The additive effect of metabolic syndrome on left ventricular impairment in patients with obstructive coronary artery disease assessed by 3.0 T cardiac magnetic resonance feature tracking

BACKGROUND

Metabolic syndrome (MetS) can increase the risk of morbidity and mortality of cardiovascular disease and obstructive coronary artery disease (OCAD), which usually have a poor prognosis. This study aimed to explore the impact of MetS on left ventricular (LV) deformation and function in OCAD patients and investigate the independent factors of impaired LV function and deformation.

MATERIALS AND METHODS

A total of 121 patients with OCAD and 52 sex- and age-matched controls who underwent cardiac magnetic resonance scanning were enrolled in the study. All OCAD patients were divided into two groups: OCAD with MetS [OCAD(MetS+), n = 83] and OCAD without MetS [OCAD(MetS-), n = 38]. LV functional and global strain parameters were measured and compared among the three groups. Multivariable linear regression analyses were constructed to investigate the independent factors of LV impairment in OCAD patients. Logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed to test the prediction efficiency of MetS for LV impairment.

RESULTS

From controls to the OCAD(MetS-) group to the OCAD(MetS+) group, LV mass (LVM) increased, and LV global function index (LVGFI) and LV global longitudinal peak strain (GLPS) decreased (all p < 0.05). Compared with the OCAD(MetS-) group, the LV GLPS declined significantly (p = 0.027), the LVM increased (p = 0.006), and the LVGFI decreased (p = 0.043) in the OCAD(MetS+) group. After adjustment for covariates in OCAD patients, MetS was an independent factor of decreased LV GLPS (β = - 0.211, p = 0.002) and increased LVM (β = 0.221, p = 0.003). The logistic multivariable regression analysis and ROC analysis showed that combined MetS improved the efficiency of predicting LV GLPS reduction (AUC = 0.88) and LVM (AUC = 0.89) increase.

CONCLUSIONS

MetS aggravated the damage of LV deformation and function in OCAD patients and was independently associated with LV deformation and impaired LV strain. Additionally, MetS increased the prediction efficiency of increased LVM and decreased LV GLPS. Early detection and intervention of MetS in patients with OCAD is of great significance.

Low HDL cholesterol and the eNOS Glu298Asp polymorphism are associated with inducible myocardial ischemia in patients with suspected stable coronary artery disease

BACKGROUND

The endothelial nitric oxide synthase (eNOS) gene deficiency is known to cause impaired coronary vasodilating capability in animal models. In the general clinical population, the eNOS gene polymorphisms, able to affect eNOS activity, were associated with cardiometabolic risk features and prevalence of coronary artery disease (CAD).

AIM

To investigate the association of eNOS Glu298Asp gene polymorphism, cardiometabolic profile, obstructive CAD and inducible myocardial ischemia in patients with suspected stable CAD.

METHODS

A total of 506 patients (314 males; mean age 62 ± 9 years) referred for suspected CAD was enrolled. Among these, 325 patients underwent stress ECG or cardiac imaging to assess the presence of inducible myocardial ischemia and 436 patients underwent non-invasive computerized tomography or invasive coronary angiography to assess the presence of obstructive CAD. Clinical characteristics and blood samples were collected for each patient.

RESULTS

In the whole population, 49.6% of patients were homozygous for the Glu298 genotype (Glu/Glu), 40.9% heterozygotes (Glu/Asp) and 9.5% homozygous for the 298Asp genotype (Asp/Asp). Obstructive CAD was documented in 178/436 (40.8%) patients undergoing coronary angiography while myocardial ischemia in 160/325 (49.2%) patients undergoing stress testing. Patients with eNOS Asp genotype (Glu/Asp + Asp/Asp) had no significant differences in clinical risk factors and in circulating markers. Independent predictors of obstructive CAD were age, gender, obesity, and low HDL-C. Independent predictors of myocardial ischemia were gender, obesity, low HDL-C and Asp genotype. In the subpopulation in which both stress tests and coronary angiography were performed, the Asp genotype remained associated with increased myocardial ischemia risk after adjustment for obstructive CAD.

CONCLUSION

In this population, low-HDL cholesterol was the only cardiometabolic risk determinant of obstructive CAD. The eNOS Glu298Asp gene polymorphism was significantly associated with inducible myocardial ischemia independently of other risk factors and presence of obstructive CAD.

Deep learning of heart-sound signals for efficient prediction of obstructive coronary artery disease

Background

Due to the limitations of current methods for detecting obstructive coronary artery disease (CAD), many individuals are mistakenly or unnecessarily referred for coronary angiography (CAG).

Objectives

Our goal is to create a comprehensive database of heart sounds in CAD and develop accurate deep learning algorithms to efficiently detect obstructive CAD based on heart sound signals. This will enable effective screening before undergoing CAG.

Methods

We included 320 subjects suspected of CAD who underwent CAG. We employed advanced filtering techniques and state-of-the-art deep learning models (VGG-16, 1D CNN, and ResNet18) to analyze the heart sound signals and identify obstructive CAD (defined as at least one ≥50 % stenosis). To assess the performance of our models, we prospectively recruited an additional 80 subjects for testing.

Results

In the test set, VGG-16 exhibited the highest performance with an area under the ROC curve (AUC) of 0.834 (95 % CI, 0.736-0.930), while ResNet-18 and CNN-7 achieved AUCs of only 0.755 (95 % CI, 0.614-0.819) and 0.652 (95 % CI, 0.554-0.770) respectively. VGG-16 demonstrated a sensitivity of 80.4 % and specificity of 86.2 % in the test set. The combined diagnostic model of VGG and DF scores achieved an AUC of 0.915 (95 % CI: 0.855-0.974), and the AUC for VGG combined with PTP scores was 0.908 (95 % CI: 0.845-0.971). The sensitivity and specificity of VGG-16 exceeded 0.85 in patients with coronary artery occlusion and those with 3 vascular lesions.

Conclusions

Our deep learning model, based on heart sounds, offers a non-invasive and efficient screening method for obstructive CAD. It is expected to significantly reduce the number of unnecessary referrals for downstream screening.

Radiomics analysis of pericoronary adipose tissue based on plain CT for preliminary screening of coronary artery disease in patients with type 2 diabetes mellitus

BACKGROUND

Type 2 diabetes mellitus (T2DM) is associated with a markedly increased prevalence of coronary artery disease (CAD). Radiomics features of pericoronary adipose tissue (PCAT) were correlated with inflammation, which may have potential value in the prediction of CAD.

PURPOSE

To determine whether radiomics analysis of PCAT captured by plain computed tomography (CT) could predict obstructive CAD in patients with T2DM.

MATERIAL AND METHODS

The study included 155 patients with T2DM with suspected CAD between January 2020 and December 2021. Volumes of right coronary artery of 10-50 mm were delineated in the plain CT to extract radiomics features and PCAT CT attenuation (PCATa). Least absolute shrinkage and selection operator was used to select the useful radiomics features to calculate the radiomics score (Rad-score). Univariate and multivariable logistic regression were applied to select independent predictors. The predictive performance was evaluated by the area under the receiver operating characteristics curve (AUC).

RESULTS

Rad-score (per 0.1 increments: odds ratio [OR] = 1.297; P < 0.001), coronary artery calcium score (CACS) (OR = 1.003; P = 0.037), and sex (OR = 3.245; P = 0.026) were identified as independent predictors for obstructive CAD. Rad-score (AUC = 0.835) outperformed CACS (AUC = 0.780), sex (AUC = 0.665), and PCATa (AUC = 0.550) in predicting obstructive CAD (P = 0.017 and 0.003 for Rad-score vs. sex and PCATa, respectively); however, the improvement between Rad-score and CACS had no statistical significance (P = 0.490).

CONCLUSION

Plain CT-derived Rad-score may be used as a preliminary screening tool for obstructive CAD in patients with T2DM.

Predictive value of a positive stress single-photon emission computed tomography or stress cardiac magnetic resonance for ruling in obstructive coronary artery disease in a real-world setting

INTRODUCTION AND OBJECTIVES

Randomized controlled trials comparing stress cardiac magnetic resonance (CMR) and single-photon emission computed tomography (SPECT) suggest similar diagnostic accuracy for detecting obstructive coronary artery disease (CAD). There are few data on whether this remains true in routine clinical practice. The aim of this study was to assess clinical and angiographic characteristics of patients undergoing invasive coronary angiography (ICA) after stress CMR or SPECT, and to compare their positive predictive value with published results from the CE-MARC trial.

METHODS

In this retrospective tertiary-center analysis, we included 429 patients undergoing ICA after a positive stress CMR or positive SPECT performed within the previous 12 months. Obstructive CAD was defined as any coronary artery stenosis ≥50% in a vessel compatible with the ischemic territory on stress testing.

RESULTS

Of the total 429 patients, 356 (83%) were referred after a positive SPECT, and 73 (17%) after a positive stress CMR. Patients did not differ according to age, cardiovascular risk factors, previous revascularization or left ventricular dysfunction, but patients with SPECT were more frequently male (p=0.046). The prevalence of obstructive CAD was similar in patients with positive SPECT vs. positive stress CMR (76.1% vs. 80.8%, respectively, p=0.385). The positive predictive values of both techniques were similar to those reported in the CE-MARC trial.

CONCLUSION

In this tertiary center analysis, stress CMR and SPECT showed similar positive predictive values, comparable to those reported in the CE-MARC trial. This finding supports the emerging adoption of CMR in clinical practice for the diagnosis and management of CAD.

Incremental effect of coronary obstruction on myocardial microvascular dysfunction in type 2 diabetes mellitus patients evaluated by first-pass perfusion CMR study

BACKGROUND

Type 2 diabetes mellitus (T2DM) frequently coexists with obstructive coronary artery disease (OCAD), which are at increased risk for cardiovascular morbidity and mortality. This study aimed to investigate the impact of coronary obstruction on myocardial microcirculation function in T2DM patients, and explore independent predictors of reduced coronary microvascular perfusion.

METHODS

Cardiac magnetic resonance (CMR) scanning was performed on 297 T2DM patients {188 patients without OCAD [T2DM(OCAD -)] and 109 with [T2DM(OCAD +)]} and 89 control subjects. CMR-derived perfusion parameters, including upslope, max signal intensity (MaxSI), and time to maximum signal intensity (TTM) in global and segmental (basal, mid-ventricular, and apical slices) were measured and compared among observed groups. According to the median of Gensini score (64), T2DM(OCAD +) patients were subdivided into two groups. Univariable and multivariable linear regression analyses were performed to identify independent predictors of microcirculation dysfunction.

RESULTS

T2DM(OCAD -) patients, when compared to control subjects, had reduced upslope and prolonged TTM in global and all of three slices (all P < 0.05). T2DM(OCAD +) patients showed a significantly more severe impairment of microvascular perfusion than T2DM(OCAD -) patients and control subjects with a more marked decline upslope and prolongation TTM in global and three slices (all P < 0.05). From control subjects, through T2DM(OCAD +) patients with Gensini score ≤ 64, to those patients with Gensini score > 64 group, the upslope declined and TTM prolonged progressively in global and mid-ventricular slice (all P < 0.05). The presence of OCAD was independently correlated with reduced global upslope (β =  - 0.104, P < 0.05) and global TTM (β = 0.105, P < 0.05) in patients with T2DM. Among T2DM(OCAD +) patients, Gensini score was associated with prolonged global TTM (r = 0.34, P < 0.001).

CONCLUSIONS

Coronary artery obstruction in the context of T2DM exacerbated myocardial microcirculation damage. The presence of OCAD and Gensini score were independent predictors of decreased microvascular function.

TRIAL REGISTRATION

Retrospectively registered.

Electrocardiogram-based deep learning algorithm for the screening of obstructive coronary artery disease

BACKGROUND

Information on electrocardiogram (ECG) has not been quantified in obstructive coronary artery disease (ObCAD), despite the deep learning (DL) algorithm being proposed as an effective diagnostic tool for acute myocardial infarction (AMI). Therefore, this study adopted a DL algorithm to suggest the screening of ObCAD from ECG.

METHODS

ECG voltage-time traces within a week from coronary angiography (CAG) were extracted for the patients who received CAG for suspected CAD in a single tertiary hospital from 2008 to 2020. After separating the AMI group, those were classified into ObCAD and non-ObCAD groups based on the CAG results. A DL-based model adopting ResNet was built to extract information from ECG data in the patients with ObCAD relative to those with non-ObCAD, and compared the performance with AMI. Moreover, subgroup analysis was conducted using ECG patterns of computer-assisted ECG interpretation.

RESULTS

The DL model demonstrated modest performance in suggesting the probability of ObCAD but excellent performance in detecting AMI. The AUC of the ObCAD model adopting 1D ResNet was 0.693 and 0.923 in detecting AMI. The accuracy, sensitivity, specificity, and F1 score of the DL model for screening ObCAD were 0.638, 0.639, 0.636, and 0.634, respectively, while the figures were up to 0.885, 0.769, 0.921, and 0.758 for detecting AMI, respectively. Subgroup analysis showed that the difference between normal and abnormal/borderline ECG groups was not notable.

CONCLUSIONS

ECG-based DL model showed fair performance for assessing ObCAD and it may serve as an adjunct to the pre-test probability in patients with suspected ObCAD during the initial evaluation. With further refinement and evaluation, ECG coupled with the DL algorithm may provide potential front-line screening support in the resource-intensive diagnostic pathways.

Cost-effectiveness of 82-Rubidium PET myocardial perfusion imaging for the diagnosis of myocardial ischemia depending on the prevalence of coronary artery disease

BACKGROUND

82-Rubidium-Positron emission tomography myocardial perfusion imaging (Rb-PET-MPI) offers higher diagnostic performance for the detection of myocardial ischemia compared to Tc-SPECT-MPI. The aim of this economic evaluation was to perform a cost-effectiveness analysis of Rb-PET-MPI versus Tc-SPECT-MPI in patients with suspected myocardial ischemia according to pretest probabilities (PTP) of obstructive coronary artery disease based on the results of the RUBIS Trial.

METHODS

Costs and effectiveness were calculated for all patients over 1 year and an incremental analysis of differences in costs and effectiveness in terms of diagnostic accuracy was performed. The uncertainty of the results was estimated using bootstrap. The analysis was conducted from the perspective of the French health care system with a time horizon of 12 months.

RESULTS

The average cost of a Rb-PET-MPI-based strategy for the detection of myocardial ischemia was €219 lower than a SPECT-MPI-based strategy (€1192 (± 1834) vs €973 (± 1939), p < 0.01). The one-year incremental cost-effectiveness ratio was negative: - €2730 (money saved per additional accurate diagnosis) in patients presenting PTP > 15% for the Rb-PET-MPI vs. Tc-SPECT-MPI strategy. Analysis of the joint distribution of costs and outcomes found that the Rb-PET-MPI strategy had a 92% probability to be dominant (cost-saving and outcome-improving).

CONCLUSIONS

Rb-PET-MPI is cost-effective compared to Tc-SPECT-MPI for the detection of myocardial ischemia in patients with PTP > 15% of obstructive coronary artery disease.

TRIAL REGISTRATION

RUBIS Trial registration: NCT01679886, Registered 03 September 2012, https://clinicaltrials.gov/ct2/show/NCT01679886 .

Comparison of risk assessment strategies incorporating coronary artery calcium score with estimation of pretest probability to defer cardiovascular testing in patients with stable chest pain

BACKGROUND

The risk assessment of patients with stable chest pain (SCP) to defer further cardiovascular testing is crucial, but the most appropriate risk assessment strategy remains unknown. We aimed to compare current strategies to identify low risk SCP patients.

METHODS

5289 symptomatic patients who had undergone coronary artery calcium score (CACS) and coronary computed tomographic angiography scan were identified and followed. Pretest probability (PTP) of obstructive coronary artery disease (CAD) for every patient was estimated according to European Society of Cardiology (ESC)-PTP model and CACS-weighted clinical likelihood (CACS-CL) model, respectively. Based on the 2019 ESC guideline-determined risk assessment strategy (ESC strategy) and CACS-CL model-based risk assessment strategy (CACS-CL strategy), all patients were divided into low and high risk group, respectively. Area under receiver operating characteristic curve (AUC), integrated discrimination improvement (IDI) and net reclassification improvement (NRI) was used.

RESULTS

CACS-CL model provided more robust estimation of PTP than ESC-PTP model did, with a larger AUC (0.838 versus 0.735, p < 0.0001), positive IDI (9%, p < 0.0001) and less discrepancy between observed and predicted probabilities. As a result, compared to ESC strategy which only applied CACS-CL model to patients with borderline ESC-PTP, CACS-CL strategy incorporating CACS with estimation of PTP to entire SCP patients indicated a positive NRI (19%, p < 0.0001) and a stronger association to major adverse cardiovascular events, with hazard ratios: 3.97 (95% confidence intervals: 2.75-5.72) versus 5.11 (95% confidence intervals: 3.40-7.69).

CONCLUSION

The additional use of CACS for all SCP patients in CACS-CL strategy improved the risk assessment of SCP patients to identify individuals at low risk.

Predictive value of CAC score combined with clinical features for obstructive coronary heart disease on coronary computed tomography angiography: a machine learning method

OBJECTIVE

We investigated the predictive value of clinical factors combined with coronary artery calcium (CAC) score based on a machine learning method for obstructive coronary heart disease (CAD) on coronary computed tomography angiography (CCTA) in individuals with atypical chest pain.

METHODS

The study included data from 1,906 individuals undergoing CCTA and CAC scanning because of atypical chest pain and without evidence for the previous CAD. A total of 63 variables including traditional cardiovascular risk factors, CAC score, laboratory results, and imaging parameters were used to build the Random forests (RF) model. Among all the participants, 70% were randomly selected to train the models on which fivefold cross-validation was done and the remaining 30% were regarded as a validation set. The prediction performance of the RF model was compared with two traditional logistic regression (LR) models.

RESULTS

The incidence of obstructive CAD was 16.4%. The area under the receiver operator characteristic (ROC) for obstructive CAD of the RF model was 0.841 (95% CI 0.820-0.860), the CACS model was 0.746 (95% CI 0.722-0.769), and the clinical model was 0.810 (95% CI 0.788-0.831). The RF model was significantly superior to the other two models (p < 0.05). Furthermore, the calibration curve and Hosmer-Lemeshow test showed that the RF model had good classification performance (p = 0.556). CAC score, age, glucose, homocysteine, and neutrophil were the top five important variables in the RF model.

CONCLUSION

RF model was superior to the traditional models in the prediction of obstructive CAD. In clinical practice, the RF model may improve risk stratification and optimize individual management.

Prognostic significance of obstructive coronary artery disease in patients admitted with acute decompensated heart failure: the ARIC study community surveillance

AIMS

We aimed to investigate the impact of obstructive coronary artery disease (CAD) in patients with acute decompensated heart failure (ADHF), and examine potential differences in prognostic utility for heart failure with reduced (HFrEF) versus preserved ejection fraction (HFpEF).

METHODS AND RESULTS

The Atherosclerosis Risk in Communities study conducted hospital surveillance of ADHF from 2005 to 2014. Obstructive CAD was defined as ≥50% or ≥75% stenosis, respectively, for the left main and other major epicardial arteries. Adjusted associations between obstructive CAD and 30-, 60-, and 90-day mortality were analysed. A total of 934 (4146 weighted) patients admitted with ADHF (mean age 72 years, 46% women, 30% Black, 30% HFpEF) had available angiography (61% performed in hospital). Obstructive CAD was more prevalent with HFrEF than HFpEF, whether at the left main (15% vs. 11%), left anterior descending (LAD) (48% vs. 30%), left circumflex (37% vs. 32%), right coronary (42% vs. 32%), or multiple coronary arteries (45% vs. 33%). In-hospital revascularization was performed in 25% and 22% of patients with HFrEF and HFpEF, respectively. Obstructive CAD was associated with higher adjusted mortality, particularly with left main or LAD involvement, and had a more pronounced association with 90-day mortality in HFrEF (odds ratio [OR] 2.77; 95% confidence interval [CI] 1.53-5.02) than HFpEF (OR 0.94; 95% CI 0.36-2.41) (p-interaction = 0.05).

CONCLUSION

Patients hospitalized with ADHF and coexisting obstructive CAD have higher short-term mortality, warranting the need for effective interventions and secondary prevention.

Value of territorial work efficiency estimation in non-ST-segment-elevation acute coronary syndrome: a study with non-invasive left ventricular pressure-strain loops

Non-ST-segment-elevation acute coronary syndrome (NSTE-ACS) patients with normal left ventricular (LV) ejection fraction (LVEF) and wall motion require a non-invasive tool to detect LV risk areas. This study utilized non-invasive LV pressure-strain loops to evaluate territorial myocardial work efficiency (WE) for identifying obstructive coronary artery stenosis, in patients with non-obstructive or obstructive coronary artery stenosis NSTE-ACS, the latter with or without occlusion. Global and territorial longitudinal strain (LS) analyses were performed via speckle-tracking imaging before coronary angiography. LV pressure-strain loops estimated global and territorial myocardial work index (MWI), constructive work (CW), wasted work (WW), and WE. Receiver operating characteristic curve analysis was used to determine the optimal cutoff value of independent parameters to detect obstructive coronary artery stenosis. Compared with non-obstructive, obstructive coronary artery stenosis showed significantly lower global and territorial LS, MWI, CW, and WE, and higher WW. Territorial LS, MWI, CW, and WE were significantly worse in territories of coronary occlusion. Territorial WE was the best parameter for predicting obstructive coronary artery stenosis (AUC 0.80, cutoff < 96%, sensitivity 73%, specificity 70%, P < 0.001). In patients with NSTE-ACS with normal wall motion and LVEF, territorial WE is more accurate than territorial LS or MWI to identify LV risk areas.

Coronary microvascular dysfunction in stable ischaemic heart disease (non-obstructive coronary artery disease and obstructive coronary artery disease)

Diffuse and focal epicardial coronary disease and coronary microvascular abnormalities may exist side-by-side. Identifying the contributions of each of these three players in the coronary circulation is a difficult task. Yet identifying coronary microvascular dysfunction (CMD) as an additional player in patients with coronary artery disease (CAD) may provide explanations of why symptoms may persist frequently following and why global coronary flow reserve may be more prognostically important than fractional flow reserve measured in a single vessel before percutaneous coronary intervention. This review focuses on the challenges of identifying the presence of CMD in the context of diffuse non-obstructive CAD and obstructive CAD. Furthermore, it is going to discuss the pathophysiology in this complex situation, examine the clinical context in which the interaction of the three components of disease takes place and finally look at non-invasive diagnostic methods relevant for addressing this question.

Automated calcium scores collected during myocardial perfusion imaging improve identification of obstructive coronary artery disease

Background

Myocardial perfusion imaging (MPI) is an accurate noninvasive test for patients with suspected obstructive coronary artery disease (CAD) and coronary artery calcium (CAC) score is known to be a powerful predictor of cardiovascular events. Collection of CAC scores simultaneously with MPI is unexplored.

Aim

We aimed to investigate whether automatically derived CAC scores during myocardial perfusion imaging would further improve the diagnostic accuracy of MPI to detect obstructive CAD.

Methods

We analyzed 150 consecutive patients without a history of coronary revascularization with suspected obstructive CAD who were referred for 82Rb PET/CT and available coronary angiographic data. Myocardial perfusion was evaluated both semi quantitatively as well as quantitatively according to the European guidelines. CAC scores were automatically derived from the low-dose attenuation correction CT scans using previously developed software based on deep learning. Obstructive CAD was defined as stenosis >70% (or >50% in the left main coronary artery) and/or fractional flow reserve (FFR) ≤0.80.

Results

In total 58% of patients had obstructive CAD of which seventy-four percent were male. Addition of CAC scores to MPI and clinical predictors significantly improved the diagnostic accuracy of MPI to detect obstructive CAD. The area under the curve (AUC) increased from 0.87 to 0.91 (p: 0.025). Sensitivity and specificity analysis showed an incremental decrease in false negative tests with our MPI + CAC approach (n = 14 to n = 4), as a consequence an increase in false positive tests was seen (n = 11 to n = 28).

Conclusion

CAC scores collected simultaneously with MPI improve the detection of obstructive coronary artery disease in patients without a history of coronary revascularization.

Cutaneous microvascular function in patients with obstructive or non-obstructive coronary artery disease evaluated by laser speckle contrast imaging

OBJECTIVE

This study aimed to compare cutaneous microvascular function in coronary artery disease (CAD) patients including obstructive CAD (ObCAD) (n = 133) and non-obstructive CAD (NObCAD) (n = 129) with that of age and gender matched healthy controls (n = 83) using laser speckle contrast imaging (LSCI) coupled with post-occlusive reactive hyperemia (PORH).

METHODS

LSCI system was used to assess subjects' cutaneous blood flow at rest and during PORH. CAD patients were divided into ObCAD and NObCAD group based on coronary angiography results.

RESULTS

Microvascular reactivity induced by PORH was significantly reduced in NObCAD group in comparison with control or ObCAD group (p < 0.05). Although, the PORH responses of ObCAD patients were also attenuated compared to controls, they did not reach statistical significance (p > 0.05).

CONCLUSION

NObCAD patients are more likely to develop cutaneous microvascular dysfunction than ObCAD patients, which may reflect the difference in the underlying mechanisms of myocardial ischemia.

Retinal fluorescein angiography: A sensitive and specific tool to predict coronary slow flow

Background

Obstructive coronary artery disease (OCAD) and coronary slow flow (CSF) are frequent angiographic findings for patients that have chest pain and require frequent hospital admission. The retina provides a window for detecting changes in microvasculature relating to the development of cardiovascular diseases such as arterial hypertension or coronary heart disease.

Objectives

To assess the coronary and ocular circulations in patients with CSF and those with obstructive coronary artery disease.

Methods

A prospective study was conducted over 3.5 years, included a total of 105 subjects classified to 4 groups: Group I (OCAD): Included 30 patients with obstructive coronary artery disease, group II (CSF): Included 30 patients with coronary slow-flow, group III (Control 1): Included 30 healthy control persons and group IV (Control 2): Included 15 patients indicated for coronary angiography that proved normal. All participants were subjected to coronary angiography (except control group 1), ophthalmic artery Doppler for measuring Pulsatility index (PI) and resistivity index (RI) and Fluorescence angiography of retinal vessels.

Results

Patients with CSF showed slow flow retinal circulation (microcirculation) evidenced by prolonged fluorescein angiography (Arm-retina time [ART] & Arterio-venous Transit time [AVTT]). Ophthalmic artery Doppler measurements (RI & PI) were significantly delayed in OCAD and CSF patients. There was significant positive correlation between TIMI frame count in all subjects and ART, AVTT, PI, RI and Body Mass Index. Using ART cutoff value of >16 s predicted CSF with sensitivity and specificity of 100%, meanwhile AVTT of >2 s predicted CSF with a sensitivity 96.7% and specificity of 93.3.

Conclusion

Both delayed arm-retina time and retinal arterio-venous transit times can accurately predict coronary slow-flow.

A simple prediction model to estimate obstructive coronary artery disease

BACKGROUND

A simple noninvasive model to predict obstructive coronary artery disease (OCAD) may promote risk stratification and reduce the burden of coronary artery disease (CAD). This study aimed to develop pre-procedural, noninvasive prediction models that better estimate the probability of OCAD among patients with suspected CAD undergoing elective coronary angiography (CAG).

METHODS

We included 1262 patients, who had reliable Framingham risk variable data, in a cohort without known CAD from a prospective registry of patients referred for elective CAG. We investigated pre-procedural OCAD (≥50% stenosis in at least one major coronary vessel based on CAG) predictors.

RESULTS

A total of 945 (74.9%) participants had OCAD. The final modified Framingham scoring (MFS) model consisted of anemia, high-sensitivity C-reactive protein, left ventricular ejection fraction, and five Framingham factors (age, sex, total and high-density lipoprotein cholesterol, and hypertension). Bootstrap method (1000 times) revealed that the model demonstrated a good discriminative power (c statistic, 0.729 ± 0.0225; 95% CI, 0.69-0.77). MFS provided adequate goodness of fit (P = 0.43) and showed better performance than Framingham score (c statistic, 0.703 vs. 0.521; P < 0.001) in predicting OCAD, thereby identifying patients with high risks for OCAD (risk score ≥ 27) with ≥70% predictive value in 68.8% of subjects (range, 37.2-87.3% for low [≤17] and very high [≥41] risk scores).

CONCLUSION

Our data suggested that the simple MFS risk stratification tool, which is available in most primary-level clinics, showed good performance in estimating the probability of OCAD in relatively stable patients with suspected CAD; nevertheless, further validation is needed.

SYNTAX score-0 patients: risk stratification in nonobstructive coronary artery disease

BACKGROUND

The complexity of coronary artery disease (CAD) is a predictor of cardiovascular events in patients with >50 % diameter stenosis as determined by SYNTAX score. Here, we compare the Gensini score to SYNTAX in patients with CAD as well as apply the Gensini score in patients with nonobstructive CAD (NOB-CAD), defined by ≤50 % diameter stenosis, were the SYNTAX score cannot be utilized to define future risk.

METHODS

The AtheroGene study enrolled 2316 patients [861/37.2 % with acute cardiovascular syndrome (ACS) and 1500/62.8 % with stable CAD (SCAD)]. Of these, 1966 had obstructive CAD (OB-CAD) with SYNTAX and Gensini scores available and 291 events with either cardiovascular mortality or non-fatal myocardial infarction were recorded. Furthermore, 350 patients had NOB-CAD with only Gensini score and 36 events. Median follow-up time was 4.9 years.

RESULTS

In the OB-CAD cohort the SYNTAX and the Gensini score predicted outcome. Kaplan-Meier curve analysis with the dichotomized Gensini score showed a significant result (p = 0.04) in the NOB-CAD cohort. Cox Regression analysis after adjustment showed a hazard ratio (HR) of 1.33 and p = 0.04 for the Gensini score in the NOB-CAD cohort. Receiver operating characteristic curve (ROC) analysis provided the highest area under the curve (AUC) regarding the outcome for the Gensini score with 0.65 (p = 0.004). Comparing the SYNTAX and Gensini score in this cohort showed improved discrimination of patients with events by the Gensini score (p = 0.02).

CONCLUSION

The Gensini score predicted events in patients with ≤50 % diameter lesions. Utilization of this score is useful to define risk in NOB-CAD patients.

Obstructive coronary artery disease in patients hospitalized for severe sepsis or septic shock with concomitant acute myocardial infarction

PURPOSE

It is difficult to differentiate type 1 acute myocardial infarction (AMI) with obstructive coronary artery disease (OCAD) from type 2 AMI in patients admitted for severe sepsis. The aims of this study were to assess the risk factors and prognosis of OCAD in patients admitted to the intensive care unit for severe sepsis with concomitant AMI.

MATERIALS AND METHODS

This is a single-center retrospective cohort study including all consecutive patients who were hospitalized for severe sepsis or septic shock between March 2006 and September 2014 and who underwent coronary angiography in the intensive care unit to identify AMI.

RESULTS

Overall, 78 (5.5%) of 1418 patients hospitalized for severe sepsis underwent coronary angiography to identify concomitant AMI. Thirty-two patients (41%) had OCAD. Following multivariate analysis, the risk factors of OCAD were peripheral vascular disease (odds ratio [OR] =5.7; 95% confidence interval [CI], 1.1-30.4; P = .042) and at least 2 cardiovascular risk factors (OR = 6.7; 95% CI, 1.9-23.8; P = .003). Obstructive coronary artery disease was associated with a significant mortality increase at 60 days (OR = 8.1; 95% CI, 1.9-30.2; P = .004).

CONCLUSIONS

Obstructive coronary artery disease is a poor prognosis factor in patients hospitalized for severe sepsis with concomitant AMI. In this setting, medical treatment should be considered for patients with peripheral vascular disease or with at least 2 cardiovascular risk factors; the need to perform coronary angiography should be considered carefully.

Development of new risk score for pre-test probability of obstructive coronary artery disease based on coronary CT angiography

Existing methods to calculate pre-test probability of obstructive coronary artery disease (CAD) have been established using selected high-risk patients who were referred to conventional coronary angiography. The purpose of this study is to develop and validate our new method for pre-test probability of obstructive CAD using patients who underwent coronary CT angiography (CTA), which could be applicable to a wider range of patient population. Using consecutive 4137 patients with suspected CAD who underwent coronary CTA at our institution, a multivariate logistic regression model including clinical factors as covariates calculated the pre-test probability (K-score) of obstructive CAD determined by coronary CTA. The K-score was compared with the Duke clinical score using the area under the curve (AUC) for the receiver-operating characteristic curve. External validation was performed by an independent sample of 319 patients. The final model included eight significant predictors: age, gender, coronary risk factor (hypertension, diabetes mellitus, dyslipidemia, smoking), history of cerebral infarction, and chest symptom. The AUC of the K-score was significantly greater than that of the Duke clinical score for both derivation (0.736 vs. 0.699) and validation (0.714 vs. 0.688) data sets. Among patients who underwent coronary CTA, newly developed K-score had better pre-test prediction ability of obstructive CAD compared to Duke clinical score in Japanese population.