scholarly journals Sudden unexpected cardiac death as a function of time since the detection of electrocardiographic and clinical risk factors in apparently healthy men: The Manitoba Follow-Up Study, 1948 to 2004

2006 ◽  
Vol 22 (3) ◽  
pp. 205-211 ◽  
Author(s):  
T. Edward Cuddy ◽  
Robert B. Tate
Keyword(s):  
Risk Factors ◽  
Cardiac Death ◽  
Clinical Risk Factors ◽  
Healthy Men ◽  
Follow Up Study ◽  
Clinical Risk ◽  
Apparently Healthy

scholarly journals Dynamic predictive accuracy of electrocardiographic biomarkers of sudden cardiac death within a survival framework: the Atherosclerosis Risk in Communities (ARIC) study

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Erick A. Perez-Alday ◽  
Aron Bender ◽  
David German ◽  
Srini V. Mukundan ◽  
Christopher Hamilton ◽  
...  
Keyword(s):  
Risk Factors ◽  
Sudden Cardiac Death ◽  
Cardiac Death ◽  
Predictive Accuracy ◽  
Clinical Risk Factors ◽  
Short Term ◽  
Clinical Risk ◽  
Atherosclerosis Risk

Abstract Background The risk of sudden cardiac death (SCD) is known to be dynamic. However, the accuracy of a dynamic SCD prediction is unknown. We aimed to measure the dynamic predictive accuracy of ECG biomarkers of SCD and competing non-sudden cardiac death (non-SCD). Methods Atherosclerosis Risk In Community study participants with analyzable ECGs in sinus rhythm were included (n = 15,716; 55% female, 73% white, age 54.2 ± 5.8 y). ECGs of 5 follow-up visits were analyzed. Global electrical heterogeneity and traditional ECG metrics (heart rate, QRS, QTc) were measured. Adjudicated SCD was the primary outcome; non-SCD was the competing outcome. Time-dependent area under the receiver operating characteristic curve (ROC(t) AUC) analysis was performed to assess the prediction accuracy of a continuous biomarker in a period of 3,6,9 months, and 1,2,3,5,10, and 15 years using a survival analysis framework. Reclassification improvement as compared to clinical risk factors (age, sex, race, diabetes, hypertension, coronary heart disease, stroke) was measured. Results Over a median 24.4 y follow-up, there were 577 SCDs (incidence 1.76 (95%CI 1.63–1.91)/1000 person-years), and 829 non-SCDs [2.55 (95%CI 2.37–2.71)]. No ECG biomarkers predicted SCD within 3 months after ECG recording. Within 6 months, spatial ventricular gradient (SVG) elevation predicted SCD (AUC 0.706; 95%CI 0.526–0.886), but not a non-SCD (AUC 0.527; 95%CI 0.303–0.75). SVG elevation more accurately predicted SCD if the ECG was recorded 6 months before SCD (AUC 0.706; 95%CI 0.526–0.886) than 2 years before SCD (AUC 0.608; 95%CI 0.515–0.701). Within the first 3 months after ECG recording, only SVG azimuth improved reclassification of the risk beyond clinical risk factors: 18% of SCD events were reclassified from low or intermediate risk to a high-risk category. QRS-T angle was the strongest long-term predictor of SCD (AUC 0.710; 95%CI 0.668–0.753 for ECG recorded within 10 years before SCD). Conclusion Short-term and long-term predictive accuracy of ECG biomarkers of SCD differed, reflecting differences in transient vs. persistent SCD substrates. The dynamic predictive accuracy of ECG biomarkers should be considered for competing SCD risk scores. The distinction between markers predicting short-term and long-term events may represent the difference between markers heralding SCD (triggers or transient substrates) versus markers identifying persistent substrate.

scholarly journals Dynamic Predictive Accuracy of Electrocardiographic Biomarkers of Sudden Cardiac Death within a Survival Framework: The Atherosclerosis Risk in Communities (ARIC) study

2019 ◽  
Author(s):  
Erick Perez-Alday ◽  
Aron Bender ◽  
David German ◽  
Srini Mukundan ◽  
Christopher Hamilton ◽  
...  
Keyword(s):  
Risk Factors ◽  
Sudden Cardiac Death ◽  
Cardiac Death ◽  
Predictive Accuracy ◽  
Clinical Risk Factors ◽  
Short Term ◽  
Clinical Risk ◽  
Atherosclerosis Risk

Abstract Background—The risk of sudden cardiac death (SCD) is known to be dynamic. However, an accuracy of a dynamic SCD prediction is unknown. We aimed to measure dynamic predictive accuracy of ECG biomarkers of SCD and competing non-SCD. Methods—Atherosclerosis Risk In Community study participants with analyzable ECGs in sinus rhythm were included (n=15,716; 55% female, 73% white, age 54.2±5.8 y). ECGs of 5 follow-up visits were analyzed. Global electrical heterogeneity and traditional ECG metrics were measured. Adjudicated SCD was the primary outcome; non-SCD was competing outcome. Time-dependent area under the (receiver operating characteristic) curve (AUC) analysis was performed to assess prediction accuracy of a continuous biomarker in a period of 3,6,9 months, and 1,2,3,5,10, and 15 years, using survival analysis framework. Reclassification improvement as compared to clinical risk factors (age, sex, race, diabetes, hypertension, coronary heart disease, stroke) was measured. Results—Over a median 24.4 y follow-up, there were 577 SCDs (incidence 1.76 (95%CI 1.63-1.91)/1,000 person-years), and 829 non-SCDs [2.55 (95%CI 2.37-2.71)]. Short-term, spatial ventricular gradient (SVG) elevation predicted SCD (AUC 0.706; 95%CI 0.526-0.886), but not a non-SCD. Short-term, upward and more likely forward–directed SVG vector predicted SCD, whereas backward-directed SVG predicted non-SCD. Within the first 3 months after ECG recording, only SVG azimuth improved reclassification of the risk beyond clinical risk factors (18% SCD events reclassified up). Long-term, backward–directed SVG predicted both SCD and non-SCD. Conclusion—Short-term predictors of SCD, non-SCD, and biomarkers of long-term SCD risk differed, reflecting differences in transient vs. persistent SCD substrates.

scholarly journals Dynamic Predictive Accuracy of Electrocardiographic Biomarkers of Sudden Cardiac Death within a Survival Framework: The Atherosclerosis Risk in Communities (ARIC) study

2019 ◽  
Author(s):  
Erick Perez-Alday ◽  
Aron Bender ◽  
David German ◽  
Srini Mukundan ◽  
Christopher Hamilton ◽  
...  
Keyword(s):  
Risk Factors ◽  
Sudden Cardiac Death ◽  
Cardiac Death ◽  
Predictive Accuracy ◽  
Clinical Risk Factors ◽  
Short Term ◽  
Clinical Risk ◽  
Atherosclerosis Risk

Abstract Background—The risk of sudden cardiac death (SCD) is known to be dynamic. However, the accuracy of a dynamic SCD prediction is unknown. We aimed to measure the dynamic predictive accuracy of ECG biomarkers of SCD and competing non-sudden cardiac death (non-SCD). Methods—Atherosclerosis Risk In Community study participants with analyzable ECGs in sinus rhythm were included (n=15,716; 55% female, 73% white, age 54.2±5.8 y). ECGs of 5 follow-up visits were analyzed. Global electrical heterogeneity and traditional ECG metrics (heart rate, QRS, QTc) were measured. Adjudicated SCD was the primary outcome; non-SCD was competing outcome. Time-dependent area under the receiver operating characteristic curve (ROC(t) AUC) analysis was performed to assess the prediction accuracy of a continuous biomarker in a period of 3,6,9 months, and 1,2,3,5,10, and 15 years using survival analysis framework. Reclassification improvement as compared to clinical risk factors (age, sex, race, diabetes, hypertension, coronary heart disease, stroke) was measured. Results—Over a median 24.4 y follow-up, there were 577 SCDs (incidence 1.76 (95%CI 1.63-1.91)/1,000 person-years), and 829 non-SCDs [2.55 (95%CI 2.37-2.71)]. No ECG biomarkers predicted SCD within 3 months after ECG recording. Within 6 months, spatial ventricular gradient (SVG) elevation predicted SCD (AUC 0.706; 95%CI 0.526-0.886), but not a non-SCD (AUC 0.527; 95%CI 0.303-0.75). SVG elevation more accurately predicted SCD if ECG was recorded 6 months before SCD (AUC 0.706; 95%CI 0.526-0.886) than 2 years before SCD (AUC 0.608; 95%CI 0.515-0.701). Within the first 3 months after ECG recording, only SVG azimuth improved reclassification of the risk beyond clinical risk factors: 18% SCD events were reclassified from low or intermediate risk to a high-risk category. Long-term, QRS-T angle was the strongest predictor of SCD (AUC 0.710; 95%CI 0.668-0.753 for ECG recorded within 10 years before SCD). Conclusion—Short-term and long-term predictive accuracy of ECG biomarkers of SCD differed, reflecting differences in transient vs. persistent SCD substrates. The dynamic predictive accuracy of ECG biomarkers should be considered for competing SCD risk scores. The distinction between markers predicting short-term and long-term events may represent the difference between markers heralding SCD (triggers or transient substrates) versus markers identifying persistent substrate.

scholarly journals Dynamic Predictive Accuracy of Electrocardiographic Biomarkers of Sudden Cardiac Death within a Survival Framework: The Atherosclerosis Risk in Communities (ARIC) study

2019 ◽  
Author(s):  
Erick Perez-Alday ◽  
Aron Bender ◽  
David German ◽  
Srini Mukundan ◽  
Christopher Hamilton ◽  
...  
Keyword(s):  
Risk Factors ◽  
Sudden Cardiac Death ◽  
Cardiac Death ◽  
Predictive Accuracy ◽  
Clinical Risk Factors ◽  
Short Term ◽  
Clinical Risk ◽  
Atherosclerosis Risk

Abstract Background—The risk of sudden cardiac death (SCD) is known to be dynamic. However, the accuracy of a dynamic SCD prediction is unknown. We aimed to measure the dynamic predictive accuracy of ECG biomarkers of SCD and competing non-sudden cardiac death (non-SCD). Methods—Atherosclerosis Risk In Community study participants with analyzable ECGs in sinus rhythm were included (n=15,716; 55% female, 73% white, age 54.2±5.8 y). ECGs of 5 follow-up visits were analyzed. Global electrical heterogeneity and traditional ECG metrics (heart rate, QRS, QTc) were measured. Adjudicated SCD was the primary outcome; non-SCD was competing outcome. Time-dependent area under the receiver operating characteristic curve (ROC(t) AUC) analysis was performed to assess the prediction accuracy of a continuous biomarker in a period of 3,6,9 months, and 1,2,3,5,10, and 15 years using survival analysis framework. Reclassification improvement as compared to clinical risk factors (age, sex, race, diabetes, hypertension, coronary heart disease, stroke) was measured. Results—Over a median 24.4 y follow-up, there were 577 SCDs (incidence 1.76 (95%CI 1.63-1.91)/1,000 person-years), and 829 non-SCDs [2.55 (95%CI 2.37-2.71)]. No ECG biomarkers predicted SCD within 3 months after ECG recording. Within 6 months, spatial ventricular gradient (SVG) elevation predicted SCD (AUC 0.706; 95%CI 0.526-0.886), but not a non-SCD (AUC 0.527; 95%CI 0.303-0.75). SVG elevation more accurately predicted SCD if ECG was recorded 6 months before SCD (AUC 0.706; 95%CI 0.526-0.886) than 2 years before SCD (AUC 0.608; 95%CI 0.515-0.701). Within the first 3 months after ECG recording, only SVG azimuth improved reclassification of the risk beyond clinical risk factors: 18% SCD events were reclassified from low or intermediate risk to a high-risk category. Long-term, QRS-T angle was the strongest predictor of SCD (AUC 0.710; 95%CI 0.668-0.753 for ECG recorded within 10 years before SCD). Conclusion—Short-term and long-term predictive accuracy of ECG biomarkers of SCD differed, reflecting differences in transient vs. persistent SCD substrates. The dynamic predictive accuracy of ECG biomarkers should be considered for competing SCD risk scores. The distinction between markers predicting short-term and long-term events may represent the difference between markers heralding SCD (triggers or transient substrates) versus markers identifying persistent substrate.

Long-Term Follow-Up of Patients With Isolated Side Branch Coronary Artery Disease

Angiology ◽  
2021 ◽  
pp. 000331972110280
Author(s):  
Sukru Arslan ◽  
Ahmet Yildiz ◽  
Okay Abaci ◽  
Urfan Jafarov ◽  
Servet Batit ◽  
...  
Keyword(s):  
Risk Factors ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Vessel Diameter ◽  
Side Branch ◽  
Clinical Risk Factors ◽  
Clinical Risk ◽  
Artery Disease

The data with respect to stable coronary artery disease (SCAD) are mainly confined to main vessel disease. However, there is a lack of information and long-term outcomes regarding isolated side branch disease. This study aimed to evaluate long-term major adverse cardiac and cerebrovascular events (MACCEs) in patients with isolated side branch coronary artery disease (CAD). A total of 437 patients with isolated side branch SCAD were included. After a median follow-up of 38 months, the overall MACCE and all-cause mortality rates were 14.6% and 5.9%, respectively. Among angiographic features, 68.2% of patients had diagonal artery and 82.2% had ostial lesions. In 28.8% of patients, the vessel diameter was ≥2.75 mm. According to the American College of Cardiology lesion classification, 84.2% of patients had either class B or C lesions. Age, ostial lesions, glycated hemoglobin A1c, and neutrophil levels were independent predictors of MACCE. On the other hand, side branch location, vessel diameter, and lesion complexity did not affect outcomes. Clinical risk factors seem to have a greater impact on MACCE rather than lesion morphology. Therefore, the treatment of clinical risk factors is of paramount importance in these patients.

Simple Laboratory Test-Based Risk Scores in Coronary Catheterization: Development, Validation, and Comparison to Conventional Risk Factors

2020 ◽  
Vol 5 (4) ◽  
pp. 616-630
Author(s):  
Michael E Gerling ◽  
Yuan Dong ◽  
Beelal Abdalla ◽  
Matthew T James ◽  
Stephen B Wilton ◽  
...  
Keyword(s):  
Risk Factors ◽  
Laboratory Tests ◽  
Clinical Risk Factors ◽  
Risk Scores ◽  
Mean Corpuscular Hemoglobin ◽  
Blood Cell Count ◽  
Corpuscular Hemoglobin ◽  
Coronary Catheterization ◽  
Clinical Risk

Abstract Background We developed and validated laboratory test–based risk scores (i.e., lab risk scores) to reclassify mortality risk among patients undergoing their first coronary catheterization. Methods Patients were catheterized between 2009 and 2015 in Calgary, Alberta, Canada (n = 14 135, derivation cohort), and in Edmonton, Alberta, Canada (n = 12 143, validation cohort). Logistic regression with group LASSO (least absolute shrinkage and selection operator) penalty was used to select quintiles of the last laboratory tests (red blood cell count, mean corpuscular hemoglobin concentration, mean corpuscular hemoglobin, mean corpuscular volume, red cell distribution width, platelet count, total white blood cell count, plasma sodium, potassium, chloride, CO2, international normalized ratio, estimated glomerular filtration rate) performed <30 days before catheterization and by age and sex that were significantly associated with death ≤60  and >60 days after catheterization. Follow-up was until 2016. Risk scores were developed from significant tests, internally validated in Calgary among bootstrap samples and externally validated in Edmonton after recalibration using coefficients developed in Calgary. Interaction tests were performed, and net reclassification improvement vs conventional demographic and clinical risk factors was determined. Results Lab risk scores were strongly associated with mortality (29–40× for top vs bottom quintile, P for trends <0.01), had good discrimination and were well calibrated in Calgary (C = 0.80–0.85, slope = 0.99–1.01) and Edmonton (C = 0.80–0.82; slope = 1.02–1.05)—similar to demographic and clinical risk factors alone. Associations were attenuated by several comorbidities; however, scores appropriately reclassified 11%–20% of deaths (both follow-up periods) and 6%–9% of survivors (>60 days) after catheterization vs demographic and clinical risk factors. Conclusions In 2 populations of patients undergoing their first coronary catheterization, risk scores based on simple laboratory tests were as powerful as a combination of demographic and clinical risk factors in predicting mortality. Lab risk scores should be used for patients undergoing coronary catheterization.

Abstract P251: The Impact of Clinical Risk Factors on Risk of Peripheral Arterial Disease in Men

Circulation ◽  
2012 ◽  
Vol 125 (suppl_10) ◽  
Author(s):  
Michel M Joosten ◽  
Jennifer K Pai ◽  
Eric B Rimm ◽  
Donna Spiegelman ◽  
Murray A Mittleman ◽  
...  
Keyword(s):  
Risk Factors ◽  
Peripheral Arterial Disease ◽  
Arterial Disease ◽  
Clinical Risk Factors ◽  
Individual Risk ◽  
Clinical Risk ◽  
Hazard Ratios ◽  
History Of ◽  
Peripheral Arterial

Background: Previous studies have examined individual risk factors in relation to peripheral arterial disease (PAD) but the combined effects of these factors are largely unknown. We investigated the degree to which clinical risk factors may explain the risk of PAD among men. Methods: We prospectively followed 45,596 men from the Health Professional Follow-up Study without a history of cardiovascular disease at baseline during a 22-year period (1986–2008). We defined four clinical risk factors - smoking, history of type 2 diabetes, hypertension, and hypercholesterolemia - that were updated biennially during follow-up. Cox proportional hazard models were used to compare PAD risk across individual and joint risk factors. Results: During 874,769 person-years of follow-up, 497 confirmed PAD cases occurred. All four clinical risk factors were significantly and independently associated with a higher risk of PAD after multivariate adjustment (Figure). Risk of PAD more than doubled (hazard ratio: 2.14; 95% confidence interval [95% CI]: 1.95–2.35) for each additional risk factor compared with the group free of risk factors. Men without any of the four risk factors had a relative risk of PAD of 0.19 compared with all other men (95% CI: 0.11–0.31). In 96.8% (95% CI: 95.2–98.3%) of the PAD cases, at least one of the four risk factors was present. Overall, 8 out of 10 cases of PAD appeared to be attributable to these four conventional risk factors. Conclusion: The great majority of PAD can be explained by four conventional risk factors. Figure legend: Hazard ratios for incident peripheral arterial disease (PAD) according to individual and joint risk factors. Hazard ratios are adjusted for age, height, aspirin use, family history of myocardial infarction before age 60 y, geographical region, body mass index, physical activity, alcohol consumption (and each of the other three binary clinical risk factors in the individual risk factor analyses).

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