Sex Differences and Utility of Treadmill Testing in Long-QT Syndrome.

Background Diagnosis of congenital long-QT syndrome (LQTS) is complicated by phenotypic ambiguity, with a frequent normal-to-borderline resting QT interval. A 3-step algorithm based on exercise response of the corrected QT interval (QTc) was previously developed to diagnose patients with LQTS and predict subtype. This study evaluated the 3-step algorithm in a population that is more representative of the general population with LQTS with milder phenotypes and establishes sex-specific cutoffs beyond the resting QTc. Methods and Results We identified 208 LQTS likely pathogenic or pathogenic KCNQ1 or KCNH2 variant carriers in the Canadian NLQTS (National Long-QT Syndrome) Registry and 215 unaffected controls from the HiRO (Hearts in Rhythm Organization) Registry. Exercise treadmill tests were analyzed across the 5 stages of the Bruce protocol. The predictive value of exercise ECG characteristics was analyzed using receiver operating characteristic curve analysis to identify optimal cutoff values. A total of 78% of male carriers and 74% of female carriers had a resting QTc value in the normal-to-borderline range. The 4-minute recovery QTc demonstrated the best predictive value for carrier status in both sexes, with better LQTS ascertainment in female patients (area under the curve, 0.90 versus 0.82), with greater sensitivity and specificity. The optimal cutoff value for the 4-minute recovery period was 440 milliseconds for male patients and 450 milliseconds for female patients. The 1-minute recovery QTc had the best predictive value in female patients for differentiating LQTS1 versus LQTS2 (area under the curve, 0.82), and the peak exercise QTc had a marginally better predictive value in male patients for subtype with (area under the curve, 0.71). The optimal cutoff value for the 1-minute recovery period was 435 milliseconds for male patients and 455 milliseconds for femal patients. Conclusions The 3-step QT exercise algorithm is a valid tool for the diagnosis of LQTS in a general population with more frequent ambiguity in phenotype. The algorithm is a simple and reliable method for the identification and prediction of the 2 major genotypes of LQTS.

Ablation of typical atrial flutter using mini electrode measurements for maximum voltage-guided ablation: A randomized, controlled trial.

BACKGROUND: Novel ablation catheters with mini electrode (ME) sensing have become available but their utility is unclear. We investigated whether ablation of the cavotricuspid isthmus (CTI) for atrial flutter (AFL) would be improved using ME signals. METHODS: Sixty-one patients (76% male, 63 ± 10 years) with CTI-dependent AFL underwent ablation using a maximum voltage-guided approach, randomized to either standard 8 mm non-irrigated catheter with bipolar signals or IntellaTip MiFi catheter using ME signals alone. RESULTS: Acute bidirectional block was achieved in 97%. Mean follow-up was 16.7 ± 10 months. The median number of ablation lesions was 13 in both groups (range 3-62 vs. 1-43, p = .85). No significant differences were observed in AFL recurrences (17% vs. 11%, p = .7), median procedure durations (97 min [interquartile range (IQR), 71-121] vs. 87 min [IQR, 72-107], p = .55) or fluoroscopy times (31 min [IQR, 21-52] vs. 38 min [IQR, 25-70], p = .56). Amplitudes of ME signals were on average 160% greater than blinded bipolar signals. In 23.7% of lesions where bipolar signals were difficult to interpret, 13.6% showed a clear ME signal. CONCLUSIONS: There was no difference in the effectiveness of CTI ablation guided by ME signals, compared with using bipolar signals from a standard 8 mm ablation catheter. While ME signal amplitudes were larger and sometimes present when the bipolar signal was unclear, this did not improve procedural characteristics or outcomes. The results suggest future research should focus on lesion integrity rather than signal sensing.

Sex-Related Differences in Cardiac Channelopathies: Implications for Clinical Practice.

Sex-related differences in prevalence, clinical presentation, and outcome of cardiac channelopathies are increasingly recognized, despite their autosomal transmission and hence equal genetic predisposition among sexes. In congenital long-QT syndrome, adult women carry a greater risk for Torsades de pointes and sudden cardiac death than do men. In contrast, Brugada syndrome is observed predominantly in adult men, with a considerably higher risk of arrhythmic sudden cardiac death in adult men than in women. In both conditions, the risk for arrhythmias varies with age. Sex-associated differences appear less evident in other cardiac channelopathies, likely a reflection of their rare(r) occurrence and our limited knowledge. In several cardiac channelopathies, sex-specific predictors of outcome have been identified. Together with genetic and environmental factors, sex hormones contribute to the sex-related disparities in cardiac channelopathies through modulation of the expression and function of cardiac ion channels. Despite these insights, essential knowledge gaps exist in the mechanistic understanding of these differences, warranting further investigation. Precise application of the available knowledge may improve the individualized care of patients with cardiac channelopathies. Promoting the reporting of sex-related phenotype and outcome parameters in clinical and experimental studies and advancing research on cardiac channelopathy animal models should translate into improved patient outcomes. This review provides a critical digest of the current evidence for sex-related differences in cardiac channelopathies and emphasizes their clinical implications and remaining gaps requiring further research.

Casein kinase 1 dynamics underlie substrate selectivity and the PER2 circadian phosphoswitch.

Post-translational control of PERIOD stability by Casein Kinase 1δ and ε (CK1) plays a key regulatory role in metazoan circadian rhythms. Despite the deep evolutionary conservation of CK1 in eukaryotes, little is known about its regulation and the factors that influence substrate selectivity on functionally antagonistic sites in PERIOD that directly control circadian period. Here we describe a molecular switch involving a highly conserved anion binding site in CK1. This switch controls conformation of the kinase activation loop and determines which sites on mammalian PER2 are preferentially phosphorylated, thereby directly regulating PER2 stability. Integrated experimental and computational studies shed light on the allosteric linkage between two anion binding sites that dynamically regulate kinase activity. We show that period-altering kinase mutations from humans to Drosophila differentially modulate this activation loop switch to elicit predictable changes in PER2 stability, providing a foundation to understand and further manipulate CK1 regulation of circadian rhythms.

Avian Influenza Risk Surveillance in North America with Online Media.

The use of Internet-based sources of information for health surveillance applications has increased in recent years, as a greater share of social and media activity happens through online channels. The potential surveillance value in online sources of information about emergent health events include early warning, situational awareness, risk perception and evaluation of health messaging among others. The challenge in harnessing these sources of data is the vast number of potential sources to monitor and developing the tools to translate dynamic unstructured content into actionable information. In this paper we investigated the use of one social media outlet, Twitter, for surveillance of avian influenza risk in North America. We collected AI-related messages over a five-month period and compared these to official surveillance records of AI outbreaks. A fully automated data extraction and analysis pipeline was developed to acquire, structure, and analyze social media messages in an online context. Two methods of outbreak detection; a static threshold and a cumulative-sum dynamic threshold; based on a time series model of normal activity were evaluated for their ability to discern important time periods of AI-related messaging and media activity. Our findings show that peaks in activity were related to real-world events, with outbreaks in Nigeria, France and the USA receiving the most attention while those in China were less evident in the social media data. Topic models found themes related to specific AI events for the dynamic threshold method, while many for the static method were ambiguous. Further analyses of these data might focus on quantifying the bias in coverage and relation between outbreak characteristics and detectability in social media data. Finally, while the analyses here focused on broad themes and trends, there is likely additional value in developing methods for identifying low-frequency messages, operationalizing this methodology into a comprehensive system for visualizing patterns extracted from the Internet, and integrating these data with other sources of information such as wildlife, environment, and agricultural data.