Digitized Electrocardiography Measurements Support the Biological Plausibility of the Pathological Significance of ST Segments in Athletes.

OBJECTIVE: ST segment deviations around the isoelectric line are common findings in manifest cardiovascular disease. In athletes, ST elevation is common, while ST depression is considered rare. However, clinical studies in athletes have associated ST depression with myocardial fibrosis and fatty infiltration and ST elevation with pericarditis and myocarditis. This study aims to explore the association between resting ST segment deviations and resting heart rate, an indicator of training and autonomic tone and electrocardiography (ECG) markers of exercise training effect and cardiovascular health R and T wave amplitude. DESIGN: Retrospective analysis of digitized ECG data. SETTING: Institutional setting. PARTICIPANTS: Seven thousand eight hundred thirty-six (male athletes = 4592, female athletes = 3244) healthy asymptomatic athletes (14-35 years). MAIN OUTCOME MEASURES: A series of correlations and regressions were conducted between ST depression (<0.0 µV) and ST elevation (>0.0 µV), on R and T wave amplitudes, and heart rate in leads V2, V5, and aVF. RESULTS: Positive correlations between ST elevation and R and T wave (S wave in V2) amplitudes and leads V5, V2, and aVF in male and female athletes (range of r = 0.1-0.54). In addition, there was a negative correlation between ST elevation and HR for male and female athletes. Finally, there was a negative correlation between ST depression and R wave and HR for male and female athletes in V5 ( P < 0.01). CONCLUSIONS: In athletes, ST segment elevation is correlated with R and T wave amplitudes and negatively correlated with HR. In addition, ST segment elevation is correlated with low heart rate, consistent with its higher prevalence in athletes. ST segment depression is not influenced by HR but is negatively associated with R and T wave amplitudes.

Should ECG criteria for Low QRS voltage (LQRSV) be specific for Sex?

INTRODUCTION: Low QRS peak-to-nadir voltage (LQRSV) is associated with arrhythmogenic right ventricular cardiomyopathy (ARVC) and other cardiomyopathies. Recent studies have proposed criteria for LQRSV when screening athletes for cardiovascular disease. These criteria have not yet been evaluated in a large population of healthy young athletes. METHODS: The target population was 10,728 (42.5% female, 57.5% male, mean age 18.1 ± 4.3 years) athletes who participated in mass ECG screenings between 2014 and 2021 at multiple sites across the United States including grade schools (11%), high schools (32%), colleges (50%), and professional athletic teams (6%) with digitally recorded ECGs and a standardized protocol. Since by design, complete follow up for outcomes and the results of testing were not available. Including only ECGs from initial evaluation among athletes 14-35 years of age and excluding those with right bundle branch block, left bundle branch block, Wolf-Parkinson-White pattern, reversed leads and 3 clinically diagnosed cardiomyopathies at Stanford, 8,679 (58% males, 42% females) remained eligible for analysis. QRS voltage was analyzed for each ECG lead and LQRSV criteria were applied and stratified by sex. RESULTS: QRS voltage was lower in all leads in female athletes compared to male athletes. Using traditional limb lead criteria or precordial lead criteria, the prevalence of LQRSV was significantly lower in males than females (P < .001). Strikingly, LQRSV using the Sokolow-Lyon Index was present in 1.9% of males and 9.8% of females (P < .001). Applying first percentile for LQRS amplitude criteria provided possible values for screening young athletes for LQRSV. CONCLUSIONS: LQRSV is more common among female athletes than male athletes using established criteria. Using first percentile sex-specific cut points should be considered in future analyses. Proposed novel LQRSV criteria in young athletes should be specific for males and females.

Feasibility of institution-agnostic, EHR-integrated regional clinical trial matching.

BACKGROUND: A lack of onsite clinical trials is the largest barrier to participation of cancer patients in trials. Development of an automated process for regional trial eligibility screening first requires identification of patient electronic health record data that allows effective trial screening, and evidence that searching for trials regionally has a positive impact compared with site-specific searching. METHODS: To assess a screening framework that would support an automated regional search tool, a set of patient clinical variables was analyzed for prescreening clinical trials. The variables were used to assess regional compared with site-specific screening throughout the United States. RESULTS: Eight core variables from patient electronic health records were identified that yielded likely matches in a prescreen process. Assessment of the screening framework was performed using these variables to search for trials locally and regionally for an 84-patient cohort. The likelihood that a trial returned in this prescreen was a provisional trial match was 45.7%. Expanding the search radius to 20 miles led to a net 91% increase in matches across cancers within the tested cohort. In a U.S. regional analysis, for sparsely populated areas, searching a 100-mile radius using the prescreening framework was needed, whereas for urban areas a 20-mile radius was sufficient. CONCLUSION: A clinical trial screening framework was assessed that uses limited patient data to efficiently and effectively identify prescreen matches for clinical trials. This framework improves trial matching rates when searching regionally compared with locally, although the applicability of this framework may vary geographically depending on oncology practice density. PLAIN LANGUAGE SUMMARY: Clinical trials provide cancer patients the opportunity to participate in research and development of new drugs and treatment approaches. It can be difficult to find available clinical trials for which a patient is eligible. This article describes an approach to clinical trial matching using limited patient data to search for trials regionally, beyond just the patient's local care site. Feasibility testing shows that this process can lead to a net 91% increase in the number of potential clinical trial matches available within 20 miles of a patient. Based on these findings, a software tool based on this model is being developed that will automatically send limited, deidentified information from patient medical records to services that can identify possible clinical trials within a given region.

Guide to the Female Student Athlete ECG: A Comprehensive Study of 3466 Young, Racially Diverse Athletes.

OBJECTIVES: The 12-lead electrocardiogram (ECG) is used in the preparticipation screening examination for athletes. Despite known differences in ECG findings by sex, only QTc prolongation is given a sex-specific threshold. We hypothesize that our large dataset-with diversity in age, race, and sport participation-can be utilized to improve ECG screening in female student athletes. METHODS: Computerized 12-lead ECGs were recorded and analyzed in female athletes who underwent preparticipation screening examination between June 2010 and September 2021. The quantitative, empirical 2017 international criteria for electrocardiographic interpretation were compared with either the 99th percentile in our cohort or the percentile that corresponded to the known disease prevalence. RESULTS: Of 3466 female athletes with ECGs as part of preparticipation screening examination, the 2017 international criteria classified 2.1% of athletes with at least one ECG abnormality requiring cardiological evaluation. Rates were similar across age, race/ethnicity, and sporting discipline. Using ranges based on our population, 2.7% of athletes would require additional workup. Surprisingly, ST depression up to 0.03 mV was a normal finding in this cohort. If RS voltage extremes were considered findings requiring follow-up, an additional 9.6% of the athlete population would be flagged using current definitions. This number decreases to 2.7% if using the 99th percentile in this cohort. CONCLUSION: These results highlight a difference in the reported prevalence of ECG abnormalities when comparing empirically derived thresholds to statistically derived ranges. Consideration of new metrics specific to the female athlete population has the potential to further refine athlete ECG screening.

Prevalence and clinical significance of isolated low QRS voltages in young athletes.

AIMS: Low QRS voltages (peak to peak <0.5 mV) in limb leads (LQRSV) on the athlete's electrocardiogram (ECG) may reflect an underlying cardiomyopathy, mostly arrhythmogenic cardiomyopathy (ACM) or non-ischaemic left ventricular scar (NILVS). We studied the prevalence and clinical meaning of isolated LQRSV in a large cohort of competitive athletes. METHODS AND RESULTS: The index group included 2229 Italian competitive athletes [median age 18 years (16-25), 67% males, 97% Caucasian] without major ECG abnormalities at pre-participation screening. Three control groups included Black athletes (N = 1115), general population (N = 1115), and patients with ACM or NILVS (N = 58). Echocardiogram was performed in all athletes with isolated LQRSV and cardiac magnetic resonance (CMR) in those with ventricular arrhythmias or echocardiographic abnormalities. The isolated LQRSV pattern was found in 1.1% index athletes and was associated with increasing age (median age 28 vs. 18 years; P < 0.001), elite status (71% vs. 34%; P < 0.001), body surface area, and body mass index but not with sex, type of sport, and echocardiographic left ventricular mass. The prevalence of isolated LQRSV was 0.2% in Black athletes and 0.3% in young individuals from the general population. Cardiomyopathy patients had a significantly greater prevalence of isolated LQRSV (12%) than index athletes, Black athletes, and general population. Five index athletes with isolated LQSRV and exercise-induced ventricular arrhythmias underwent CMR showing biventricular ACM in 1 and idiopathic NILVS in 1. CONCLUSIONS: Unlike cardiomyopathy patients, the ECG pattern of isolated LQRSV was rarely observed in athletes. This ECG sign should prompt clinical work-up for exclusion of an underlying cardiomyopathy.

Comparison of the Stanford ECG Left Atrial Criteria With the International ECG Criteria for Sports Screening.

OBJECTIVE: Because the International left atrial enlargement electrocardiographic (ECG) screening criteria (ECG-LAE) for athletes are rarely fulfilled in young athletes, we compared it with evidence-based criteria from a recent clinical outcome study of ECG left atrial abnormality (ECG-LAA). DESIGN: Retrospective analyses. SETTING: Routine preparticipation ECG screening in California. PARTICIPANTS: Four thousand four hundred thirty-eight young individuals (18.5 ± 5.4 years, 40% women). ASSESSMENT OF RISK FACTORS: The International criteria for ECG-LAE were applied: prolonged P wave duration of ≥120 ms in leads I or II AND negative portion of ≥1 mm in depth in lead V1. This was compared with Stanford criteria for ECG-LAA: prolonged P wave duration of ≥140 ms odds ratio (OR) negative portion in V1 and V2 greater than 1 mm. MAIN OUTCOME MEASURES: Differences in the classification of abnormal ECGs between the 2 criteria applied to the same population of young athletes. RESULTS: Only 33 (0.7%) of our subjects fulfilled the International criteria for ECG-LAE while 110 (2.5%) fulfilled the ECG-LAA criteria. Adding our new ECG-LAA criterion and considering it a major criterion raised the abnormal ECG prevalence and athletes referred for further evaluation from 2.9% to 4.4%. CONCLUSIONS: The Stanford evidence-based criterion for ECG-LAA incorporating V2 and replacing "or" for "and" regarding P wave duration increased the yield of abnormal classification for P waves. Future follow-up studies are needed to confirm that this new criterion should be included in future ECG screening consensus documents.

Economic evaluation from beef cattle production industry with intensification in Brazil's tropical pastures.

This study aimed to evaluate different scenarios (year, supplementation level) about economic results of beef cattle production during rearing and finishing phase in Brazilian's tropical pastures. Four scenarios were evaluated in combination with fourteen supplements, and it was originated from some research developed inside Forage Crops and Grasslands section from São Paulo State University among years 2011 and 2014. The economic evaluation was analyzed by operating cost, total operational costs, gross revenue, operating profit, and financial net income. Besides profitability, internal rate of return (IRR), benefit/cost ratio (B:C), and simple payback period (SPP) were calculated too. During rearing phase, the best result was observed for scenario 2 (2012), supplement 3.2 (mineral mix) with values of 11 cycles, 26.3%, 9.30%, and 0.39 for SPP, profitability, IRR, and B:C ratio, respectively. Already to finishing phase, the best scenario was 3 (2013), supplement 10 (multiple supplement with supplementation level equal 1.0% body weight), which obtained 4 cycles, 68.7%, 27.00%, and 2.34 for the same variables above mentioned. Results were consistent being that higher IRR and profitability occurred when using low supplementation level. Hence, the economic responses from different scenarios (years and supplements) can alter the final livestock farm financial statement.

Impact of the distance from the chest wall to the heart on surface ECG voltage in athletes.

OBJECTIVE: Available ECG criteria for detection of left ventricular (LV) hypertrophy have been reported to have limited diagnostic capability. Our goal was to describe how the distance between the chest wall and the left ventricle determined by echocardiography affected the relationship between ECG voltage and LV mass (LVM) in athletes. METHODS: We retrospectively evaluated digitised ECG data from college athletes undergoing routine echocardiography as part of their preparticipation evaluation. Along with LV mass and volume, we determined the chest wall-LV distance in the parasternal short-axis and long-axis views from two-dimensional transthoracic echocardiographic images and explored the relation with ECG QRS voltages in all leads, as well as summed voltages as included in six major ECG-LVH criteria. RESULTS: 239 athletes (43 women) were included (age 19±1 years). In men, greater LV-chest wall distance was associated with higher R-wave amplitudes in leads aVL and I (R=0.20 and R=0.25, both p<0.01), while in women greater distance was associated with higher R-amplitudes in V5 and V6 (R=0.42 and R=0.34, both p<0.01). In women, the chest wall-LV distance was the only variable independently (and positively) associated with R V5 voltage, while LVM, height and weight contributed to the relationship in men. CONCLUSIONS: The chest wall-LV distance was weakly associated with ECG voltage in athletes. Inconsistent associations in men and women imply different intrathoracic factors affecting impedance and conductance between sexes. This may help explain the poor relationship between QRS voltage and LVM in athletes.

Limitations of Electrocardiography for Detecting Left Ventricular Hypertrophy or Concentric Remodeling in Athletes.

BACKGROUND: Electrocardiography (ECG) is used to screen for left ventricular hypertrophy (LVH), but common ECG-LVH criteria have been found less effective in athletes. The purpose of this study was to comprehensively evaluate the value of ECG for identifying athletes with LVH or a concentric cardiac phenotype. METHODS: A retrospective analysis of 196 male Division I college athletes routinely screened with ECG and echocardiography within the Stanford Athletic Cardiovascular Screening Program was performed. Left-ventricular mass and volume were determined using echocardiography. LVH was defined as left ventricular mass (LVM) >102 g/m²; a concentric cardiac phenotype as LVM-to-volume (M/V) ≥1.05 g/mL. Twelve-lead electrocardiograms including high-resolution time intervals and QRS voltages were obtained. Thirty-seven previously published ECG-LVH criteria were applied, of which the majority have never been evaluated in athletes. C-statistics, including area under the receiver operating curve (AUC) and likelihood ratios were calculated. RESULTS: ECG lead voltages were poorly associated with LVM (r = 0.18-0.30) and M/V (r = 0.15-0.25). The proportion of athletes with ECG-LVH was 0%-74% across criteria, with sensitivity and specificity ranging between 0% and 91% and 27% and 99.5%, respectively. The average AUC of the criteria in identifying the 11 athletes with LVH was 0.57 (95% confidence interval [CI] 0.56-0.59), and the average AUC for identifying the 8 athletes with a concentric phenotype was 0.59 (95% CI 0.56-0.62). CONCLUSION: The diagnostic capacity of all ECG-LVH criteria were inadequate and, therefore, not clinically useful in screening for LVH or a concentric phenotype in athletes. This is probably due to the weak association between LVM and ECG voltage.

QT Corrections for Long QT Risk Assessment: Implications for the Preparticipation Examination.

BACKGROUND: Because sudden cardiac death (SCD) in the young mainly occurs in individuals with structurally normal hearts, improved screening techniques for detecting inherited arrhythmic diseases are needed. The QT interval is an important screening measurement; however, the criteria for detecting an abnormal QT interval are based on Bazett formula and older populations. OBJECTIVE: To define the normal upper limits for QT interval from the electrocardiograms (ECGs) of healthy young individuals, compare the major correction formula and propose new QT interval thresholds for detecting those at risk of SCD. METHODS: Young active individuals underwent ECGs as part of routine preparticipation physical examinations for competitive sports or community screening. This was a nonfunded study using de-identified data with no follow-up. RESULTS: There were 31 558 subjects: 2174 grade school (7%), 18 547 high school (59%), and 10 822 college (34%). Mean age was 17 (12-35 years), 45% were female, 67% white, and 11% of African descent. Bazett performed least favorably for removing the effect of heart rate (HR), whereas Fridericia performed the best. Fridericia correction also closely fit the raw data best (R of 0.65), and at percentile values applicable to screening. The recommended risk cut points using Bazetts correction identified less than half of the athletes in the 99th or 99.5th percentiles of the uncorrected QT by HR range. Use of Fridericia correction increased capture rates by over 50%. CONCLUSION: Our results support the application of the Fridericia-corrected threshold of 460 for men and 470 milliseconds for women (and 485 milliseconds for marked prolongation) rather than Bazett correction for the preparticipation examination.

Comparison of QT Interval Measurement Methods and Correction Formulas in Atrial Fibrillation.

Antiarrhythmic drugs used in atrial fibrillation (AF) cause QT prolongation and are associated with torsades de pointes, a deadly ventricular arrhythmia. No consensus exists on the optimal method of QT measurement or correction in AF. Therefore, we compared common methods to measure and correct QT in AF to identify the most accurate approach. We identified patients who had electrocardiograms done at Stanford Hospital (Stanford, California) between January 2014 and October 2016 with conversion from AF to sinus rhythm (SR) within a 24-hour period. QT intervals were determined using different measurement methods and corrected using the Bazett's, Framingham, Fridericia, or Hodges formulas for heart rate (HR). Comparisons were made between QT in a patient's last instance of AF to SR. Computerized measurements were taken from 715 patients. Manual measurements were taken from a 50-patient subset. Bazett's formula produced the longest corrected QT in AF compared with other formulas (p <0.005). Measuring QT as an average over multiple beats resulted in a smaller difference between AF and SR than choosing a single beat. Determining QT from a 5-beat average resulted in a QTc that was 19.0 ms higher (interquartile range 0.30 to 43.7) in AF than SR. After correcting for residual effect of HR on QTc, there was not a significant difference between QTc in AF to SR. In conclusion, measuring QT over multiple beats produces a more accurate measurement of QT in AF. Differences between QTc in AF and SR exist because of imperfect HR correction formula and not due to an independent effect of AF.

Heart Rate Variability: An Old Metric with New Meaning in the Era of Using mHealth technologies for Health and Exercise Training Guidance. Part Two: Prognosis and Training.

It has been demonstrated that heart rate variability (HRV) is predictive of all-cause and cardiovascular mortality using clinical ECG recordings. This is true for rest, exercise and ambulatory HRV clinical ECG device recordings in prospective cohorts. Recently, there has been a rapid increase in the use of mobile health technologies (mHealth) and commercial wearable fitness devices. Most of these devices use ECG or photo-based plethysmography and both are validated for providing accurate heart rate measurements. This offers the opportunity to make risk information from HRV more widely available. The physiology of HRV and the available technology by which it can be assessed has been summarised in Part 1 of this review. In Part 2 the association between HRV and risk stratification is addressed by reviewing the current evidence from data acquired by resting ECG, exercise ECG and medical ambulatory devices. This is followed by a discussion of the use of HRV to guide the training of athletes and as a part of fitness programmes.

Heart Rate Variability: An Old Metric with New Meaning in the Era of using mHealth Technologies for Health and Exercise Training Guidance. Part One: Physiology and Methods.

The autonomic nervous system plays a major role in optimising function of the cardiovascular (CV) system, which in turn has important implications for CV health. Heart rate variability (HRV) is a measurable reflection of this balance between sympathetic and parasympathetic tone and has been used as a marker for cardiac status and predicting CV outcomes. Recently, the availability of commercially available heart rate (HR) monitoring systems has had important CV health implications and permits ambulatory CV monitoring on a scale not achievable with traditional cardiac diagnostics. The focus of the first part of this two-part review is to summarise the physiology of HRV and to describe available technologies for HRV monitoring. Part two will present HRV measures for assessing CV prognosis and athletic training.

Milk feeding and first complementary foods during the first year of life in the TEDDY study.

The aim was to describe milk feeding patterns and first weaning foods during the first year of life in a large prospective birth cohort of infants with increased genetic risk for Type 1 diabetes (T1D) recruited in 4 different countries: the United States, Finland, Germany, and Sweden. All enrolled children with dietary information (n = 8,673) were included in the analyses; 1,307 (15%) children who dropped out before the first birthday were excluded from some analyses. Supplementary milk feeding in the first 3 days of life was common in all the four countries, although the type of the supplementary milk differed by country and by maternal T1D. Donated human milk was commonly used only in Finland. In all the countries, the most common first supplementary food was cow's milk-based infant formula, especially among offspring of mothers with T1D. The use of specific types of infant formulas differed notably by country: Extensively hydrolysed formulas were most used in Finland, partially hydrolysed ones in the United States and in Germany, and soy formulas only in the United States. Infant formulas commonly included probiotics, prebiotics, and starches. During the first year of life, most of the infants received conventional cow's milk. Overall, milk feeding during the first 3 days of life and thereafter until the first birthday differed markedly by maternal T1D status and across countries. These descriptive data may be useful in understanding early infant feeding practices and in planning potential interventions, which affect infant feeding.

Clinical Implications of Technological Advances in Screening for Atrial Fibrillation.

The incidence of atrial fibrillation (AF) continues to increase worldwide as people live longer. AF is the leading cause of stroke among patients older than 75 years and is responsible for at least 15% of all strokes. Industry has responded to this problem with a plethora of monitoring devices. These include single lead ECG adhesive sensors, implantable loop recorders, smartphone attachments and wearables. This review will concentrate on clinical studies using these technologies. There are wearables including watches and watch-like devices that will be mentioned but these have not been validated for clinical use. This review will begin with a background regarding screening for AF and at the end present findings from Cardiac Implantable devices that could influence use of the new mobile health technologies.

Identification of non-HLA genes associated with development of islet autoimmunity and type 1 diabetes in the prospective TEDDY cohort.

Traditional linkage analysis and genome-wide association studies have identified HLA and a number of non-HLA genes as genetic factors for islet autoimmunity (IA) and type 1 diabetes (T1D). However, the relative risk associated with previously identified non-HLA genes is usually very small as measured in cases/controls from mixed populations. Genetic associations for IA and T1D may be more accurately assessed in prospective cohorts. In this study, 5806 subjects from the TEDDY (The Environmental Determinants of Diabetes in the Young) study, an international prospective cohort study, were genotyped for 176,586 SNPs on the ImmunoChip. Cox proportional hazards analyses were performed to discover the SNPs associated with the risk for IA, T1D, or both. Three regions were associated with the risk of developing any persistent confirmed islet autoantibody: one known region near SH2B3 (HR = 1.35, p = 3.58 × 10-7) with Bonferroni-corrected significance and another known region near PTPN22 (HR = 1.46, p = 2.17 × 10-6) and one novel region near PPIL2 (HR = 2.47, p = 9.64 × 10-7) with suggestive evidence (p < 10-5). Two known regions (PTPN22: p = 2.25 × 10-6, INS; p = 1.32 × 10-7) and one novel region (PXK/PDHB: p = 8.99 × 10-6) were associated with the risk for multiple islet autoantibodies. First appearing islet autoantibodies differ with respect to association. Two regions (INS: p = 5.67 × 10-6 and TTC34/PRDM16: 6.45 × 10-6) were associated if the fist appearing autoantibody was IAA and one region (RBFOX1: p = 8.02 × 10-6) was associated if the first appearing autoantibody was GADA. The analysis of T1D identified one region already known to be associated with T1D (INS: p = 3.13 × 10-7) and three novel regions (RNASET2, PLEKHA1, and PPIL2; 5.42 × 10-6 > p > 2.31 × 10-6). These results suggest that a number of low frequency variants influence the risk of developing IA and/or T1D and these variants can be identified by large prospective cohort studies using a survival analysis approach.

Correction: Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

[This corrects the article DOI: 10.1371/journal.pgen.1006528.].

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits.

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.

Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

Normal computerized Q wave measurements in healthy young athletes.

BACKGROUND: Recent Expert consensus statements have sought to decrease false positive rates of electrocardiographic abnormalities requiring further evaluation when screening young athletes. These statements are largely based on traditional ECG patterns and have not considered computerized measurements. OBJECTIVE: To define the normal limits for Q wave measurements from the digitally recorded ECGs of healthy young athletes. METHODS: All athletes were categorized by sex and level of participation (high school, college, and professional), and underwent screening ECGs with routine pre-participation physicals, which were electronically captured and analyzed. Q wave amplitude, area and duration were recorded for athletes with Q wave amplitudes greater than 0.5mm at standard paper amplitude display (1mV/10mm). ANOVA analyses were performed to determine differences these parameters among all groups. A positive ECG was defined by our Stanford Computerized Criteria as exceeding the 99th percentile for Q wave area in 2 or more leads. Proportions testing was used to compare the Seattle Conference Q wave criteria with our data-driven criteria. RESULTS: 2073 athletes in total were screened. Significant differences in Q wave amplitude, duration and area were identified both by sex and level of participation. When applying our Stanford Computerized Criteria and the Seattle criteria to our cohort, two largely different groups of athletes are identified as having abnormal Q waves. CONCLUSION: Computer analysis of athletes' ECGs should be included in future studies that have greater numbers, more diversity and adequate end points.