Search

The technological evolution and widespread availability of wearables and handheld ECG devices capable of screening for atrial fibrillation (AF), and their promotion directly to consumers, has focused attention of health care professionals and patient organizations on consumer-led AF screening. In this Frontiers review, members of the AF-SCREEN International Collaboration provide a critical appraisal of this rapidly evolving field to increase awareness of the complexities and uncertainties surrounding consumer-led AF screening. Although there are numerous commercially available devices directly marketed to consumers for AF monitoring and identification of unrecognized AF, health care professional–led randomized controlled studies using multiple ECG recordings or continuous ECG monitoring to detect AF have failed to demonstrate a significant reduction in stroke. Although it remains uncertain if consumer-led AF screening reduces stroke, it could increase early diagnosis of AF and facilitate an integrated approach, including appropriate anticoagulation, rate or rhythm management, and risk factor modification to reduce complications. Companies marketing AF screening devices should report the accuracy and performance of their products in high- and low-risk populations and avoid claims about clinical outcomes unless improvement is demonstrated in randomized clinical trials. Generally, the diagnostic yield of AF screening increases with the number, duration, and temporal dispersion of screening sessions, but the prognostic importance may be less than for AF detected by single–time point screening, which is largely permanent, persistent, or high-burden paroxysmal AF. Consumer-initiated ECG recordings suggesting possible AF always require confirmation by a health care professional experienced in ECG reading, whereas suspicion of AF on the basis of photoplethysmography must be confirmed with an ECG. Consumer-led AF screening is unlikely to be cost-effective for stroke prevention in the predominantly young, early adopters of this technology. Studies in older people at higher stroke risk are required to demonstrate both effectiveness and cost-effectiveness. The direct interaction between companies and consumers creates new regulatory gaps in relation to data privacy and the registration of consumer apps and devices. Although several barriers for optimal use of consumer-led screening exist, results of large, ongoing trials, powered to detect clinical outcomes, are required before health care professionals should support widespread adoption of consumer-led AF screening.

Background: Atrial fibrillation (AF) has a substantial genetic basis. Identification of individuals at greatest AF risk could minimize the incidence of cardioembolic stroke. Methods: To determine whether genetic data can stratify risk for development of AF, we examined associations between AF genetic risk scores and incident AF in 5 prospective studies comprising 18 919 individuals of European ancestry. We examined associations between AF genetic risk scores and ischemic stroke in a separate study of 509 ischemic stroke cases (202 cardioembolic [40%]) and 3028 referents. Scores were based on 11 to 719 common variants (≥5%) associated with AF at P values ranging from −3 to −8 in a prior independent genetic association study. Results: Incident AF occurred in 1032 individuals (5.5%). AF genetic risk scores were associated with new-onset AF after adjustment for clinical risk factors. The pooled hazard ratio for incident AF for the highest versus lowest quartile of genetic risk scores ranged from 1.28 (719 variants; 95% confidence interval, 1.13–1.46; P =1.5×10 −4 ) to 1.67 (25 variants; 95% confidence interval, 1.47–1.90; P =9.3×10 −15 ). Discrimination of combined clinical and genetic risk scores varied across studies and scores (maximum C statistic, 0.629–0.811; maximum ΔC statistic from clinical score alone, 0.009–0.017). AF genetic risk was associated with stroke in age- and sex-adjusted models. For example, individuals in the highest versus lowest quartile of a 127-variant score had a 2.49-fold increased odds of cardioembolic stroke (95% confidence interval, 1.39–4.58; P =2.7×10 −3 ). The effect persisted after the exclusion of individuals (n=70) with known AF (odds ratio, 2.25; 95% confidence interval, 1.20–4.40; P =0.01). Conclusions: Comprehensive AF genetic risk scores were associated with incident AF beyond associations for clinical AF risk factors but offered small improvements in discrimination. AF genetic risk was also associated with cardioembolic stroke in age- and sex-adjusted analyses. Efforts are warranted to determine whether AF genetic risk may improve identification of subclinical AF or help distinguish between stroke mechanisms.

Background— Statins are important in vascular disease prevention in the elderly. However, the best method of selecting older patients for treatment is uncertain. We assessed the role of plasma lipoproteins as predictors of risk and of treatment benefit in the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER). Method and Results— The association of LDLc and HDLc with risk was examined in the 5804 70- to 82-year-old subjects of PROSPER. Baseline LDLc showed no relation to risk of the primary end point in the placebo group ( P =0.27), nor did on-treatment LDLc in the pravastatin group ( P =0.12). HDLc was inversely associated with risk in subjects on placebo ( P =0.0019) but not in those on pravastatin ( P =0.24). Risk reduction on pravastatin treatment was unrelated to baseline LDLc ( P =0.38) but exhibited a significant interaction with HDLc ( P =0.012). Subjects in the lowest 2 quintiles of HDLc (P P =0.53). During follow-up, there was no relation between achieved level of LDLc or HDLc and risk. However, the change in the LDLc/HDLc ratio on statin treatment appeared to account for the effects of therapy. Conclusions— In people >70 years old, HDLc appears to be a key predictor of risk and of treatment benefit. Findings in PROSPER suggest that statin therapy could usefully be targeted to those with HDLc 3.3.

The goals of electrocardiographic (ECG) monitoring in hospital settings have expanded from simple heart rate and basic rhythm determination to the diagnosis of complex arrhythmias, myocardial ischemia, and prolonged QT interval. Whereas computerized arrhythmia analysis is automatic in cardiac monitoring systems, computerized ST-segment ischemia analysis is available only in newer-generation monitors, and computerized QT-interval monitoring is currently unavailable. Even in hospitals with ST-monitoring capability, ischemia monitoring is vastly underutilized by healthcare professionals. Moreover, because no computerized analysis is available for QT monitoring, healthcare professionals must determine when it is appropriate to manually measure QT intervals (eg, when a patient is started on a potentially proarrhythmic drug). The purpose of the present review is to provide 'best practices' for hospital ECG monitoring. Randomized clinical trials in this area are almost nonexistent; therefore, expert opinions are based upon clinical experience and related research in the field of electrocardiography. This consensus document encompasses all areas of hospital cardiac monitoring in both children and adults. The emphasis is on information clinicians need to know to monitor patients safely and effectively. Recommendations are made with regard to indications, timeframes, and strategies to improve the diagnostic accuracy of cardiac arrhythmia, ischemia, and QT-interval monitoring. Currently available ECG lead systems are described, and recommendations related to staffing, training, and methods to improve quality are provided. (Circulation. 2004;110:2721-2746.)

Background —We examined the development of new diabetes mellitus in men aged 45 to 64 years during the West of Scotland Coronary Prevention Study. Methods and Results —Our definition of diabetes mellitus was based on the American Diabetic Association threshold of a blood glucose level of ≥7.0 mmol/L. Subjects who self-reported diabetes at baseline or had a baseline glucose level of ≥7.0 mmol/L were excluded from the analyses. A total of 5974 of the 6595 randomized subjects were included in the analysis, and 139 subjects became diabetic during the study. The baseline predictors of the transition from normal glucose control to diabetes were studied. In the univariate model, body mass index, log triglyceride, log white blood cell count, systolic blood pressure, total and HDL cholesterol, glucose, and randomized treatment assignment to pravastatin were significant predictors. In a multivariate model, body mass index, log triglyceride, glucose, and pravastatin therapy were retained as predictors of diabetes in this cohort. Conclusions —We concluded that the assignment to pravastatin therapy resulted in a 30% reduction ( P =0.042) in the hazard of becoming diabetic. By lowering plasma triglyceride levels, pravastatin therapy may favorably influence the development of diabetes, but other explanations, such as the anti-inflammatory properties of this drug in combination with its endothelial effects, cannot be excluded with these analyses.

Background —The study of QT dispersion (QTd) is of increasing clinical interest, but there are very few data in large healthy populations. Furthermore, there is still discussion on the extent to which QTd reflects dispersion of measurement. This study addresses these problems. Methods and Results —Twelve-lead ECGs recorded on 1501 apparently healthy adults and 1784 healthy neonates, infants, and children were used to derive normal limits of QTd and QT intervals by use of a fully automated approach. No age gradient or sex differences in QTd were seen and it was found that an upper limit of 50 ms was highly specific. Three-orthogonal-lead ECGs (n=1220) from the Common Standards for Quantitative Electrocardiography database were used to generate derived 12-lead ECGs, which had a significant increase in QTd of 10.1±13.1 ms compared with the original orthogonal-lead ECG but a mean difference of only 1.63±12.2 ms compared with the original 12-lead ECGs. In a population of 361 patients with old myocardial infarction, there was a statistically significant increase in mean QTd compared with that of the adult normal group (32.7±10.0 versus 24.53±8.2 ms; P Conclusions —These data indicate that QTd is age and sex independent, has a highly specific upper normal limit of 50 ms, is significantly lower in the 3-orthogonal-lead than in the 12-lead ECG, and is longer in patients with a previous myocardial infarction than in normal subjects.

Background— The microsomal triglyceride transfer protein (MTP) transfers lipids into apolipoprotein B-containing lipoproteins for secretion from liver, intestine, and heart. The T-variant of a functional polymorphism in the MTP promoter, MTP-493G/T, has been associated with reduced low-density lipoprotein cholesterol concentrations. We hypothesize that this polymorphism impacts on coronary heart disease (CHD) risk. Methods and Results— The effect of the polymorphism was therefore tested in the West of Scotland Coronary Prevention Study biobank (580 cases and 1160 controls). MTP-493T carrier status was associated with significantly increased risk of CHD despite a small reduction in total cholesterol. Compared with the genotypic group with the lowest event rate (MTP-493GG, pravastatin treatment), the respective odds ratios (95% confidence interval) in the placebo group for CHD events were: GG, 1.23 (0.92 to 1.63); GT, 1.53 (1.12 to 2.08); and TT, 2.78 (1.53 to 5.05), suggestive of a gene-dose effect. The excess risk for CHD of the MTP-493T-variant was eliminated by pravastatin treatment. The Uppsala Longitudinal Study of Adult Men (ULSAM), which is a 20-year follow-up study of CHD, was used as an independent confirmatory database. These unexpected findings prompted the investigation of non-plasma lipid factors that could associate the MTP gene with CHD risk. In a limited number of subjects (n=18), heart muscle biopsies showed a MTP-493T genotype-specific depression of MTP mRNA expression. Conclusion— The MTP-493T variant confers an increased risk of CHD that is unrelated to plasma lipids and lipoproteins, but eliminated by pravastatin treatment. A direct effect of the MTP polymorphism on myocardial lipid metabolism and vulnerability upon ischemic damage cannot be excluded.

To the Editor: I would like to extend the comments of Sattar et al1 on the metabolic syndrome and its relationship to diabetes mellitus. In data presented at the American Academy of Family Physicians Annual Scientific Assembly (1999) and at the 2001 Drugs Affecting Lipid Metabolism symposium, I noted that the incidence of diabetes in patients with combined low HDL cholesterol and elevated triglycerides (TG) was 45% and the incidence of impaired glucose tolerance was 18%. (The data presented were a proposed classification of lipid disorders based on LDL and HDL cholesterol, stratified by TG). This group contained the highest number of patients with impaired glucose tolerance/diabetes of any of the possible LDL, HDL, and TG combinations—ie, high LDL, normal HDL, and low TG versus normal LDL, normal HDL, and …

Background— The National Cholesterol Education Program (NCEP) recently proposed a simple definition for metabolic syndrome. Information on the prospective association of this definition for coronary heart disease (CHD) and type 2 diabetes is currently limited. Methods and Results— We used a modified NCEP definition with body mass index in place of waist circumference. Baseline assessments in the West of Scotland Coronary Prevention Study were available for 6447 men to predict CHD risk and for 5974 men to predict incident diabetes over 4.9 years of follow-up. Mean LDL cholesterol was similar but C-reactive protein was higher ( P P =0.045) in a multivariate model incorporating conventional risk factors. Men with 4 or 5 features of the syndrome had a 3.7-fold increase in risk for CHD and a 24.5-fold increase for diabetes compared with men with none (both P Conclusions— A modified NCEP metabolic syndrome definition predicts CHD events, and, more strikingly, new-onset diabetes, and thus helps identify individuals who may receive particular benefit from lifestyle measures to prevent these diseases.

Background Risk factors specific to sudden cardiac death (SCD), ie, death within 1 hour after onset of symptoms, have been poorly identified, although recent findings from the present study incriminate heavy drinking and elevated heart rate. This paper examines the relations between a wide range of established and potential risk factors for ischemic heart disease (IHD) and SCD to identify independent risk factors for SCD and factors that might particularly or specifically relate to SCD. Methods and Results We present a prospective study of a cohort that was drawn from general practices in 24 British towns of 7735 middle-aged men who were followed up for 8 years. During 8 years of follow-up, the men experienced 488 major IHD events (nonfatal and fatal), of which 117 (24%) were classified as SCD. Age, preexisting IHD, arrhythmia, systolic blood pressure, blood cholesterol, elevated heart rate (≥90 beats per minute), physical activity (all, P P =.06), HDL cholesterol ( P P Conclusions Three risk factors appear to be specific or particular to the risk of SCD, and these and other risk factors operate differently in patients with versus those without preexisting IHD. These findings have implications for the causes and prevention of SCD.