Large-scale pharmacogenomic study of sulfonylureas and the QT, JT and QRS intervals: CHARGE Pharmacogenomics Working Group.

Sulfonylureas, a commonly used class of medication used to treat type 2 diabetes, have been associated with an increased risk of cardiovascular disease. Their effects on QT interval duration and related electrocardiographic phenotypes are potential mechanisms for this adverse effect. In 11 ethnically diverse cohorts that included 71 857 European, African-American and Hispanic/Latino ancestry individuals with repeated measures of medication use and electrocardiogram (ECG) measurements, we conducted a pharmacogenomic genome-wide association study of sulfonylurea use and three ECG phenotypes: QT, JT and QRS intervals. In ancestry-specific meta-analyses, eight novel pharmacogenomic loci met the threshold for genome-wide significance (P<5 × 10-8), and a pharmacokinetic variant in CYP2C9 (rs1057910) that has been associated with sulfonylurea-related treatment effects and other adverse drug reactions in previous studies was replicated. Additional research is needed to replicate the novel findings and to understand their biological basis.

Pharmacogenomics study of thiazide diuretics and QT interval in multi-ethnic populations: the cohorts for heart and aging research in genomic epidemiology.

Thiazide diuretics, commonly used antihypertensives, may cause QT interval (QT) prolongation, a risk factor for highly fatal and difficult to predict ventricular arrhythmias. We examined whether common single-nucleotide polymorphisms (SNPs) modified the association between thiazide use and QT or its component parts (QRS interval, JT interval) by performing ancestry-specific, trans-ethnic and cross-phenotype genome-wide analyses of European (66%), African American (15%) and Hispanic (19%) populations (N=78 199), leveraging longitudinal data, incorporating corrected standard errors to account for underestimation of interaction estimate variances and evaluating evidence for pathway enrichment. Although no loci achieved genome-wide significance (P<5 × 10-8), we found suggestive evidence (P<5 × 10-6) for SNPs modifying the thiazide-QT association at 22 loci, including ion transport loci (for example, NELL1, KCNQ3). The biologic plausibility of our suggestive results and simulations demonstrating modest power to detect interaction effects at genome-wide significant levels indicate that larger studies and innovative statistical methods are warranted in future efforts evaluating thiazide-SNP interactions.

Antidepressants and heart-rate variability in older adults: a population-based study.

BACKGROUND: Tricyclic antidepressants (TCAs) and selective serotonin reuptake inhibitors (SSRIs) may be associated with lower heart rate variability (HRV), a condition associated with increased mortality risk. We aimed to investigate the association between TCAs, SSRIs and HRV in a population-based study. METHOD: In the prospective Rotterdam Study cohort, up to five electrocardiograms (ECGs) per participant were recorded (1991-2012). Two HRV variables were studied based on 10-s ECG recordings: standard deviation of normal-to-normal RR intervals (SDNN) and root mean square of successive RR interval differences (RMSSD). We compared the HRV on ECGs recorded during use of antidepressants with the HRV on ECGs recorded during non-use of any antidepressant. Additionally, we analysed the change in HRV on consecutive ECGs. Those who started or stopped using antidepressants before the second ECG were compared with non-users on two ECGs. RESULTS: We included 23 647 ECGs from 11 729 participants (59% women, mean age 64.6 years at baseline). Compared to ECGs recorded during non-use of antidepressants (n = 22 971), SDNN and RMSSD were lower in ECGs recorded during use of TCAs (n = 296) and SSRIs (n = 380). Participants who started using TCAs before the second ECG had a decrease in HRV and those who stopped had an increase in HRV compared to consistent non-users (p < 0.001). Starting or stopping SSRIs was not associated with HRV changes. CONCLUSION: TCAs were associated with a lower HRV in all analyses, indicating a real drug effect. For SSRIs the results are mixed, indicating a weaker association, possibly due to other factors.

Drug-gene interactions and the search for missing heritability: a cross-sectional pharmacogenomics study of the QT interval.

Variability in response to drug use is common and heritable, suggesting that genome-wide pharmacogenomics studies may help explain the 'missing heritability' of complex traits. Here, we describe four independent analyses in 33 781 participants of European ancestry from 10 cohorts that were designed to identify genetic variants modifying the effects of drugs on QT interval duration (QT). Each analysis cross-sectionally examined four therapeutic classes: thiazide diuretics (prevalence of use=13.0%), tri/tetracyclic antidepressants (2.6%), sulfonylurea hypoglycemic agents (2.9%) and QT-prolonging drugs as classified by the University of Arizona Center for Education and Research on Therapeutics (4.4%). Drug-gene interactions were estimated using covariable-adjusted linear regression and results were combined with fixed-effects meta-analysis. Although drug-single-nucleotide polymorphism (SNP) interactions were biologically plausible and variables were well-measured, findings from the four cross-sectional meta-analyses were null (Pinteraction>5.0 × 10(-8)). Simulations suggested that additional efforts, including longitudinal modeling to increase statistical power, are likely needed to identify potentially important pharmacogenomic effects.

Resting heart rate and incident atrial fibrillation: A stratified Mendelian randomization in the AFGen consortium.

BACKGROUND: Both elevated and low resting heart rates are associated with atrial fibrillation (AF), suggesting a U-shaped relationship. However, evidence for a U-shaped causal association between genetically-determined resting heart rate and incident AF is limited. We investigated potential directional changes of the causal association between genetically-determined resting heart rate and incident AF. METHOD AND RESULTS: Seven cohorts of the AFGen consortium contributed data to this meta-analysis. All participants were of European ancestry with known AF status, genotype information, and a heart rate measurement from a baseline electrocardiogram (ECG). Three strata of instrumental variable-free resting heart rate were used to assess possible non-linear associations between genetically-determined resting heart rate and the logarithm of the incident AF hazard rate: <65; 65-75; and >75 beats per minute (bpm). Mendelian randomization analyses using a weighted resting heart rate polygenic risk score were performed for each stratum. We studied 38,981 individuals (mean age 59±10 years, 54% women) with a mean resting heart rate of 67±11 bpm. During a mean follow-up of 13±5 years, 4,779 (12%) individuals developed AF. A U-shaped association between the resting heart rate and the incident AF-hazard ratio was observed. Genetically-determined resting heart rate was inversely associated with incident AF for instrumental variable-free resting heart rates below 65 bpm (hazard ratio for genetically-determined resting heart rate, 0.96; 95% confidence interval, 0.94-0.99; p = 0.01). Genetically-determined resting heart rate was not associated with incident AF in the other two strata. CONCLUSIONS: For resting heart rates below 65 bpm, our results support an inverse causal association between genetically-determined resting heart rate and incident AF.

Effect of minimally invasive autopsy and ethnic background on acceptance of clinical postmortem investigation in adults.

OBJECTIVES: Autopsy rates worldwide have dropped significantly over the last five decades. Imaging based autopsies are increasingly used as alternatives to conventional autopsy (CA). The aim of this study was to investigate the effect of the introduction of minimally invasive autopsy, consisting of CT, MRI and tissue biopsies on the overall autopsy rate (of CA and minimally invasive autopsy) and the autopsy rate among different ethnicities. METHODS: We performed a prospective single center before-after study. The intervention was the introduction of minimally invasive autopsy as an alternative to CA. Minimally invasive autopsy consisted of MRI, CT, and CT-guided tissue biopsies. Autopsy rates over time and the effect of introducing minimally invasive autopsy were analyzed with a linear regression model. We performed a subgroup analysis comparing the autopsy rates of two groups: a group of western-European ethnicity versus a group of other ethnicities. RESULTS: Autopsy rates declined from 14.0% in 2010 to 8.3% in 2019. The linear regression model showed a significant effect of both time and availability of minimally invasive autopsy on the overall autopsy rate. The predicted autopsy rate in the model started at 15.1% in 2010 and dropped approximately 0.1% per month (ß = -0.001, p < 0.001). Availability of minimally invasive autopsy increased the overall autopsy rate by 2.4% (ß = 0.024, p < 0.001). The overall autopsy rate of people with an ethnic background other than western-European was significantly higher in years when minimally invasive autopsy was available compared to when it was not (22/176 = 12.5% vs. 81/1014 (8.0%), p = 0.049). CONCLUSIONS: The introduction of the minimally invasive autopsy had a small, but significant effect on the overall autopsy rate. Furthermore, the minimally invasive autopsy appears to be more acceptable than CA among people with an ethnicity other than western-European.

Mapping the domain of medical informatics.

OBJECTIVES: The domain of medical informatics (MI) is not well defined. It covers a wide range of research topics. Our objective is to characterize the field of MI by means of the scientific literature in this domain. METHODS: We used titles and abstracts from MEDLINE records of papers published between July 1993 and July 2008, and extracted uni-, bi- and trigrams as features. Starting with the ISI category of medical informatics, we applied a semi-automated procedure to identify the set of journals and proceedings pertaining to MI. A clustering algorithm was subsequently applied to the articles from this set of publications. RESULTS: MI literature can be divided into three subdomains: 1) the organization, application, and evaluation of health information systems, 2) medical knowledge representation, and 3) signal and data analysis. Over the last fifteen years, the field has remained relatively stable, although most journals have shifted their focus somewhat. CONCLUSIONS: We identified the scientific literature pertaining to the field of MI, and the main areas of research. We were able to show trends in the field, and the positioning of different journals within this field.

Minimum bandwidth requirements for recording of pediatric electrocardiograms.

BACKGROUND: Previous studies that determined the frequency content of the pediatric ECG had their limitations: the study population was small or the sampling frequency used by the recording system was low. Therefore, current bandwidth recommendations for recording pediatric ECGs are not well founded. We wanted to establish minimum bandwidth requirements using a large set of pediatric ECGs recorded at a high sampling rate. METHODS AND RESULTS: For 2169 children aged 1 day to 16 years, a 12-lead ECG was recorded at a sampling rate of 1200 Hz. The averaged beats of each ECG were passed through digital filters with different cut off points (50 to 300 Hz in 25-Hz steps). We measured the absolute errors in maximum QRS amplitude for each simulated bandwidth and determined the percentage of records with an error >25 microV. We found that in any lead, a bandwidth of 250 Hz yields amplitude errors <25 microV in >95% of the children <1 year. For older children, a gradual decrease in ECG frequency content was demonstrated. CONCLUSIONS: We recommend a minimum bandwidth of 250 Hz to record pediatric ECGs. This bandwidth is considerably higher than the previous recommendation of 150 Hz from the American Heart Association.

Atrial fibrillation and the risk of cerebral white matter lesions.

BACKGROUND: Cerebral white matter lesions are often observed on MRI scans of elderly nondemented and demented persons. Their pathogenesis is not fully understood but cerebral hypoperfusion may be involved. Atrial fibrillation is a common finding in elderly subjects and may lead to a reduced cardiac output with cerebral hypoperfusion. The authors investigated the association between atrial fibrillation and the presence of white matter lesions. METHODS: From 1995 through 1996, the authors randomly sampled 1077 subjects from two ongoing prospective population-based studies. From each participant, an electrocardiogram (ECG) was recorded; atrial fibrillation and left ventricular hypertrophy were diagnosed with a computer program. For one of the two groups (553 subjects), earlier ECGs were available (mean follow-up 4.7 years). All subjects underwent 1.5-T MRI scanning; white matter lesions were separately rated for the periventricular and subcortical regions. RESULTS: The prevalence of atrial fibrillation was 1.9% among subjects younger than 75 years and 5.5% in subjects older than 75 years. The total number of subjects with atrial fibrillation was 28. Subjects with atrial fibrillation had severe periventricular white matter lesions more than twice as often as subjects who did not (RR 2.2; 95% CI 1.0 to 5.2) but had no increased risk of subcortical white matter lesions (RR 1.1; 95% CI 0.4 to 2.6). For seven subjects with atrial fibrillation both at baseline and at follow up, these relative risks were 6.3 (95% CI 1.1 to 37.1) and 0.7 (95% CI 0.1 to 3.7). CONCLUSIONS: Atrial fibrillation is associated with periventricular white matter lesions, but not with subcortical white matter lesions.

Accurate automatic detection of electrode interchange in the electrocardiogram.

In recording an electrocardiogram (ECG), an interchange of electrodes may easily go unnoticed. Automatic detection would be desirable, but current algorithms, when dealing with more than left arm-right arm reversal, have moderate sensitivity. We propose a novel approach that uses the redundancy of information in the standard 12-lead ECG. We assume that each of the 8 independent electrocardiographic leads can be reconstructed from the 7 others in reasonable approximation. The correlation between any electrocardiographic lead and its reconstruction should be higher if the electrodes are correctly placed than when some interchange were present. The difference in correlation should have discriminative power. This was verified on a set of 3,305 ECGs for 14 common electrode interchange errors. The material was split in a learning and test set, and general reconstruction coefficients were computed from the learning set. For each interchange, electrode-error ECGs were derived by rearranging leads of the unaltered ECGs. Correlations between the actual leads and their reconstructions were computed for all ECGs. From the differences in lead correlation, decision rules were derived for each kind of interchange. All 14 rules had specificities of > or =99.5% in the test set. Sensitivities were > or =93% for 11 rules, and left arm-left leg electrode reversal scored low.

Improvement of automated electrocardiographic diagnosis by combination of computer interpretations of the electrocardiogram and vectorcardiogram.

In the international project "Common Standards for Quantitative Electrocardiography" (CSE), diagnostic results of different computer programs for the interpretation of the electrocardiogram (ECG) and of the vectorcardiogram (VCG) were combined, and it was shown that the "combined program" performs better than each program separately. Because the program MEANS (Modular ECG Analysis System) comprises 2 different classification programs--one for the ECG, the other for the VCG--this allowed investigation of whether the combined interpretations would yield a better diagnostic result than either one separately. This approach requires that a VCG always be recorded in addition to the ECG. To circumvent this complication, the VCG was reconstructed from the simultaneously recorded ECG leads. This reconstructed VCG was then interpreted by the VCG classification program, whereupon the diagnostic interpretations of the ECG and the reconstructed VCG were combined. For the validation, the CSE database of documented ECGs and VCGs (n = 1,220) was used. The combination of the ECG and VCG interpretations yielded a better diagnostic result than each interpretation program separately (total accuracy 74.2% (ECG + VCG) vs 69.8% (ECG) and 70.2% (VCG), p less than 0.001 in both cases). The results for the reconstructed VCG (total accuracy 70.5%) are comparable to those for the ECG and the VCG (p greater than 0.10 in both cases). The performance of the combined interpretations of ECG and reconstructed VCG (total accuracy 73.6%) is approximately the same as that of the combined ECG and VCG (p greater than 0.10). Thus, the performance of an ECG computer program can be improved by incorporating both ECG and VCG classificatory knowledge, using only the ECG itself.

Prolonged QT interval: a tricky diagnosis?

Prolonged heart-rate adjusted QT intervals on the electrocardiogram (ECG) are associated with an increased risk for coronary heart disease and sudden death. However, the diagnosis of the prolonged QT interval is hampered by lack of standards. We studied variations in the prevalence of prolonged QT, based on different common definitions, in a large nonhospitalized population, and compared our results with other studies applying the same definitions. The study population consisted of 2,200 men and 3,366 women participants of the Rotterdam Study, > or =55 years old. The QT interval was computed by our Modular ECG Analysis System (MEANS). Three different formulas to adjust QT for heart rate were used: Bazett's formula (QTc), a linear regression equation (QTlr), and the QT index (QTI). Prolonged QT occurred frequently in both men and women, and its prevalence increased with age. Women had longer heart-rate adjusted QT intervals than men (mean QTc 433 ms vs 422 ms), and mean values for QTlr were lower than for QTc (mean QTlr 422 ms in women and 412 ms in men). Prevalence was highest for prolonged QTlr (31% in men and 26% in women) and lowest for prolonged QTI (6% in men and 9% in women). Comparison with other studies applying the same correction formulas showed large discrepancies in prevalence estimates of prolonged QTc and QTlr, and to a lesser degree of prolonged QTI, possibly due to differences in measurement techniques. Future research is needed to relate QT interval to prognosis, to obtain measurement technique specific reference values of heart-rate adjusted QT measurements, and to obtain age- and sex-specific threshold values for prolonged QT. Such data are needed to use the QT interval with confidence.

Diagnostic interpretation of electrocardiograms in population-based research: computer program research physicians, or cardiologists?

We assessed the performance of diagnostic electrocardiogram (ECG) interpretation by the computer program MEANS and by research physicians, compared to cardiologists, in a physician-based study. To establish a strategy for ECG interpretation in health surveys, we also studied the diagnostic capacity of three scenarios: use of the computer program alone (A), computer program and cardiologist (B), and computer program, research physician, and cardiologist (C). A stratified random sample of 381 ECGs was drawn from ECGs collected in the Rotterdam Study (n = 3057), which were interpreted both by a trained research physician using a form for structured clinical evaluation and by MEANS. All ECGs were interpreted independently by two cardiologists; if they disagreed (n = 175) the ECG was judged by a third cardiologist. Five ECG diagnoses were considered: anterior and inferior myocardial infarction (MI), left and right bundle branch block (LBBB and RBBB), and left ventricular hypertrophy (LVH). Overall, sensitivities and specificities of MEANS and the research physicians were high. The sensitivity of MEANS ranged from 73.8% to 92.9% and of the research physician ranged from 71.8% to 96.9%. The specificity of MEANS ranged from 97.5% to 99.8% and of the research physician from 96.3% to 99.6%. To diagnose LVH, LBBB, and RBBB, use of the computer program alone gives satisfactory results. Preferably, all positive findings of anterior and inferior MI by the program should be verified by a cardiologist. We conclude that diagnostic ECG interpretation by computer can be very helpful in population-based research, being at least as good as ECG interpretation by a trained research physician, but much more efficient and therefore less expensive.

Measurement error as a source of QT dispersion: a computerised analysis.

OBJECTIVE: To establish a general method to estimate the measuring error in QT dispersion (QTD) determination, and to assess this error using a computer program for automated measurement of QTD. SUBJECTS: Measurements were done on 1220 standard simultaneous 12 lead electrocardiograms. DESIGN: The computer program was validated against two observers on a random subset of 100 electrocardiograms. Simple laws of physics require that at least five of the six extremity leads have the same QT duration. This allows the direct assessment of the error in measuring QTD derived from five extremity leads (QTD5). It also enables ST-T amplitude dependent distributions of measurement error in determining QT duration to be established. These QT error distributions were then used to estimate the error in measuring QTD from all 12 leads (QTD12). MAIN OUTCOME MEASURES: Mean and standard deviation of error in measuring QTD duration, QTD5, and QTD12. RESULTS: Performance of the program was comparable to that of observers. Errors in measuring QT duration (measured QT minus reference QT) fell from a mean (SD) of 6.9 (17.1) ms for ST-T amplitudes < 50 microV to -1.4 (6.3) ms for amplitudes > 350 microV. Measurement errors of QTD5 and QTD12 were 20.4 (11.5) ms and 29.4 (14.9) ms. CONCLUSIONS: The fact that no QTD can exist between five of the six extremity leads provides a means of estimating QTD measurement error. Measuring error of QT duration is dependent on ST-T amplitude. QTD measurement error is large compared with typical QTD values reported.

Interference removal with an improved incremental estimation filter.

Mains interference in digitized electrocardiographic signals is often removed with a nonlinear filter, the so-called incremental estimation filter. A prerequisite for proper functioning of the filter is that the variation of the signal is considerably slower than that of the disturbing interference. This condition will often not be true, especially during wave deflections. As a result, the filter will not fully remove the interference when present, or, alternatively, it may generate a sine wave in the absence of interference. These effects are analyzed and different solutions proposed, one of which is the use of new, very simple filters based on the incremental estimation technique.

Classification methods for computerized interpretation of the electrocardiogram.

Two methods for diagnostic classification of the electrocardiogram are described: a heuristic one and a statistical one. In the heuristic approach, the cardiologist provides the knowledge to construct a classifier, usually a decision tree. In the statistical approach, probability densities of diagnostic features are estimated from a learning set of ECGs and multivariate techniques are used to attain diagnostic classification. The relative merits of both approaches with respect to criteria selection, comprehensibility, flexibility, combined diseases, and performance are described. Optimization of heuristic classifiers is discussed. It is concluded that heuristic classifiers are more comprehensible than statistical ones; encounter less difficulties in dealing with combined categories; are flexible in the sense that new categories may readily be added or that existing ones may be refined stepwise. Statistical classifiers, on the other hand, are more easily adapted to another operating environment and require less involvement of cardiologists. Further research is needed to establish differences in performance between both methods. In relation to performance testing the issue is raised whether the ECG should be classified using as much prior information as possible, or whether it should be classified on itself, explicitly discarding information other than age and sex, while only afterwards other information will be used to reach a final diagnosis. Consequences of taking one of both positions are discussed.

Reconstruction of repetitive signals.

A technique is presented for the reconstruction of signals that suffered sampling-frequency decimation. Two assumptions are made: the original signal has to be repetitive, and no anti-aliasing filter has been used before frequency decimation. The performance of the technique is assessed by using test signals of which the original signal is known.

Signal analysis for ECG interpretation.

In ECG interpretation usually two main areas are discerned: the signal analysis and the diagnostic classification. This article reviews the major developments in the first area. ECG signal analysis itself is subdivided into the stages data acquisition, data transformation, feature selection, and data reduction. These stages are consecutively reviewed, while in the data transformation stage digital filtering, detection, wave typing, beat selection, and boundary recognition are discussed.

Methodology of the modular ECG analysis system MEANS.

The methodology, used in the Modular ECG Analysis System (MEANS) is described. MEANS consists of modules for signal analysis and diagnostic classification. The basic structure of the modular interpretation system remained intact over a period of 20 years, while all modules underwent many changes as a function of experience and insight, and the continuously changing information technology. The article describes the advantages of a modular approach to decision-support systems, the most important ones being easier maintenance of the software package and separate optimization and testing of each module. The overall evaluation of MEANS was done in the CSE study. Evaluation results for modules and for the entire system are presented.

The Delphi method to validate diagnostic knowledge in computerized ECG interpretation.

We investigated the applicability of the Delphi method for increasing the agreement among multiple cardiologists on, firstly, their classifications of a set of electrocardiograms and, secondly, their reasons for these classifications. Five cardiologists were requested to judge the computer classifications of a set of thirty ECGs. If a cardiologist disagreed with the computer classification, he had to provide a new classification and a reason for this change. The results of this first round were compiled and anonymously fed back to the cardiologists. In a second round the cardiologists were asked once again to judge the ECGs and to rate the reasons provided in the first round. The level of agreement was estimated by means of the kappa statistic. The Delphi procedure substantially increased the agreement on the classifications among the cardiologists. The final agreement was very high and comparable with the intraobserver agreement. There was also a high level of agreement on the reasons provided by the cardiologists. However, their use in improving the program's performance is hampered by the qualitative nature of many of the reasons. Suggestions are given for a more formalized elicitation of knowledge.