Dataset Information

Temporal variability of T-wave morphology and risk of sudden cardiac death in patients with coronary artery disease.

ABSTRACT:

Background

The possible relationship between temporal variability of electrocardiographic spatial heterogeneity of repolarization and the risk of sudden cardiac death (SCD) in patients with coronary artery disease (CAD) is not completely understood.

Methods

The standard deviation of T-wave morphology dispersion (TMD-SD), of QRST angle (QRSTA-SD), and of T-wave area dispersion (TW-Ad-SD) were analyzed on beat-to-beat basis from 10 min period of the baseline electrocardiographic recording in ARTEMIS study patients with angiographically verified CAD.

Results

After on average of 8.6 ± 2.3 years of follow-up, a total of 66 of the 1,678 present study subjects (3.9%) had experienced SCD or were resuscitated from sudden cardiac arrest (SCA). TMD-SD was most closely associated with the risk for SCD and was significantly higher in patients who had experienced SCD/SCA compared with those who remained alive (3.61 ± 2.83 vs. 2.64 ± 2.52, p = .008, respectively), but did not differ significantly between the patients who had experienced non-SCD (n = 71, 4.2%) and those who remained alive (3.20 ± 2.73 vs. 2.65 ± 2.53, p = .077, respectively) or between the patients who succumbed to non-cardiac death (n = 164, 9.8%) and those who stayed alive (2.64 ± 2.17 vs. 2.68 ± 2.58, p = .853). After adjustments with relevant clinical risk indicators of SCD/SCA, TMD-SD still predicted SCD/SCA (HR 1.107, 95% CIs 1.035-1.185, p = .003).

Conclusions

Temporal variability of electrocardiographic spatial heterogeneity of repolarization represented by TMD-SD independently predicts long-term risk of SCD/SCA in patients with CAD.

SUBMITTER: Rahola JT

PROVIDER: S-EPMC8164143 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Coronary artery spasm (CAS) plays an important role in the pathogeneses of various ischemic heart diseases and has gradually become a common cause of life-threatening arrhythmia. The specific molecular mechanism of CAS has not been fully elucidated, nor are there any specific diagnostic markers for the condition. Therefore, this study aimed to examine the specific molecular mechanism underlying CAS, and screen for potential diagnostic markers. To this end, we successfully constructed a rat CAS model and achieved in vitro culture of a human coronary-artery smooth-muscle cell (hCASMC) contraction model. Possible molecular mechanisms by which protein kinase C (PKC) regulated CAS through the C kinase-potentiated protein phosphatase 1 inhibitor of 17 kDa (CPI-17)/myosin II regulatory light chain (MLC2) pathway were studied in vivo and in vitro to screen for potential molecular markers of CAS. We performed hematoxylin and eosin staining, myocardial zymogram, and transmission electron microscopy to determine myocardial and coronary artery injury in CAS rats. Then, using immunohistochemical staining, immunofluorescence staining, and Western blotting, we further demonstrated a potential molecular mechanism by which PKC regulated CAS via the CPI-17/MLC2 pathway. The results showed that membrane translocation of PKCα occurred in the coronary arteries of CAS rats. CPI-17/MLC2 signaling was observably activated in coronary arteries undergoing CAS. In addition, in vitro treatment of hCASMCs with angiotensin II (Ang II) increased PKCα membrane translocation while consistently activating CPI-17/MLC2 signaling. Conversely, GF-109203X and calphostin C, specific inhibitors of PKC, inactivated CPI-17/MLC2 signaling. We also collected the coronary artery tissues from deceased subjects suspected to have died of CAS and measured their levels of phosphorylated CPI-17 (p-CPI-17) and MLC2 (p-MLC2). Immunohistochemical staining was positive for p-CPI-17 and p-MLC2 in the tissues of these subjects. These findings suggest that PKCα induced CAS through the CPI-17/MLC2 pathway; therefore, p-CPI-17 and p-MLC2 could be used as potential markers for CAS. Our data provide novel evidence that therapeutic strategies against PKC or CPI-17/MLC2 signaling might be promising in the treatment of CAS.

Project description:BackgroundLate gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) offers the potential to noninvasively characterize the phenotypic substrate for sudden cardiac death (SCD).ObjectivesThe authors assessed the utility of infarct characterization by CMR, including scar microstructure analysis, to predict SCD in patients with coronary artery disease (CAD).MethodsPatients with stable CAD were prospectively recruited into a CMR registry. LGE quantification of core infarction and the peri-infarct zone (PIZ) was performed alongside computational image analysis to extract morphologic and texture scar microstructure features. The primary outcome was SCD or aborted SCD.ResultsOf 437 patients (mean age: 64 years; mean left ventricular ejection fraction [LVEF]: 47%) followed for a median of 6.3 years, 49 patients (11.2%) experienced the primary outcome. On multivariable analysis, PIZ mass and core infarct mass were independently associated with the primary outcome (per gram: HR: 1.07 [95% CI: 1.02-1.12]; P = 0.002 and HR: 1.03 [95% CI: 1.01-1.05]; P = 0.01, respectively), and the addition of both parameters improved discrimination of the model (Harrell's C-statistic: 0.64-0.79). PIZ mass, however, did not provide incremental prognostic value over core infarct mass based on Harrell's C-statistic or risk reclassification analysis. Severely reduced LVEF did not predict the primary endpoint after adjustment for scar mass. On scar microstructure analysis, the number of LGE islands in addition to scar transmurality, radiality, interface area, and entropy were all associated with the primary outcome after adjustment for severely reduced LVEF and New York Heart Association functional class of >1. No scar microstructure feature remained associated with the primary endpoint when PIZ mass and core infarct mass were added to the regression models.ConclusionsComprehensive LGE characterization independently predicted SCD risk beyond conventional predictors used in implantable cardioverter-defibrillator (ICD) insertion guidelines. These results signify the potential for a more personalized approach to determining ICD candidacy in CAD.