 1471-2261

Contact us