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The objectives of this study were to explore the role that eicosapentaenoic acid (EPA) and/or docosahexaenoic acid (DHA) plays in heart failure (HF), highlighting the potential connection to oxidative stress pathways. Following PRISMA guidelines, we conducted electronic searches of the literature in MEDLINE and EMBASE focusing on serum EPA and/or DHA and EPA and/or DHA supplementation in adult patients with heart failure or who had heart failure as an outcome of this study. We screened 254 studies, encompassing RCTs, observational studies, and cohort studies that examined HF outcomes in relation to either serum concentrations or dietary supplementation of EPA and/or DHA. The exclusion criteria were pediatric patients, non-HF studies, abstracts, editorials, case reports, and reviews. Eleven studies met our criteria. In meta-analyses, high serum concentrations of DHA were associated with a lower rate of heart failure with a hazard ratio of 0.74 (CI = 0.59-0.94). High serum concentrations of EPA also were associated with an overall reduction in major adverse cardiovascular events with a hazard ratio of 0.60 (CI = 0.46-0.77). EPA and DHA, or n3-PUFA administration, were associated with an increased LVEF with a mean difference of 1.55 (CI = 0.07-3.03)%. A potential explanation for these findings is the ability of EPA and DHA to inhibit pathways by which oxidative stress damages the heart or impairs cardiac systolic or diastolic function producing heart failure. Specifically, EPA may lower oxidative stress within the heart by reducing the concentration of reactive oxygen species (ROS) within cardiac tissue by (i) upregulating nuclear factor erythroid 2-related factor 2 (Nrf2), which increases the expression of antioxidant enzyme activity, including heme oxygenase-1, thioredoxin reductase 1, ferritin light chain, ferritin heavy chain, and manganese superoxide dismutase (SOD), (ii) increasing the expression of copper-zinc superoxide dismutase (MnSOD) and glutathione peroxidase, (iii) targeting Free Fatty Acid Receptor 4 (Ffar4), (iv) upregulating expression of heme-oxygenase-1, (v) lowering arachidonic acid levels, and (vi) inhibiting the RhoA/ROCK signaling pathway. DHA may lower oxidative stress within the heart by (i) reducing levels of mitochondrial-fission-related protein DRP-1(ser-63), (ii) promoting the incorporation of cardiolipin within the mitochondrial membrane, (iii) reducing myocardial fibrosis, which leads to diastolic heart failure, (iv) reducing the expression of genes such as Appa, Myh7, and Agtr1α, and (v) reducing inflammatory cytokines such as IL-6, TNF-α. In conclusion, EPA and/or DHA have the potential to improve heart failure, perhaps mediated by their ability to modulate oxidative stress.

Background: Left ventricular hypertrophy (LVH) is a powerful predictor of future cardiovascular events. Objectives: The objectives of this study were to conduct a systematic review of machine learning (ML) algorithms for the identification of LVH and compare them with respect to the classical features of test sensitivity, specificity, accuracy, ROC and the traditional ECG criteria for LVH. Methods: A search string was constructed with the operators "left ventricular hypertrophy, electrocardiogram" AND machine learning; then, Medline and PubMed were systematically searched. Results : There were 14 studies that examined the detection of LVH utilizing the ECG and utilized at least one ML approach. ML approaches encompassed support vector machines, logistic regression, Random Forest, GLMNet, Gradient Boosting Machine, XGBoost, AdaBoost, ensemble neural networks, convolutional neural networks, deep neural networks and a back-propagation neural network. Sensitivity ranged from 0.29 to 0.966 and specificity ranged from 0.53 to 0.99. A comparison with the classical ECG criteria for LVH was performed in nine studies. ML algorithms were universally more sensitive than the Cornell voltage, Cornell product, Sokolow-Lyons or Romhilt-Estes criteria. However, none of the ML algorithms had meaningfully better specificity, and four were worse. Many of the ML algorithms included a large number of clinical (age, sex, height, weight), laboratory and detailed ECG waveform data (P, QRS and T wave), making them difficult to utilize in a clinical screening situation. Conclusions : There are over a dozen different ML algorithms for the detection of LVH on a 12-lead ECG that use various ECG signal analyses and/or the inclusion of clinical and laboratory variables. Most improved in terms of sensitivity, but most also failed to outperform specificity compared to the classic ECG criteria. ML algorithms should be compared or tested on the same (standard) database.

While the link between aging and mortality from dementia is widely appreciated, the mechanism is not clear. The objective of this study was to determine whether there is a direct relationship between Alzheimer dementia (AD) and the QT interval, because the latter has been related to cardiac mortality. A systematic review and meta-analysis were conducted after a Medline and EMBASE search using terms "Alzheimer disease or Dementia AND QT interval, QT dispersion or cardiac repolarization." Four studies with control groups were identified. There were significant differences in QT interval between individuals with AD vs individuals without dementia (controls) (odds ratio (OR)1.665 [random effects model] and 1.879 [fixed effect model]) ( p  < 0.001). There were significant differences in QT interval between individuals with AD vs individuals with mild cognitive impairment (MCI) (OR 1.760 [random effects] and 1.810 [fixed effect]) ( p  < 0.001). A significant ( p  <0.001) correlation exists between the QTc and the Mini-Mental State Exam (MMSE), a test of cognitive function. Two studies examined QT variability (the difference between the longest and shortest QT interval on a 12 lead ECG); the OR for QT variability AD vs MCI was 3.858 [random effects model] and 3.712 [fixed effects model] ( p  < 0.001). When compared to the control group, the OR for QT dispersion in AD was 6.358 [random effects model] or 5.143 (  P < 0.001) [fixed effects model]. A qualitative analysis of the data raised questions about paucity of data defining the nature of the control groups, the pathophysiologic mechanism, and the uniform use of a poor QT heart rate correction factor. The longer QT in AD, greater QT variability in AD, and the direct relationship between QT interval and AD severity supports a brain-heart connection in AD that might be fundamental to aging-induced AD and mortality. Issues with defining the control group, limited number of studies, conflicting data in population studies, and the lack of a strong electrophysiological basis underscore the need for additional research in this field., Competing Interests: The author declares no conflict of interest., (© 2024 The Authors. Aging Medicine published by Beijing Hospital and John Wiley & Sons Australia, Ltd.)

Background: Understanding the pathophysiology of heart failure (HF) with preserved ejection fraction (HFpEF) continues to be challenging. Several inflammatory and metabolic biomarkers have recently been suggested to be involved in HFpEF., Objectives: The purpose of this review was to synthesize the evidence on non-traditional biomarkers from metabolomic studies that may distinguish HFpEF from heart failure with reduced ejection fraction (HFrEF) and controls without HF., Methods: A systematic search was conducted using Medline and PubMed with search terms such as "HFpEF" and "metabolomics", and a meta-analysis was conducted., Results: Myeloperoxidase (MPO) levels were significantly (p < 0.001) higher in HFpEF than controls without HF, but comparable (p = 0.838) between HFpEF and HFrEF. Carnitine levels were significantly (p < 0.0001) higher in HFrEF than HFpEF, but comparable (p = 0.443) between HFpEF and controls without HF. Derivatives of reactive oxidative metabolites (DROMs) were not significantly (p = 0.575) higher in HFpEF than controls without HF., Conclusion: These data suggest that MPO is operative in HFpEF and HFrEF and may be a biomarker for HF. Furthermore, circulating carnitine levels may distinguish HFrEF from HFpEF., Competing Interests: Declaration of Competing Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Objectives: To examine the relationship of QRS voltages and left ventricular (LV) mass across the spectrum of individuals with different LV mass., Methods: Twenty QRS voltage measurements or combinations were determined in a consecutive series of 159 adults with an ECG and echocardiogram without previous myocardial infarction, left or right bundle branch block, pre-excitation, or electronic pacemaker., Results: The four strongest and significant correlations between QRS and LV mass were S in V4, deepest S wave in any precordial lead plus S in V4, S in V3, and S in V3 plus R in AVL times QRS duration. For men, the strength of the relationships were S in V3 ( F  = 33.8), deepest S wave in any precordial lead plus S V4 ( F  = 33.7), S in V3 plus R aVL ( F  = 29.9), S in V4 ( F  = 29.79), and deepest S in precordial leads ( F  = 17.9). The R wave in AVL alone did not correlate with LV mass. Criteria using the R wave in lateral precordial leads did not correlate as strongly with LV mass. For women, only S in V4 significantly correlated with LV mass. Overall, the R wave voltage in limb leads (AVL I or II) did not correlate with precordial S wave amplitudes. Univariate and multivariate analysis showed that some but not all QRS voltages correlated with each other. In multivariate analysis, using only single variables and not combination of QRS variables, the only significant relationship between QRS voltage and left ventricular mass was for men the S in V3 ( p = 0.04) and for women S in V4 ( p = 0.016) and R in V6 ( p = 0.04)., Conclusion: The S wave in V3 and V4 correlate most strongly with LV mass while the R wave in limb leads, including AVL, do not correlate., Competing Interests: The authors declare that they have no conflicts of interest that could have appeared to influence the work reported in this paper., (Copyright © 2024 Simon W. Rabkin and Jeremy C. J. Zhou.)

Background: Measurement of the QT interval in the ECG (QT interval) is important in evaluating risk for cardiac death and for assessing the impact of drugs on the heart. The objective of this study is to determine whether the time of day affects the QT interval, QT interval variability and whether these relationships are influenced by an individual's sex., Methods: Twenty-four hour ECGs were analyzed in detail on 50 individuals, 49 years of age, without evidence of coronary artery disease, structural heart disease, or significant arrhythmias. Four different QT-heart rate adjustment formulae were calculated and compared., Results: There were significant (P=0.0014) differences between the QT-heart rate relationship during three different time-periods (night 00:00 to 08:00 h, day 08:00 to 14:00 h and evening 14:00 to 24:00 h). Women, compared to men, had a steeper relation of QT to RR interval indicating that when heart rate slows at night, the QT interval is more prolonged which is consistent with a greater susceptibility to fatal arrhythmias. The variability of the QT interval (the SD) was significantly (P<0.01) greater in men than women at night and in the evening but not during the day. There were differences in the ability of different QT heart rate adjustment formulae to blunt the effect of heart rate changes on the QT interval during the day., Conclusion: The time of the day that the QT interval is assessed should be considered. The QT heart rate relationship is different in women than in men especially at night. QT interval variability is greater at night especially in men. There are differences in the ability of QT heart rate adjustment formulae to blunt the effect of heart rate on the QT interval. Differences in the QTc at night might be the basis for the higher prevalence of sudden death in women at night., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (AJCD Copyright © 2023.)

This review will focus on epigenetic modifications utilizing the DNA methylation mechanism, which is potentially involved in the pathogenesis of heart failure with preserved ejection fraction (HFpEF). The putative pathways of HFpEF will be discussed, specifically myocardial fibrosis, myocardial inflammation, sarcoplasmic reticulum Ca 2+ -ATPase, oxidative-nitrosative stress, mitochondrial and metabolic defects, as well as obesity. The relationship of HFpEF to aging and atrial fibrillation will be examined from the perspective of DNA methylation.

Arterial stiffness has been linked to impaired cognitive function and dementia but the reason for the association is uncertain. This review proposes that collagen type IV is a critical factor linking arterial stiffness and dementia. Several genome wide association studies have related arterial stiffness to Collagen type IVα. Proteomic studies of arteries, demonstrated higher levels of collagen IVα1 in persons with high arterial stiffness. Collagen type IV defects are associated genetic causes of dementia as well as dementia of a variety of other causes. There are plausible causal roles for collagen type IV in dementia. Disorders of Collagen type IV can produce (I) fibro-hyalinosis and elastosis of small arterioles leading to cerebral ischemia and infarction; (II) dysfunction of the blood brain barrier leading to cerebral hemorrhage; (III) carotid artery stiffness with increase pulse pressure induces cerebral blood vessel damage leading to cerebral atrophy. The mechanisms by which Collagen type IV can lead to vascular stiffness include its degradation by matrix metalloprotease type 2 that (a) stimulates vascular smooth muscle cells to produce more extracellular matrix or (b) liberates peptides that damage the subendothelial space. Factors, such as TGF-β1, and LDL cholesterol especially oxidized LDL can increase collagen type IV and produce vascular stiffness and dementia. Fibroblast growth factor 23, and abnormal NO signaling have been linked to collagen type IV or increased vascular stiffness and an increased risk of dementia. Recognition of the central role of collagen type IV in arterial stiffness and dementia will inspire new research focused on determining whether its modification can benefit arterial and brain health., Competing Interests: None., (AJTR Copyright © 2023.)

Background: Current inferences about the site of origin (SOO) of premature ventricular complexes (PVC) from the surface ECG have not been subjected to newer data analytic techniques that identify signals that are not recognized by visual inspection., Aims: The objective of this study was to apply data analytics to PVC characteristics., Methods: PVCs from 12-lead ECGs of a consecutive series of 338 individuals were examined by unsupervised machine learning cluster analysis, and indexes were compared to a composite criterion for SOO., Results: Data analytics found that V1S plus V2S ≤ 9.25 of the PVC had a LVOT origin (sensitivity 95.4%; specificity 97.5%). V1R + V2R + V3R > 15.0 (a RBBB configuration) likely had a LVOT origin. PVCs with V1S plus V2S > 12.75 (LBBB configuration) likely had a RVOT origin. PVC with V1S plus V2S > 14.25 (LBBB configuration) and all inferior leads positive likely had a RVOT origin., Conclusion: Newer data analytic techniques provide a non-invasive approach to identifying PVC SOO, which should be useful for the clinician evaluating a 12-lead ECG.

Background: Identifying prolonged QT interval in RBBB has been problematic., Methods: Four approaches were compared to adjust for the QT prolongation in intermittent RBBB. The implications were assessed in a separate group of 200 persons with established RBBB., Results: In 12 individuals, mean age 74.5 years with intermittent RBBB, the presence of RBBB significantly ( p  < 0.05) increased the QT interval in each of six different heart rate correction formulae by an amount ranging from 35.4 ms in the Hodges formula to 50.2 ms in the Bazett formula. Four different equations were tested to adjust the QT interval and one approach QTc RBBB  = 0.945*QTc RBBB  - 26 was the best method to adjust for the increased QT in RBBB as it produced a QT value that was not significantly different from the QT interval in the absence of RBBB in intermittent RBBB.Failure to adjust the QT interval in RBBB produces an overestimate of the QT interval which in some heart rate adjustment formulae was marked. For the Bazett heart rate adjustment approach QTc 450 ms was found in 73.9% of men and QTc over 460 ms was found in 60.6% of women., Conclusion: These data suggest the implementation of a new approach to recalculate the QT intervals in RBBB. QTc RBBB = 0.945*QTc RBBB  - 26 with an appropriate heart rate adjustment formula (other than the Bazett formula) accurately predicts the QT interval in the absence of RBBB.

Background: The main objective of this study was to determine whether myocardial strain and myocardial work are altered in hypertension and whether the strain is independent of hypertension-induced left ventricular hypertrophy., Methods: Two systematic literature searches were conducted using Medline and EMBASE through to June 30, 2022. In the first, search terms left ventricular strain or speckle tracking AND hypertension and left ventricular hypertrophy were used in conjunction with Boolean operators to identify articles reporting left ventricular strain in patients with hypertension. In the second, the terms Global cardiac or myocardial work AND hypertension were used to identify articles. Publication bias was assessed by examination of funnel plots and calculation of the Failsafe N and Duval and Tweedie's Trim and fill. The results were presented as Forrest plots., Results: Global longitudinal strain (GLS) was significantly lower in patients with hypertension compared to those without hypertension with a mean difference of 2.0 ± 0.1 (standard error of mean(SEM)) in the fixed effect model. Global circumferential strain (GCS) was significantly lower in hypertension. The mean difference between the hypertensive and non-hypertensive groups was 1.37 ± 0.17. Global radial strain (GRS) was significantly ( p < 0.05) greater in hypertension. However, this difference was significant in only 3 and of borderline significance in 3 of 14 studies where GRS was measured. The mean difference between the hypertensive and non-hypertensive groups was 1.5 ± 0.5 using the fixed effects model. There was a significant relationship between GLS and GCS as well as between GCS and GRS but no significant relationship between GLS and GRS. There was no significant difference in left ventricular ejection fraction (LVEF) between the hypertension and no hypertension groups. There was no significant relationship between LVEF and either GLS or GCS but a significant negative correlation was found between LVEF and GRS. GLS was further reduced in persons with hypertension and left ventricular hypertrophy (LVH) compared to hypertension without LVH. In contrast, there were no or minimal differences in GCS and GRS for individuals with hypertension and LVH compared to those without LVH. Global myocardial work index (GWI) and Global constructive work (GCW) were significantly greater in patients with hypertension compared to controls. Global wasted work (GWW) indicated significantly less wasted work in controls compared to hypertension. In contrast, Global work efficiency (GWE) was significantly lower in hypertension compared to the control., Conclusions: There was a significant reduction in GLS and GCS in hypertension while GRS was increased. The reduction in GLS in hypertension was not dependent on the presence of LVH. GLS was further reduced in persons with hypertension when LVH was present. In contrast, there were no or minimal differences in GCS and GRS for individuals with LVH compared to those without LVH. GLS was independent of left ventricle (LV) ejection fraction. GWI, GCW and GWW were greater in hypertension while GWE was lower in hypertension compared to controls. These data support the contention that GLS and indices of global work are early markers of hypertensive heart disease., Competing Interests: The authors declare no conflict of interest. Simon W. Rabkin is serving as Guest Editor of this journal. We declare that Simon W. Rabkin had no involvement in the peer review of this article and has no access to information regarding its peer review. Full responsibility for the editorial process for this article was delegated to Vincent Figueredo., (Copyright: © 2023 The Author(s). Published by IMR Press.)

Purpose of Review: The purpose of this review was to synthesize the evidence on non-traditional biomarkers from proteomic and metabolomic studies that may distinguish heart failure (HF) with preserved ejection fraction (HFpEF) from heart failure with reduced ejection fraction (HFrEF) and non-HF., Recent Findings: Understanding the pathophysiology of HFpEF continues to be challenging. A number of inflammatory and metabolic biomarkers that have recently been suggested to be involved include C-reactive protein (CRP), interleukin-6 (IL-6), trimethylamine-N-oxide (TMAO), syndecan-1 (SDC-1), nitric oxide (NO), and tumor necrosis factor receptor-1 (TNFR-1). A systematic search was conducted using Medline, EMBASE, and Web of Science with search terms such as "HFpEF," "metabolomics," and "proteomics," and a meta-analysis was conducted. The results demonstrate significantly higher levels of TMAO, CRP, SDC-1, and IL-6 in HFpEF compared to controls without HF and significantly higher levels of TMAO and CRP in HFrEF compared to controls. The results further suggest that HFpEF might be distinguishable from HFrEF based on higher levels of IL-6 and lower levels of SDC-1 and NO. These data may reflect pathophysiological differences between HFpEF and HFrEF., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Clozapine, a superior treatment for treatment-resistant schizophrenia can cause potentially life-threatening myocarditis and dilated cardiomyopathy. While the occurrence of this condition is well known, its molecular mechanisms are unclear and may be multifactorial. Putative mechanisms warrant an in-depth review not only from the perspective of toxicity but also for understanding the molecular mechanisms of the adverse cardiac effects of clozapine and the development of novel therapeutic approaches. Clozapine-induced cardiac toxicity encompasses a diverse set of pathways, including (i) immune modulation and proinflammatory processes encompassing an IgEmediated (type I hypersensitivity) response and perhaps a cytokine release syndrome (ii) catecholaminergic activation (iii) induction of free radicals and oxidative stress (iv) activation of cardiomyocyte cell death pathways, including apoptosis, ischemia through impairment in coronary blood flow via changes in endothelial production of NO and vasoconstriction induced by norepinephrine as well as other factors released from cardiac mast cells. (v) In addition, an extensive examination of the effects of clozapine on non-cardiac cellular proteins demonstrates that clozapine can impair enzymes involved in cellular metabolism, such as pyruvate kinase, mitochondrial malate dehydrogenase, and other proteins, including α-enolase, triosephosphate isomerase and cofilin, which might explain clozapine-induced reductions in myocardial energy generation for cell viability as well as contractile function. Pharmacologic antagonism of these cellular protein effects may lead to the development of strategies to antagonize the cardiac damage induced by clozapine., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Heart failure with preserved ejection (HFpEF) is a heterogenous condition affecting nearly half of all patients with heart failure (HF). Artificial intelligence methodologies can be useful to identify patient subclassifications with important clinical implications. We sought a comparison of different machine learning (ML) techniques and clustering capabilities in defining meaningful subsets of patients with HFpEF. Three unsupervised clustering strategies, hierarchical clustering, K-prototype, and partitioning around medoids (PAM), were used to identify distinct clusters in patients with HFpEF, based on a wide range of demographic, laboratory, and clinical parameters. The study population had a median age of 77 years, with a female majority, and moderate diastolic dysfunction. Hierarchical clustering produced six groups but two were too small (two and seven cases) to be clinically meaningful. The K-prototype methods produced clusters in which several clinical and biochemical features did not show statistically significant differences and there was significant overlap between the clusters. The PAM methodology provided the best group separations and identified six mutually exclusive groups (HFpEF1-6) with statistically significant differences in patient characteristics and outcomes. Comparison of three different unsupervised ML clustering strategies, hierarchical clustering, K-prototype, and partitioning around medoids (PAM), was performed on a mixed dataset of patients with HFpEF containing clinical and numerical data. The PAM method identified six distinct subsets of patients with HFpEF with different long-term outcomes or mortality. By comparison, the two other clustering algorithms, the hierarchical clustering and K-prototype, were less optimal.

The ability to distinguish clinically meaningful subtypes of heart failure with preserved ejection fraction (HFpEF) has recently been examined by machine learning techniques but studies appear to have produced discordant results. The objective of this study is to synthesize the types of HFpEF by examining their features and relating them to phenotypes with adverse prognosis. A systematic search was conducted using the search terms "Diastolic Heart Failure" OR "heart failure with preserved ejection fraction" OR "heart failure with normal ejection fraction" OR "HFpEF" AND "machine learning" OR "artificial intelligence" OR 'computational biology'. Ten studies were identified and they varied in their prevalence of ten clinical variables: age, sex, body mass index (BMI) or obesity, hypertension, diabetes mellitus, coronary artery disease, atrial fibrillation, chronic kidney disease, chronic obstructive pulmonary disease or symptom severity (NYHA class or BNP). The clinical findings associated with the different phenotypes in > 85 % of studies were age, hypertension, atrial fibrillation, chronic kidney disease and worse symptoms severity; an adverse outcome was in 65 % to 85 % of studies identified diabetes mellitus and female sex and in less than 65 % of studies was body mass index or obesity, and coronary artery disease. COPD was a relevant factor in only 33 % of studies. Adverse clinical outcome - death or admission to hospital (for heart failure) defined phenogroups with the worst outcome. Combining the 4 studies that calculated the MAGGIC score showed a significant (p<0.05) linear relationship between MAGGIC score and outcome, using the one-year event rate. A new score based on strength of the evidence of the HFpEF studies analyzed here, using 9 variables (eliminating COPD), showed a significant (p<0.009) linear relationship with one-year event rate. Three studies examined biomarkers in detail and the ones most prominently related to outcome or consistently found in the studies were GDF15, FABP4, FGF23, sST2, renin and TNF. The dominant factors that identified phenotypes of HFpEF with adverse outcome were hypertension, atrial fibrillation, chronic kidney disease and worse symptoms severity. A new simplified score, based on clinical factors, was proposed to assess prognosis in HFpEF. Several biomarkers were consistently elevated in phenogroups with adverse outcomes and may indicate the underlying mechanism or pathophysiology specific for phenotypes with an adverse prognosis., (Copyright © 2022 Rabkin.)

Background and Objective: Palpitations are a common symptom that may indicate cardiac arrhythmias, be a somatic complaint in anxiety disorders, and can be present in patients without either condition. The objective of this review was to explore the pathways and fundamental mechanisms through which individuals appreciate palpitations., Observations: Cardiac afferents provide beat-to-beat sensory information on the heart to the spinal cord, brain stem, and higher brain centers. Cardioception, a subset of interoception ('the physiological sense of the condition of the body'), refers to sensing of the heartbeat. High cardioception is present in persons with lower body mass index, lower percentages of body fat, and anxiety disorders. Low cardioception (lower interoceptive awareness) is associated with psychiatric disorders, such as depression, personality disorders, and schizophrenia. CNS sites associated with heartbeat detection have been identified by functional magnetic resonance imaging studies and heartbeat-evoked electroencephalogram potentials. The right insula, cingulate gyrus, somatomotor and somatosensory cortices nucleus accumbens, left subthalamic nucleus, and left ventral capsule/striatum are implicated in both palpitations and heartbeat detection. Involvement of the brain as a primary modulator of palpitations rests on the data that various areas of the brain are activated in association with cardioception, the ability of focal brain stimulation to induce palpitations, the ability of central alpha receptor agonists and antagonists to modulate palpitations, and suppression of palpitations by transcranial repetitive magnetic stimulation (rTMS)., Conclusions: Palpitations should be viewed as a pathway extending from the heart to the brain. Palpitations are, in part, a reflection of an individual's cardioception awareness, which is modulated by body size, percentage of body fat, and psychological or psychiatric conditions. Palpitations can originate in the brain and involve central neurotransmitters. Treatment of palpitations unrelated to cardiac arrhythmias or anxiety disorders should consider the use of central alpha-2 agonists and possibly rTMS., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Many health care organizations struggle and often do not succeed to be high-performance organizations that are not only efficient and effective but also enjoyable places to work. This review focuses on the physician and organizational roles in limiting achievement of a high-performance team in health care organizations. Ten dimensions were constructed and a number of competencies and metrics were highlighted to overcome the failures to: (i) Ensure that the goals, purpose, mission and vision are clearly defined; (ii) establish a supportive organizational structure that encourages high performance of teams; (iii) ensure outstanding physician leadership, performance, goal attainment; and (iv) recognize that medical team leaders are vulnerable to the abuses of personal power or may create a culture of intimidation/fear and a toxic work culture; (v) select a good team and team members-team members who like to work in teams or are willing and able to learn how to work in a team and ensure a well-balanced team composition; (vi) establish optimal team composition, individual roles and dynamics, and clear roles for members of the team; (vii) establish psychological safe environment for team members; (viii) address and resolve interpersonal conflicts in teams; (xi) ensure good health and well-being of the medical staff; (x) ensure physician engagement with the organization. Addressing each of these dimensions with the specific solutions outlined should overcome the constraints to achieving high-performance teams for physicians in health care organizations.

Objective: There is a need to identify genetic factors that may produce coronary artery atherosclerotic disease (CAD) that are not involved in the usual risk factors leading to CAD. Previous studies have often equated coronary artery calcification (CAC) with CAD with coronary stenosis or its sequelae. The objective of this study was to examine the relationship between phosphatase and actin regulator 1 (PHACTR1) single nucleotide polymorphisms (SNPs) and the type of coronary artery disease CAD versus CAC., Method: A systematic review of the literature was conducted to answer the question of whether PHACTR1 gene polymorphisms are associated with coronary artery disease expressed as coronary artery atherosclerosis or CAC., Results: Eighteen studies spanning seven PHACTR1 SNPs were identified and evaluated for the relationship between PHACTR1 and coronary artery disease. There were significant relationships between rs9349379, rs12526453, and CAD with odds ratios (ORs) (confidence interval) of, respectively, 1.15 (1.13-1.17), 1.13 (1.09-1.17) but not for rs2026458, 1.03 (0.88-1.19). The OR for CAC was 1.22 (1.18-1.26) for rs9349379 and 1.28 (1.21-1.38) for rs12526453., Conclusions: Several PHACTR1 specifically rs9349379 and rs12526453 polymorphisms but not rs2026458, are associated with CAD. There are differences in the association of PHACTR1 SNPs with CAC. PHACTR1 warrants more attention and study for the prevention and treatment of CAD., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

The objective was to evaluate the diagnosis of heart failure with preserved ejection fraction (HFpEF) using the biomarkers, growth differentiation factor-15 (GDF-15), galectin-3 (Gal-3), and soluble ST2 (sST2), and to determine whether they can differentiate HFpEF from heart failure with reduced ejection fraction (HFrEF). Medline and Embase databases were searched with the terms diastolic heart failure or HFpEF, biomarkers, and diagnosis, limited to years 2000 to 2019. There were significantly and consistently higher levels of GDF-15, Gal-3, and sST2 in HFpEF compared to no heart failure. Importantly, the magnitude of the increase in GDF-15 or Gal-3 and possibly sST2,correlated with a greater degree of diastolic dysfunction. There were no significant differences between GDF-15, Gal-3, and sST2 in patients with HFpEF vs HFrEF. In the studies assessing these three biomarkers, BNP was significantly greater in heart failure than controls. Furthermore, BNP was significantly higher in HFrEF compared to HFpEF. The diagnostic utility of GDF-15, Gal-3, and sST2 compared to BNP was evaluated by comparing ROC curves. The data supports the contention that to distinguish HFpEF from HFrEF, an index is needed that incorporates GDF-15, Gal-3, or sST2 as well as BNP. The three biomarkers GDF-15, Gal-3, or sST2 can identify patients with HFpEF compared to individuals without heart failure but cannot differentiate HFpEF from HFrEF. BNP is higher in and is better at differentiating HFrEF from HFpEF. Indices that incorporate GDF-15, Gal-3, or sST2 as well as BNP show promise in differentiating HFpEF from HFrEF.

Objective: Heart failure with preserved ejection (HFpEF) represents nearly half of all patients with heart failure (HF). The objective of this study was to determine whether patient characteristics identify discrete kinds of HFpEF., Methods: Data were collected on 196 patients with HFpEF in a non-hospitalized setting. Clinical and laboratory variables were collected, and 47 candidate variables were examined by the unsupervised clustering strategy partitioning around medoids. The Meta-analysis Global Group in Chronic Heart Failure (MAGGIC) risk score was calculated. Follow-up data on all-cause mortality, cardiovascular mortality, and HF exacerbation, were collected and were not part of the data used to identify subgroups., Results: Six significantly different groups or clusters were found. There were three groups of women (i) individuals with a low proportion of vascular risk factors (HFpEF 1 ) (ii) individuals with a high proportion of hypertension and diabetes, but lower proportion of kidney disease and diastolic dysfunction (HFpEF 3) (iii) older individuals with high rates of atrial fibrillation (AF), chronic kidney disease. They had the worst long-term outcomes (HFpEF 4 ). There were three groups of men (i) individuals with a high proportion of coronary artery disease (CAD), dyslipidemia, higher serum creatinine, and diastolic dysfunction (HFpEF 2 )(ii) individuals with highest BMI, and high proportion of CAD, obstructive sleep apnea, and poorly controlled diabetes (HFpEF 5 ) (iii) individuals with high rates of AF, elevated BNP, biventricular remodeling (HFpEF 6 ). They had a high cardiovascular mortality., Conclusions: HFpEF consists of a heterogenous group of individuals with six distinct clinical subsets that have different long-term outcomes., Competing Interests: Declaration of Competing Interest There were no conflicts of interest., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Whether the QT interval displays circadian rhythm after heart rate correction is unresolved and the relationship of QT interval to heart rate variability (HRV) is uncertain., Objectives: To test the hypothesis that there is a circadian rhythm to QT interval and HRV and determine the relationship between QTc and HRV., Methods: The hourly average ECG data from 24-h ECGs were examined in individuals (50 without medications and 9 on beta blockers only) with no evidence of coronary artery disease or structural heart disease. The QT duration of normal QRS complexes from a series of 30-s windows was measured. The presence of circadian rhythm was tested by the data analytic approach of goodness of fit to a cosine function., Results: QT interval with and without heart rate correction showed a circadian rhythm for five heart rate adjustment formulae except for the Bazett formula. HRV also showed circadian rhythm but with different acrophages and nadirs depending on the HRV component. There were significant (p < 0.05) positive correlations of QTc with pNN50 rms-SD and SDNN and significant (p < 0.05) negative correlations with SDANN and Tri. The beta blocker group did not generally show circadian rhythm for QT interval or HRV., Conclusion: QT, after heart rate adjustment, and HRV have circadian rhythmicity. There are significant correlations between QT interval and HRV indices. Circadian rhythm was blunted with beta blockers. The data are consistent with the concept of a predominance of parasympathetic activity to increase QTc and sympathetic activity to shorten QTc, even after 'correction' of the QT interval for heart rate., (Copyright © 2021 Elsevier Inc. All rights reserved.)

A short QT interval has been difficult to define, and there is debate whether it exists outside of an extremely small group of individuals with inherited channelopathies and whether it predicts cardiac arrhythmias. The objective was to identify cases with short QT and their consequences. Our hospital ECG database was screened for cases with a QTc based on the Bazett formula (QTcBZT) of less than 340 ms. The QTc was recalculated using the spline (QTcRBK) formula, which more accurately adjusts for the heart rate and identifies cases based on percentile distribution of the QT interval. The exclusion criteria were presence of bundle branch block, arrhythmias, or electronic pacemakers. An age- and sex-matched cohort was obtained from individuals with normal QT intervals with the same exclusion criteria. There were 28 cases with a short QTc (QTcRBK < 380 ms). The age was 69.6 ± 14.6 years (mean ± SD) (50% males). The QT interval was 305.7 ± 61.1 ms with QTcRBK 308.4 ± 31.4 ms. Subsequent ECGs showed atrial flutter in 21%, atrial fibrillation in 18%, and atrial tachycardia in 4% of cases. Thus, atrial arrhythmias occurred in 43% of cases. This incidence was significantly ( p < 0.0001) greater than the incidence of atrial arrhythmias in age- and sex-matched controls. In conclusion, a short QT interval can be readily identified based on the first percentile of the new QTc formula. A short QTc is an important marker for the development of atrial arrhythmias, including atrial flutter and atrial fibrillation, with the former predominating. It should be part of patient assessment and warrants consideration to develop strategies for detection and prevention of atrial arrhythmias., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2020 Simon W. Rabkin and Jacky K. K. Tang.)

Hypertension Canada's 2020 guidelines for the prevention, diagnosis, risk assessment, and treatment of hypertension in adults and children provide comprehensive, evidence-based guidance for health care professionals and patients. Hypertension Canada develops the guidelines using rigourous methodology, carefully mitigating the risk of bias in our process. All draft recommendations undergo critical review by expert methodologists without conflict to ensure quality. Our guideline panel is diverse, including multiple health professional groups (nurses, pharmacy, academics, and physicians), and worked in concert with experts in primary care and implementation to ensure optimal usability. The 2020 guidelines include new guidance on the management of resistant hypertension and the management of hypertension in women planning pregnancy., (Copyright © 2020 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved.)

Objective: The objective of the study was to determine the optimal formula to estimate QT interval adjusting for QRS prolongation during right ventricular (RV) pacing., Methods: This observational study included individuals (n = 43) with a newly implanted permanent ventricular pacemaker, who had a narrow QRS complex before pacemaker insertion. QT interval with RV pacing was related to QT interval before pacemaker implantation. The validation cohort (n = 442) had permanent RV pacing in DDD mode., Results: A new QTc formula was derived utilizing the constants from the relationship between the spline heart rate QT correction (QTcRBK) before and after pacing; specifically, QTcRBK PACED  = QTcRBK × 0.86. The JT interval from paced complexes was highly heart rate (HR) dependent and was not accurate for QT assessment. Previous, QTc formula for paced complexes were not highly correlated with QT before pacing unless a robust HR correction is added. Formulae subtracting a fixed amount from QTc PACED markedly overestimated QTc before pacing., Conclusion: We proposed a new, simple formula for QT estimation in RV pacing. JT interval in paced complexes is highly HR dependent and is not accurate for QT assessment. The new spline approach for HR correction for the QT, once incorporated into some previously proposed formulae, blunts HR dependency and improves prediction of QT before pacing. QTcRBK PACED *0.86 and QTcRBK PACED - (QRS*0.5) demonstrated the best balance of relatively strong correlation to QTc before pacing and accurate QTc prolongation identification. Abnormal QT for QTcRBK PACED *0.86 as defined by the 97.5th and 99th percentile are 469 and 479 ms respectively., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Objective: To determine the effect of exercise and heart rate on the early repolarization (ER) pattern; focusing on the new criteria for identification of ER., Methods: The ECG measurements on the terminal QRS notch or slur found in early repolarization were quantitated before, during and after exercise; specifically: (i) the amplitude at the onset of the notch (J o ) (ii) the amplitude at the peak of the notch (J p ), (iii) the amplitude at the end of the notch (J t ), (iv) the duration from J o to J p (D 1 ) and (v) the duration from J o to J t (D 2 )., Results: All individuals (N = 21) fulfilling the criteria for ER showed complete disappearance of ER after 3 min of exercise. After 5 min of recovery, 29% of subjects showed return of the ER. The return of ER was dynamic with QRS notching of varying extent, without ST elevation, being evident first. The relationship between heart rate and ER was significant and nonlinear, best fit by a second-order polynomial, suggesting that changes in heart rate with exercise was a factor influencing the presence of the ER pattern and the parameters that define ER., Conclusion: Each of the newly defined characteristics of the ER are modified and eventually disappear with exercise. The return of ER was dynamic with QRS notching of varying extent being evident first. The changes correlated with variations in heart rate, during both exercise and recovery, suggesting, in part, a role in the underlying mechanism of ER., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Engagement of physicians with their healthcare community or institution should be a central issue in healthcare because it can be translated into improved patient care, enhanced well-being for physicians as well as safer, more effective and less costly healthcare. To accomplish the mission/goal of meaningful physician engagement, we set about to establish a 'charter' for physician engagement. We defined our concept of meaningful physician engagement and customised the engagement spectrum construct for physician relationship with their healthcare community or institution. While recognising the importance of physician leaders within the hierarchical system for efficacy of organisational management, relying only on physicians in formal executive positions is insufficient for developing physician engagement. There is a need for widespread physician engagement across the organisation. The objective is both an improvement in patient care and in physician well-being., (© Royal College of Physicians 2019. All rights reserved.)

Background: Determination of the prolonged QT interval in left bundle branch block (LBBB), which should be of special concern to identify individuals at high risk of potentially fatal cardiac arrhythmia risk, has been problematic., Methods: Electrocardiograms (ECGs) (n = 17) in intermittent LBBB were used to develop a new formula for the calculation of QTc in LBBB. This formula and 5 others were compared in a population with LBBB (n = 2610). The QT was corrected for heart rate (HR) using the Bazett formula (QTcBZT) and the spline QT formula (QTcRBK), which is relatively independent of HR. The JT interval was significantly related to HR., Results: The new approach (QTc LBBB NEW = 0.945*QTcRBK LBBB  - 26) in LBBB showed the highest correlation with intrinsic QTc (without LBBB) and had minimal HR dependency. Previous formulae to determine the QT interval in LBBB showed significant HR dependency except for one proposed by Rautaharju et al. Inclusion of an HR correction factor in existing formulae blunted HR dependency but not if the QT interval was adjusted by the QTcBZT. In men and women, use of the QTcBZT markedly increases the proportion of individuals with prolonged QTc, which was more evident with increasing HR. The 99th and 97.5th percentiles for QTc LBBB NEW for men and women identified abnormal QT prolongation in LBBB., Conclusions: A new formula that modifies the QT and JT intervals in LBBB predicts the QT interval in the absence of LBBB. Abnormal QT intervals in the 99th and 97.5th percentiles can identify patients with LBBB who have QT interval prolongation., (Copyright © 2019 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved.)

Heart failure with preserved ejection fraction (HFpEF), a common condition with an increased mortality, is strongly associated with obesity and the metabolic syndrome. The latter two conditions are associated with increased epicardial fat that can extend into the heart. This review advances the proposition that hypoxia-inhibitory factor-1α (HIF-1α) maybe a key factor producing HFpEF. HIF-1α, a highly conserved transcription factor that plays a key role in tissue response to hypoxia, is increased in adipose tissue in obesity. Increased HIF-1α expression leads to expression of a potent profibrotic transcriptional programme involving collagen I, III, IV, TIMP, and lysyl oxidase. The net effect is the formation of collagen fibres leading to fibrosis. HIF-1α is also responsible for recruiting M1 macrophages that mediate obesity-associated inflammation, releasing IL-6, MCP-1, TNF-α, and IL-1β with increased expression of thrombospondin, pro α2 (I) collagen, transforming growth factor β, NADPH oxidase, and connective tissue growth factor. These factors can accelerate cardiac fibrosis and impair cardiac diastolic function. Inhibition of HIF-1α expression in adipose tissue of mice fed a high-fat diet suppressed fibrosis and reduces inflammation in adipose tissue. Delineation of the role played by HIF-1α in obesity-associated HFpEF may lead to new potential therapies., (© 2019 World Obesity Federation.)

Heart failure with preserved ejection fraction (HFpEF) represents an important cardiac condition because of its increasing prevalence, resistance to treatment and high associated morbidity and mortality. Two of the major mechanisms responsible for HFpEF are impaired cardiomyocyte sarcoplasmic reticulum (SR) Ca 2+ ATPase (SERCA2a), which is responsible for calcium reuptake into the SR, and cardiac fibroblasts/myofibroblasts that produce collagen or myocardial fibrosis. Phospholamban (PLB), in the SR and endoplasmic reticulum, is the primary regulator of SERCA2a in the heart and acts as a reversible inhibitor of SERCA2a. Glucagon-like peptide-1, a 30 amino acid peptide, improves diastolic function through increasing SERCA2a expression and activity as well as by decreasing phosphorylation of Ryanodine receptors. It also enhances collagen production through enhanced procollagen IalphaI/IIIalphaI, connective tissue growth factor, fibronectin, TGF-β3 as well as Interleukin -10, -1beta, and -6 gene expression. Relaxin-2, a two chain, 53 amino acid peptide, increases Ser16- and Thr17-phosphorylation levels of PLB, thereby relieving SERCA2a of its inhibition. H3 Relaxin inhibits TGF-β1-stimulated collagen deposition through H3 relaxin-induced increases in pSmad2. Neuregulin-1, an epidermal growth factor, induces nitric oxide and PI-3 kinase activation that enhance SERCA2 activity. Neuregulin-1 was associated with less myocardial macrophage infiltration and cytokine expression reducing collagen deposition. Ghrelin, a 28 amino acid peptide, improves SERCA2a function by inducing PLB phosphorylation. Ghrelin also reduces cardiac fibrosis. In summary, Glucagon-like peptide-1, Relaxin-2, Neuregulin-1, and Ghrelin each modify calcium dynamics, collagen expression, and myocardial fibrosis through attenuation of deleterious signaling cascades, and induction of adaptive pathways, representing potential therapeutic targets for HFpEF., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Hypertension Canada provides annually updated, evidence-based guidelines for the diagnosis, assessment, prevention, and treatment of hypertension in adults and children. This year, the adult and pediatric guidelines are combined in one document. The new 2018 pregnancy-specific hypertension guidelines are published separately. For 2018, 5 new guidelines are introduced, and 1 existing guideline on the blood pressure thresholds and targets in the setting of thrombolysis for acute ischemic stroke is revised. The use of validated wrist devices for the estimation of blood pressure in individuals with large arm circumference is now included. Guidance is provided for the follow-up measurements of blood pressure, with the use of standardized methods and electronic (oscillometric) upper arm devices in individuals with hypertension, and either ambulatory blood pressure monitoring or home blood pressure monitoring in individuals with white coat effect. We specify that all individuals with hypertension should have an assessment of global cardiovascular risk to promote health behaviours that lower blood pressure. Finally, an angiotensin receptor-neprilysin inhibitor combination should be used in place of either an angiotensin-converting enzyme inhibitor or angiotensin receptor blocker in individuals with heart failure (with ejection fraction < 40%) who are symptomatic despite appropriate doses of guideline-directed heart failure therapies. The specific evidence and rationale underlying each of these guidelines are discussed., (Copyright © 2018 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved.)

Systolic and diastolic blood pressure thresholds, below which cardiovascular events increase, are widely debated. Using data from the SPRINT (Systolic Blood Pressure Intervention Trial), we evaluated the relation between systolic and diastolic pressure and cardiovascular events among 1519 participants with or 7574 without prior cardiovascular disease. Using Cox regression, we examined the composite risk of myocardial infarction, other acute coronary syndrome, stroke, heart failure, or cardiovascular death, and follow-up systolic and diastolic pressure were analyzed as time-dependent covariates for a median of 3.1 years. Models were adjusted for age, sex, baseline systolic pressure, body mass index, 10-year Framingham risk score, and estimated glomerular filtration rate. A J-shaped relationship with diastolic pressure was observed in both treatment arms in patients with or without cardiovascular disease ( P nonlinearity≤0.002). When diastolic pressure fell <55 mm Hg, the hazards were at least 25% higher relative to 70 mm Hg ( P =0.29). The hazard ratios (95% CI) of diastolic pressure <55 mm Hg versus 55 to 90 mm Hg were 1.68 (1.16-2.43), P value 0.006 and 1.52 (0.99-2.34), P value 0.06 in patients without and with prior cardiovascular disease, respectively. After adjusting for follow-up diastolic pressure, follow-up systolic pressure was not associated with the outcome in those without prior cardiovascular disease ( P =0.64). In those with cardiovascular disease, adjusting for diastolic pressure, follow-up systolic pressure was associated with the risk in the intensive arm (hazard ratio per 10 mm Hg decrease, 0.86; 95% CI, 0.75-0.99; P interaction=0.02). Although the observed J-shaped relationship may be because of reverse causality in the SPRINT population, we advise caution in aggressively lowering diastolic pressure., (© 2018 American Heart Association, Inc.)

Current assessment and management of ascending thoracic aortic aneurysm (ATAA) rely heavily on the diameter of the ATAA and blood pressure rather than biomechanical and hemodynamic parameters such as arterial wall deformation or wall shear stress. The objective of the current study was to develop an accurate computational method for modeling the mechanical responses of the ATAA to provide additional information in patient evaluations. Fully coupled fluid structure interaction simulations were conducted using data from cases with ATAA with measured geometrical parameters in order to evaluate and analyze the change in biomechanical responses under normotensive and hypertensive conditions. Anisotropic hyperelastic material property estimates were applied to the ATAA data which represented three different geometrical configurations of ATAAs. The resulting analysis showed significant variations in maximum wall shear stress despite minimal differences in flow velocity between two blood pressure conditions. Additionally, the three different ATAA conditions identified different aortic expansions that were not uniform under pulsatile pressure. The elevated wall stress with hypertension was also geometry-dependent. The developed models suggest that ATTA cases have unique characteristic in biomechanical and hemodynamic evaluations that can be useful in risk management.

The objective was to improve the management of patients with hypertension (HTN) and coronary artery disease (CAD), utilizing a model which integrates 3 determinants of coronary blood flow (CBF)-CAD severity, diastolic blood pressure (DBP), and left ventricular (LV) mass. We validated non-parametric equations for CBF estimation in a consecutive patient sample (N = 81) with HTN and CAD. There was a highly significant correlation (r = .565; P < .01) between clinical DBP and estimated CBF. Greater LV mass and more severe CAD shifted the relationship towards less CBF at the same DBP. LV mass was more critical when DBP >70 mm Hg. Estimated changes in CBF at different DBP considering the severity of CAD and LV mass can be calculated. In summary, the severity of CAD from coronary CT or coronary angiography combined with LV mass from echocardiography permits clinicians to guide the extent of, or target for, DBP to avoid seriously compromising CBF., (©2018 Wiley Periodicals, Inc.)