Accurate diagnosis of apical hypertrophic cardiomyopathy using explainable advanced electrocardiogram analysis.

AIMS: Typical electrocardiogram (ECG) features of apical hypertrophic cardiomyopathy (ApHCM) include tall R waves and deep or giant T-wave inversion in the precordial leads, but these features are not always present. The ECG is used as the gatekeeper to cardiac imaging for diagnosis. We tested whether explainable advanced ECG (A-ECG) could accurately diagnose ApHCM. METHODS AND RESULTS: Advanced ECG analysis was performed on standard resting 12-lead ECGs in patients with ApHCM [n = 75 overt, n = 32 relative (<15 mm hypertrophy); a subgroup of which underwent cardiovascular magnetic resonance (n = 92)], and comparator subjects (n = 2449), including healthy volunteers (n = 1672), patients with coronary artery disease (n = 372), left ventricular electrical remodelling (n = 108), ischaemic (n = 114) or non-ischaemic cardiomyopathy (n = 57), and asymmetrical septal hypertrophy HCM (n = 126). Multivariable logistic regression identified four A-ECG measures that together discriminated ApHCM from other diseases with high accuracy [area under the receiver operating characteristic (AUC) curve (bootstrapped 95% confidence interval) 0.982 (0.965-0.993)]. Linear discriminant analysis also diagnosed ApHCM with high accuracy [AUC 0.989 (0.986-0.991)]. CONCLUSION: Explainable A-ECG has excellent diagnostic accuracy for ApHCM, even when the hypertrophy is relative, with A-ECG analysis providing incremental diagnostic value over imaging alone. The electrical (ECG) and anatomical (wall thickness) disease features do not completely align, suggesting that future diagnostic and management strategies may incorporate both features.

Accelerated DNA methylation age plays a role in the impact of cardiovascular risk factors on the human heart.

BACKGROUND: DNA methylation (DNAm) age acceleration (AgeAccel) and cardiac age by 12-lead advanced electrocardiography (A-ECG) are promising biomarkers of biological and cardiac aging, respectively. We aimed to explore the relationships between DNAm age and A-ECG heart age and to understand the extent to which DNAm AgeAccel relates to cardiovascular (CV) risk factors in a British birth cohort from 1946. RESULTS: We studied four DNAm ages (AgeHannum, AgeHorvath, PhenoAge, and GrimAge) and their corresponding AgeAccel. Outcomes were the results from two publicly available ECG-based cardiac age scores: the Bayesian A-ECG-based heart age score of Lindow et al. 2022 and the deep neural network (DNN) ECG-based heart age score of Ribeiro et al. 2020. DNAm AgeAccel was also studied relative to results from two logistic regression-based A-ECG disease scores, one for left ventricular (LV) systolic dysfunction (LVSD), and one for LV electrical remodeling (LVER). Generalized linear models were used to explore the extent to which any associations between biological cardiometabolic risk factors (body mass index, hypertension, diabetes, high cholesterol, previous cardiovascular disease [CVD], and any CV risk factor) and the ECG-based outcomes are mediated by DNAm AgeAccel. We derived the total effects, average causal mediation effects (ACMEs), average direct effects (ADEs), and the proportion mediated [PM] with their 95% confidence intervals [CIs]. 498 participants (all 60-64 years) were included, with the youngest ECG heart age being 27 and the oldest 90. When exploring the associations between cardiometabolic risk factors and Bayesian A-ECG cardiac age, AgeAccelPheno appears to be a partial mediator, as ACME was 0.23 years [0.01, 0.52] p = 0.028 (i.e., PM≈18%) for diabetes, 0.34 [0.03, 0.74] p = 0.024 (i.e., PM≈15%) for high cholesterol, and 0.34 [0.03, 0.74] p = 0.024 (PM≈15%) for any CV risk factor. Similarly, AgeAccelGrim mediates ≈30% of the relationship between diabetes or high cholesterol and the DNN ECG-based heart age. When exploring the link between cardiometabolic risk factors and the A-ECG-based LVSD and LVER scores, it appears that AgeAccelPheno or AgeAccelGrim mediate 10-40% of these associations. CONCLUSION: By the age of 60, participants with accelerated DNA methylation appear to have older, weaker, and more electrically impaired hearts. We show that the harmful effects of CV risk factors on cardiac age and health, appear to be partially mediated by DNAm AgeAccelPheno and AgeAccelGrim. This highlights the need to further investigate the potential cardioprotective effects of selective DNA methyltransferases modulators.

Heart age gap estimated by explainable advanced electrocardiography is associated with cardiovascular risk factors and survival.

Aims: Deep neural network artificial intelligence (DNN-AI)-based Heart Age estimations have been presented and used to show that the difference between an electrocardiogram (ECG)-estimated Heart Age and chronological age is associated with prognosis. An accurate ECG Heart Age, without DNNs, has been developed using explainable advanced ECG (A-ECG) methods. We aimed to evaluate the prognostic value of the explainable A-ECG Heart Age and compare its performance to a DNN-AI Heart Age. Methods and results: Both A-ECG and DNN-AI Heart Age were applied to patients who had undergone clinical cardiovascular magnetic resonance imaging. The association between A-ECG or DNN-AI Heart Age Gap and cardiovascular risk factors was evaluated using logistic regression. The association between Heart Age Gaps and death or heart failure (HF) hospitalization was evaluated using Cox regression adjusted for clinical covariates/comorbidities. Among patients [n = 731, 103 (14.1%) deaths, 52 (7.1%) HF hospitalizations, median (interquartile range) follow-up 5.7 (4.7-6.7) years], A-ECG Heart Age Gap was associated with risk factors and outcomes [unadjusted hazard ratio (HR) (95% confidence interval) (5 year increments): 1.23 (1.13-1.34) and adjusted HR 1.11 (1.01-1.22)]. DNN-AI Heart Age Gap was associated with risk factors and outcomes after adjustments [HR (5 year increments): 1.11 (1.01-1.21)], but not in unadjusted analyses [HR 1.00 (0.93-1.08)], making it less easily applicable in clinical practice. Conclusion: A-ECG Heart Age Gap is associated with cardiovascular risk factors and HF hospitalization or death. Explainable A-ECG Heart Age Gap has the potential for improving clinical adoption and prognostic performance compared with existing DNN-AI-type methods.

Electrocardiographic parameters associated with pacemaker induced cardiomyopathy.

BACKGROUND: Chronic right ventricular (RV) pacing can induce left ventricular (LV) dyssynchrony and cause pacemaker induced cardiomyopathy (PiCM). Identifying which patients are at risk for PiCM is limited. METHODS: Patients receiving RV-only permanent pacemakers (PPMs) at Duke University Medical Center between 2011 and 2017 who had normal baseline ejection fractions (EFs) were identified. Patients who developed a subsequent decrease in EF, died, or underwent cardiac resynchronization therapy, left ventricular assist device, or heart transplant without a competing cause were considered as the primary endpoint. Pre-PPM and post-PPM electrocardiograms (ECGs) were analyzed to extract scalar measurements including the lead one ratio (LOR) as well as advanced-ECG (A-ECG) features to identify predictors of PiCM. Traditional and penalized Cox regression were used to identify variables predictive of the primary endpoint. RESULTS: Pre-PPM ECGs were evaluated for 404 patients of whom 140 (35%) experienced the primary endpoint. Predictors included female sex (hazard ratio [HR] 1.14), a T' wave in V6 (HR 1.31), a P' wave in aVL (HR 0.88), and estimated glomerular filtration rate (HR 0.88). Post-PPM ECGs were evaluated for 228 patients for whom 94 (41%) experienced the primary endpoint. Predictors included female sex (HR 0.50), age (HR 1.06), and a history of congestive heart failure (HR 1.63). Neither LOR nor A-ECG parameters were strong predictors of the primary endpoint. CONCLUSIONS: Baseline and paced ECG data provide limited insight into which patients are at high risk for developing PiCM.

An electrocardiography score predicts heart failure hospitalization or death beyond that of cardiovascular magnetic resonance imaging.

The electrocardiogram (ECG) and cardiovascular magnetic resonance imaging (CMR) provide powerful prognostic information. The aim was to determine their relative prognostic value. Patients (n = 783) undergoing CMR and 12-lead ECG with a QRS duration < 120 ms were included. Prognosis scores for one-year event-free survival from hospitalization for heart failure or death were derived using continuous ECG or CMR measures, and multivariable logistic regression, and compared. Patients (median [interquartile range] age 55 [43-64] years, 44% female) had 155 events during 5.7 [4.4-6.6] years. The ECG prognosis score included (1) frontal plane QRS-T angle, and (2) heart rate corrected QT duration (QTc) (log-rank 55). The CMR prognosis score included (1) global longitudinal strain, and (2) extracellular volume fraction (log-rank 85). The combination of positive scores for both ECG and CMR yielded the highest prognostic value (log-rank 105). Multivariable analysis showed an association with outcomes for both the ECG prognosis score (log-rank 8.4, hazard ratio [95% confidence interval] 1.29 [1.09-1.54]) and the CMR prognosis score (log-rank 47, hazard ratio 1.90 [1.58-2.28]). An ECG prognosis score predicted outcomes independently of CMR. Combining the results of ECG and CMR using both prognosis scores improved the overall prognostic performance.

Improved evaluation of left ventricular hypertrophy using the spatial QRS-T angle by electrocardiography.

Electrocardiographic (ECG) signs of left ventricular hypertrophy (LVH) lack sensitivity. The aim was to identify LVH based on an abnormal spatial peaks QRS-T angle, evaluate its diagnostic performance compared to conventional ECG criteria for LVH, and its prognostic performance. This was an observational study with four cohorts with a QRS duration < 120 ms. Based on healthy volunteers (n = 921), an abnormal spatial peaks QRS-T angle was defined as ≥ 40° for females and ≥ 55° for males. In other healthy volunteers (n = 461), the specificity of the QRS-T angle to detect LVH was 96% (females) and 98% (males). In patients with at least moderate LVH by cardiac imaging (n = 225), the QRS-T angle had a higher sensitivity than conventional ECG criteria (93-97% vs 13-56%, p < 0.001 for all). In clinical consecutive patients (n = 783), of those who did not have any LVH, 238/556 (43%) had an abnormal QRS-T angle. There was an association with hospitalization for heart failure or all-cause death in univariable and multivariable analysis. An abnormal QRS-T angle rarely occurred in healthy volunteers, was a mainstay of moderate or greater LVH, was common in clinical patients without LVH but with cardiac co-morbidities, and associated with outcomes.

The Neuroimmune Response to Surgery - An Exploratory Study of Trauma-Induced Changes in Innate Immunity and Heart Rate Variability.

Surgery triggers a systemic inflammatory response that ultimately impacts the brain and associates with long-term cognitive impairment. Adequate regulation of this immune surge is pivotal for a successful surgical recovery. We explored the temporal immune response in a surgical cohort and its associations with neuroimmune regulatory pathways and cognition, in keeping with the growing body of evidence pointing towards the brain as a regulator of peripheral inflammation. Brain-to-immune communication acts through cellular, humoral and neural pathways. In this context, the vagal nerve and the cholinergic anti-inflammatory pathway (CAP) have been shown to modify peripheral immune cell activity in both acute and chronic inflammatory conditions. However, the relevance of neuroimmune regulatory mechanisms following a surgical trauma is not yet elucidated. Twenty-five male patients undergoing elective laparoscopic abdominal surgery were included in this observational prospective study. Serial blood samples with extensive immune characterization, assessments of heart rate variability (HRV) and cognitive tests were performed before surgery and continuing up to 6 months post-surgery. Temporal immune responses revealed biphasic reaction patterns with most pronounced changes at 5 hours after skin incision and 14 days following surgery. Estimations of cardiac vagal nerve activity through HRV recordings revealed great individual variations depending on the pre-operative HRV baseline. A principal component analysis displayed distinct differences in systemic inflammatory biomarker trajectories primarily based on pre-operative HRV, with potiential consequences for long-term surgical outcomes. In conclusion, individual pre-operative HRV generates differential response patterns that associate with distinct inflammatory trajectories following surgery. Long-term surgical outcomes need to be examined further in larger studies with mixed gender cohorts.

Heart age estimated using explainable advanced electrocardiography.

Electrocardiographic (ECG) Heart Age conveying cardiovascular risk has been estimated by both Bayesian and artificial intelligence approaches. We hypothesised that explainable measures from the 10-s 12-lead ECG could successfully predict Bayesian 5-min ECG Heart Age. Advanced analysis was performed on ECGs from healthy subjects and patients with cardiovascular risk or proven heart disease. Regression models were used to predict patients' Bayesian 5-min ECG Heart Ages from their standard, resting 10-s 12-lead ECGs. The difference between 5-min and 10-s ECG Heart Ages were analyzed, as were the differences between 10-s ECG Heart Age and the chronological age (the Heart Age Gap). In total, 2,771 subjects were included (n = 1682 healthy volunteers, n = 305 with cardiovascular risk factors, n = 784 with cardiovascular disease). Overall, 10-s Heart Age showed strong agreement with the 5-min Heart Age (R2 = 0.94, p < 0.001, mean ± SD bias 0.0 ± 5.1 years). The Heart Age Gap was 0.0 ± 5.7 years in healthy individuals, 7.4 ± 7.3 years in subjects with cardiovascular risk factors (p < 0.001), and 14.3 ± 9.2 years in patients with cardiovascular disease (p < 0.001). Heart Age can be accurately estimated from a 10-s 12-lead ECG in a transparent and explainable fashion based on known ECG measures, without deep neural network-type artificial intelligence techniques. The Heart Age Gap increases markedly with cardiovascular risk and disease.

Heat Shock Protein 27 Levels Predict Myocardial Inhomogeneities in Hemodialysis Patients.

Background: Sudden cardiac death (SCD) is the single major cause of death in hemodialysis (HD) patients. QRS-T angle is an established marker of global repolarization heterogeneity associated with electrical instability and SCD. Heat shock protein 27 (HSP27) plays an important, protective role against noxious factors in the cardiovascular (CV) system. This study is aimed at assessing whether low HSP27 is associated with myocardial inhomogeneities in HD patients, as expressed by increases in the spatial QRS-T angle. Methods: Clinical data and biochemical, echocardiographic, and electrocardiographic parameters were evaluated in 182 HD patients. Patients were split into normal and abnormal QRS-T angle groups. Results: Patients with abnormally high QRS-T angles were older and had higher prevalence of diabetes as well as myocardial infarction, higher left ventricular mass index (LVMI) and C-reactive protein, worse oxidant/antioxidant status, and lower ejection fraction and HSP27. Multiple regression analysis revealed that abnormal QRS-T values were independently, negatively associated with serum HSP27 and positively associated with LVMI. Conclusions: Low HSP27 levels are associated with increased heterogeneity of myocardial action potential, as expressed by increased spatial QRS-T angle.

Metabolomics and a Breath Sensor Identify Acetone as a Biomarker for Heart Failure.

BACKGROUND: Multi-omics delivers more biological insight than targeted investigations. We applied multi-omics to patients with heart failure with reduced ejection fraction (HFrEF). METHODS: 46 patients with HFrEF and 20 controls underwent metabolomic profiling, including liquid/gas chromatography mass spectrometry (LC-MS/GC-MS) and solid-phase microextraction (SPME) volatilomics in plasma and urine. HFrEF was defined using left ventricular global longitudinal strain, ejection fraction and NTproBNP. A consumer breath acetone (BrACE) sensor validated results in n = 73. RESULTS: 28 metabolites were identified by GCMS, 35 by LCMS and 4 volatiles by SPME in plasma and urine. Alanine, aspartate and glutamate, citric acid cycle, arginine biosynthesis, glyoxylate and dicarboxylate metabolism were altered in HFrEF. Plasma acetone correlated with NT-proBNP (r = 0.59, 95% CI 0.4 to 0.7), 2-oxovaleric and cis-aconitic acid, involved with ketone metabolism and mitochondrial energetics. BrACE > 1.5 ppm discriminated HF from other cardiac pathology (AUC 0.8, 95% CI 0.61 to 0.92, p < 0.0001). CONCLUSION: Breath acetone discriminated HFrEF from other cardiac pathology using a consumer sensor, but was not cardiac specific.

Suppression of Electrographic Seizures Is Associated with Amelioration of QTc Interval Prolongation in Patients with Traumatic Brain Injury.

INTRODUCTION: Disorders in electroencephalography (EEG) are commonly noted in patients with traumatic brain injury (TBI) and may be associated with electrocardiographic disturbances. Electrographic seizures (ESz) are the most common features in these patients. This study aimed to explore the relationship between ESz and possible changes in QTc interval and spatial QRS-T angle both during ESz and after ESz resolution. METHODS: Adult patients with TBI were studied. Surface 12-lead ECGs were recorded using a Cardiax device during ESz events and 15 min after their effective suppression using barbiturate infusion. The ESz events were diagnosed using Masimo Root or bispectral index (BIS) devices. RESULTS: Of the 348 patients considered for possible inclusion, ESz were noted in 72, with ECG being recorded in 21. Prolonged QTc was noted during ESz but significantly ameliorated after ESz suppression (540.19 ± 60.68 ms vs. 478.67 ± 38.52 ms, p < 0.001). The spatial QRS-T angle was comparable during ESz and after treatment. Regional cerebral oximetry increased following ESz suppression (from 58.4% ± 6.2 to 60.5% ± 4.2 (p < 0.01) and from 58.2% ± 7.2 to 60.8% ± 4.8 (p < 0.05) in the left and right hemispheres, respectively). CONCLUSION: QTc interval prolongation occurs during ESz events in TBI patients but both it and regional cerebral oximetry are improved after suppression of seizures.

Predicting peri-operative troponin elevation by advanced electrocardiography.

BACKGROUND: Peri-operative mortality remains a global problem and an improved pre-operative risk assessment identifying those at highest risk for peri-operative myocardial injury might improve postsurgical outcomes. AIMS: To determine whether pre-operative measures of advanced electrocardiography (A-ECG) could predict elevated serum troponin T (TnT) in patients undergoing elective, major non-cardiac surgery. MATERIAL AND METHODS: This observational cohort study included 257 surgical patients who underwent elective major non-cardiac surgery between the years 2012-2013 and 2015-2016 at Karolinska University Hospital. All selected patients were ≥ 18 years of age [median age 70 (63-75) years], had a pre-operative digital 12­lead ECG < 6 months prior to the procedure and a postoperative high-sensitivity cardiac TnT (hs-cTnT) sample. A-ECG confounders including atrial fibrillation or flutter, abundant premature atrial or ventricular contractions, bundle branch blocks, QRS duration >110 ms, heart rate > 100 beats/min and paced rhythms were excluded. Previously validated A-ECG diagnostic scores that detect cardiovascular pathologies were calculated and compared in patients with and without peri-operative myocardial injury, defined as hs-cTnT >14 ng l-1. RESULTS: Pre-operative left ventricular systolic dysfunction by A-ECG was more probable in patients with than without peri-operative myocardial injury (p = 0.03). CONCLUSIONS: While a pre-operative A-ECG score for LVSD was able to differentiate between patients with versus without elevated peri-operative TnT levels, it did not add any further utility to standard clinical parameters for predicting troponin-related events in the studied population.

Multiomics, virtual reality and artificial intelligence in heart failure.

Aim: Multiomics delivers more biological insight than targeted investigations. We applied multiomics to patients with heart failure (HF) and reduced ejection fraction (HFrEF), with machine learning applied to advanced ECG (AECG) and echocardiography artificial intelligence (Echo AI). Patients & methods: In total, 46 patients with HFrEF and 20 controls underwent metabolomic profiling, including liquid/gas chromatography-mass spectrometry and solid-phase microextraction volatilomics in plasma and urine. HFrEF was defined using left ventricular (LV) global longitudinal strain, EF and N-terminal pro hormone BNP. AECG and Echo AI were performed over 5 min, with a subset of patients undergoing a virtual reality mental stress test. Results: A-ECG had similar diagnostic accuracy as N-terminal pro hormone BNP for HFrEF (area under the curve = 0.95, 95% CI: 0.85-0.99), and correlated with global longitudinal strain (r = -0.77, p < 0.0001), while Echo AI-generated measurements correlated well with manually measured LV end diastolic volume r = 0.77, LV end systolic volume r = 0.8, LVEF r = 0.71, indexed left atrium volume r = 0.71 and indexed LV mass r = 0.6, p < 0.005. AI-LVEF and other HFrEF biomarkers had a similar discrimination for HFrEF (area under the curve AI-LVEF = 0.88; 95% CI: -0.03 to 0.15; p = 0.19). Virtual reality mental stress test elicited arrhythmic biomarkers on AECG and indicated blunted autonomic responsiveness (alpha 2 of RR interval variability, p = 1 × 10-4) in HFrEF. Conclusion: Multiomics-related machine learning shows promise for the assessment of HF.

Lay abstract Multiomics is the integration of multiple sources of health information, for example, genomic, metabolite, etc. This delivers more insight than targeted single investigations and provides an ability to perceive subtle individual differences between people. In this study we applied multiomics to patients with heart failure (HF) using DNA sequencing, metabolomics and machine learning applied to ECG echocardiography. We demonstrated significant differences between subsets of patients with HF using these methods. We also showed that machine learning has significant diagnostic potential in identifying HF patients more efficiently than manual or conventional techniques.

Decompressive Craniectomy Improves QTc Interval in Traumatic Brain Injury Patients.

BACKGROUND: Traumatic brain injury (TBI) is commonly associated with cardiac dysfunction, which may be reflected by abnormal electrocardiograms (ECG) and/or contractility. TBI-related cardiac disorders depend on the type of cerebral injury, the region of brain damage and the severity of the intracranial hypertension. Decompressive craniectomy (DC) is commonly used to reduce intra-cranial hypertension (ICH). Although DC decreases ICH rapidly, its effect on ECG has not been systematically studied. The aim of this study was to analyze the changes in ECG in patients undergoing DC. METHODS: Adult patients without previously known cardiac diseases treated for isolated TBI with DC were studied. ECG variables, such as: spatial QRS-T angle (spQRS-T), corrected QT interval (QTc), QRS and T axes (QRSax and Tax, respectively), STJ segment and the index of cardio-electrophysiological balance (iCEB) were analyzed before DC and at 12-24 h after DC. Changes in ECG were analyzed according to the occurrence of cardiac arrhythmias and 28-day mortality. RESULTS: 48 patients (17 female and 31 male) aged 18-64 were studied. Intra-cranial pressure correlated with QTc before DC (p < 0.01, r = 0.49). DC reduced spQRS-T (p < 0.001) and QTc interval (p < 0.01), increased Tax (p < 0.01) and changed STJ in a majority of leads but did not affect QRSax and iCEB. The iCEB was relatively increased before DC in patients who eventually experienced cardiac arrhythmias after DC (p < 0.05). Higher post-DC iCEB was also noted in non-survivors (p < 0.05), although iCEB values were notably heart rate-dependent. CONCLUSIONS: ICP positively correlates with QTc interval in patients with isolated TBI, and DC for relief of ICH reduces QTc and spQRS-T. However, DC might also increase risk for life-threatening cardiac arrhythmias, especially in ICH patients with notably prolonged QTc before and increased iCEB after DC.

Plasma Hyperosmolality Prolongs QTc Interval and Increases Risk for Atrial Fibrillation in Traumatic Brain Injury Patients.

INTRODUCTION: Hyperosmotic therapy with mannitol is frequently used for treatment cerebral edema, and 320 mOsm/kg H2O has been recommended as a high limit for therapeutic plasma osmolality. However, plasma hyperosmolality may impair cardiac function, increasing the risk of cardiac events. The aim of this study was to analyze the relation between changes in plasma osmolality and electrocardiographic variables and cardiac arrhythmia in patients treated for isolated traumatic brain injury (iTBI). METHODS: Adult iTBI patients requiring mannitol infusion following cerebral edema, and with a Glasgow Coma Score below 8, were included. Plasma osmolality was measured with Osmometr 800 CLG. Spatial QRS-T angle (spQRS-T), corrected QT interval (QTc) and STJ segment were calculated from digital resting 12-lead ECGs and analyzed in relation to four levels of plasma osmolality: A) <280 mOsm/kg H2O; B) 280-295 mOsm/kg H2O; C) 295-310 mOsm/kg H2O; and D) >310 mOsm/kg H2O. All parameters were measured during five consecutive days of treatment. RESULTS: 94 patients aged 18-64 were studied. Increased plasma osmolality correlated with prolonged QTc (p < 0.001), intensified disorders in STJ and increased the risk for cardiac arrhythmia. Moreover, plasma osmolality >313 mOms/kg H2O significantly increased the risk of QTc prolongation >500 ms. CONCLUSION: In patients treated for iTBI, excessively increased plasma osmolality contributes to electrocardiographic disorders including prolonged QTc, while also correlating with increased risk for cardiac arrhythmias.

Successful Combination of Landiolol and Levosimendan in Patients with Decompensated Heart Failure.

Tachycardia and supraventricular tachyarrhythmias often impair cardiovascular capacity in patients with decompensated heart failure (dHF) treated with inotropes. Normalization of heart rhythm or rate typically improves diastolic filling and stroke volume (SV). Thus, isochronal administration of an ultra-short-acting and highly selective ß1-blockers, such as landiolol, along with inotropic calcium-sensitizer medications, such as levosimendan, could benefit patients with dHF.We present a case series of three patients with severe dHF and low ejection fraction who were successfully treated with a combination of landiolol and levosimendan. The co-administration of landiolol and levosimendan was well tolerated, improved cardiac function, normalized SV, and enabled the reduction of norepinephrine dosing in all patients. Additionally, the combination improved the vectorcardiographic spatial QRS-T angle and decreased the corrected QT interval. All patients were successfully discharged from the intensive care unit (ICU).A combination of levosimendan and landiolol was safe and well-tolerated. This combination may be a new option for successful treatment of patients with acute dHF complicated by sinus or supraventricular tachycardias.

Substantial prevalence of subclinical cardiovascular diseases in patients with hemophilia A evaluated by advanced electrocardiography.

BACKGROUND: Patients with hemophilia A (PWHA) have reportedly lower mortality due to cardiovascular disease (CVD) compared to the general population. AIM: To evaluate signs of CVD in asymptomatic PWHA using advanced electrocardiography (A-ECG). METHODS: PWHA (n = 29, median [interquartile range] age 57 [47-70] years) and age-matched male controls (n = 29, 59 [48-68] years) were evaluated. Digital resting 12­lead ECGs were retrospectively analysed using both conventional and A-ECG techniques including derived vectorcardiography and waveform complexity. Previously validated multivariate A-ECG scores designed to detect: 1) cardiac disease in general, 2) left ventricular systolic dysfunction (LVSD), 3) coronary artery disease or coronary microvascular disease (CAD/CMVD), or 4) left ventricular hypertrophy defined as left ventricular electrical remodelling (LVH/LVER), were quantified and compared between PWHA and controls. RESULTS: Compared to controls, PWHA had a higher probability of having cardiac disease (median [interquartile range] 84.6 [32.5-99.5] vs. 0.6 [0.2-8.2]%), LVSD (4.1 [1.3-12.9] vs. 0.9 [0.5-3.2]%), CAD/CMVD (84.3 [35.6-96.6] vs. 6.7 [0.8-24.4]%), and LVH/LVER (17 [5/29] vs. 0 [0/29]%). Compared to patients with non-severe HA (n = 20), patients with severe HA (n = 9) showed a non-significant trend towards lower probability of cardiac disease, CAD/CMVD, LVSD and LVH/LVER. CONCLUSION: In PWHA, A-ECG exhibits changes more indicative of overt or subclinical CVD compared to controls, and there is a tendency for lower scores for CVD in patients with severe compared to non-severe HA. These results suggest that PWHA ≥ 40 years could be at higher risk for CVD than age-matched controls and that A-ECG could potentially be used for early detection.

Elective lung resection increases spatial QRS-T angle and QTc interval.

BACKGROUND: Lung resection changes intra-thoracic anatomy, which may affect electrocardiographic results. While postoperative cardiac arrhythmias have been recognized after lung resection, no study has documented changes in vectorcardiographic variables in patients undergoing this surgery. The purpose of this study was to analyse changes in spatial QRS-T angle (spQRS-T) and corrected QT interval (QTc) after lung resection. METHODS: Adult patients undergoing elective lung resection under general anaesthesia were studied. The patients were allocated into four groups: those undergoing (1) left lobectomy (LL); (2) left pneumonectomy (LP); (3) right lobectomy (RL); and (4) right pneumonectomy (RP). The spQRS-T angle and QTc interval were measured one day before surgery (baseline) and 24, 48 and 72 h after surgery. RESULTS: Seventy-one adult patients (47 men and 24 women) aged 47-80 (65 ± 7) years were studied. In the study group as a whole, lung resection was associated with significant increases in spQRS-T (p < 0.001) and QTc (p < 0.05 at 24 and 48 h and p < 0.01 at 72 h). The greatest changes were noted in patients undergoing LP. Postoperative atrial fibrillation (AF) was noted in 6.4% of patients studied, in whom the widest spQRS-T angle and the most prolonged QTc intervals were also noted. CONCLUSIONS: Lung resection widens the spQRS-T angle and prolongs the QTc interval, especially in patients undergoing LP. While postoperative AF was a relatively rare complication after lung resection in this study, it was associated with the widest spQRS-T angles and most prolonged QTc intervals.

The electrical determinants of increased wall thickness and mass in left ventricular hypertrophy.

INTRODUCTION: Left ventricular hypertrophy (LVH), defined as an increased left ventricular mass (LVM), can manifest as increased wall thickness, ventricular dilatation, or both. Existing LVH criteria from the electrocardiogram (ECG) have poor sensitivity. However, it is unknown whether changes in wall thickness and mass, respectively, can be separately detected by the ECG. METHODS: Patients undergoing cardiovascular magnetic resonance and resting 12-lead ECG were included. Exclusion criteria were clinical confounders that might influence the ECG, including myocardial scar. Advanced ECG (A-ECG) analysis included conventional ECG measures and amplitudes, derived vectorcardiographic and polarcardiographic measures, and singular value decomposition of waveform complexity. A-ECG scores for 1) increased LVM index (LVMI), and 2) increased global wall thickness index (GTI) beyond the upper limit of normal in healthy volunteers, respectively, were derived using multivariable logistic regression. The area under the curve (AUC) and its bootstrapped confidence interval (CI) for each score were compared to those of conventional ECG-LVH criteria including Cornell voltage, Cornell product, and Sokolow-Lyon voltage criteria. RESULTS: Out of 485 patients (median [interquartile range] age 51 [38-61] years, 54% female), 51 (11%) had increased LVMI and 65 (13%) had increased GTI. The A-ECG scores for increased LVMI (AUC [95% CI] 0.84 [0.78-0.90]), and increased GTI (0.80 [0.74-0.85]) differed, and had a higher AUC than the conventional ECG-LVH criteria (p < 0.001 for all). CONCLUSIONS: Increased LVMI differed from increased GTI in its electrocardiographic manifestation by A-ECG. New A-ECG scores outperform conventional ECG criteria for LVH in determining increased LVMI and GTI, respectively.