CPSS: Fusing consistency regularization and pseudo-labeling techniques for semi-supervised deep cardiovascular disease detection using all unlabeled electrocardiograms.

BACKGROUND AND OBJECTIVE: Deep learning usually achieves good performance in the supervised way, which requires a large amount of labeled data. However, manual labeling of electrocardiograms (ECGs) is laborious that requires much medical knowledge. Semi-supervised learning (SSL) provides an effective way of leveraging unlabeled data to improve model performance, providing insight for solving this problem. The objective of this study is to improve the performance of cardiovascular disease (CVD) detection by fully utilizing unlabeled ECG. METHODS: A novel SSL algorithm fusing consistency regularization and pseudo-labeling techniques (CPSS) is proposed. CPSS consists of supervised learning and unsupervised learning. For supervised learning, the labeled ECGs are mapped into prediction vectors by the classifier. The cross-entropy loss function is used to optimize the classifier. For unsupervised learning, the unlabeled ECGs are weakly and strongly augmented, and a consistency loss is used to minimize the difference between the classifier's predictions for the two augmentations. Pseudo-labeling techniques include positive pseudo-labeling (PL) and ranking-based negative pseudo-labeling (RNL). PL introduces pseudo-labels for data with high prediction confidence. RNL assigns negative pseudo-labels to the lower-ranked categories in the prediction vectors to leverage data with low prediction confidence. In this study, VGGNet and ResNet are used as classifiers, which are jointly optimized by labeled and unlabeled ECGs. RESULTS: CPSS has been validated on several databases. With the same number of labeled ECGs (10%), it improves the accuracies over pure supervised learning by 13.59%, 4.60%, and 5.38% in the CPSC2018, PTB-XL, and Chapman databases, respectively. CPSS achieves comparable results to the fully supervised method with only 10% of labeled ECGs, which reduces the labeling workload by 90%. In addition, to verify the practicality of CPSS, a cardiovascular disease monitoring system is designed by heterogeneously deploying the trained classifiers on an SoC (system-on-a-chip), which can detect CVD in real time. CONCLUSION: The results of this study indicate that the proposed CPSS can significantly improve the performance of CVD detection using unlabeled ECG, which reduces the burden of ECG labeling in deep learning. In addition, the designed monitoring system makes the proposed CPSS promising for real-world applications.

Early detection of low QRS voltage and its association with mortality in patients with sepsis.

Various electrocardiographic changes occur during sepsis, but data on the clinical importance of a low QRS voltage in sepsis are still limited. We aimed to evaluate the association between low QRS voltage identified early in sepsis and mortality in patients with sepsis. Between September 2019 and December 2020, all consecutive adult patients diagnosed with sepsis in the emergency room or general ward at Samsung Medical Center were enrolled. Patients without a 12-lead electrocardiogram recorded within 48 h of recognition of sepsis were excluded. In 432 eligible patients, 12-lead electrocardiogram was recorded within the median of 24 min from the first recognition of sepsis, and low QRS voltage was identified in 115 (26.6%) patients. The low QRS group showed more severe organ dysfunction and had higher levels of N-terminal pro-brain natriuretic peptide. The hospital mortality was significantly higher in the low QRS voltage group than in the normal QRS voltage group (49.6% vs. 28.1%, p < 0.001). Similarly, among the 160 patients who required intensive care unit admission, significantly more patients in the low QRS group died in the intensive care unit (35.9% vs. 18.2%, p = 0.021). Low QRS voltage was associated with increased hospital mortality in patients with sepsis.

Impact of preanaesthetic electrocardiogram on decision making and modification of anaesthetic protocols in dogs.

BACKGROUND: This retrospective observational study explored the impact of preanaesthetic electrocardiogram (ECG) assessment on preoperative echocardiography requests and modifications to a standardised anaesthetic protocol in healthy dogs. METHODS: A total of 228 healthy dogs with no previously diagnosed heart disease that underwent general anaesthesia at Complutense Veterinary Teaching Hospital from December 2017 to June 2018 were included. Preanaesthetic ECGs were assessed for abnormalities, and the findings were documented. The number of dogs requiring echocardiography, based on ECG findings, and the echocardiography results were recorded. All anaesthesia-related decisions were documented. RESULTS: Overall, 72 dogs (31.6%) exhibited ECG abnormalities. Echocardiography was requested for five dogs (2.2%). The anaesthetic protocol was changed in 11 dogs (15.3% of those with ECG abnormalities). P wave disturbances, ventricular premature complexes and impulse conduction issues were abnormalities that prompted echocardiography. Bradycardia and electrical impulse conduction abnormalities influenced protocol modifications. LIMITATIONS: The limited sample size meant that it was not possible to investigate potential correlations between demographics and ECG alterations. CONCLUSIONS: Preanaesthetic ECG screening was useful for promoting echocardiography and influencing anaesthesia plans in a subset of dogs. Despite this, further assessment of the impact of routine use of non-targeted preoperative ECG on anaesthesia-related outcomes is warranted.

Electrophysiological and biochemical effect of zinc oxide nanoparticles on heart functions of male Wistar rats.

Zinc oxide nanoparticles (ZnO NPs) are one of the most abundantly used nanomaterials in cosmetics and topical products, and nowadays, they are explored in drug delivery and tissue engineering. Some recent data evidenced that they are responsible for cardiotoxic effects and systemic toxicity. The present study aimed to investigate the toxic effect of ZnO NPs (39 nm) on the heart of Wistar rats and to perform a dose-response relationship using three different dose levels (25, 50, 100 mg/kg bw) of ZnO NPs on the electrocardiogram (ECG) readings, the levels of biochemical function parameters of heart, and the oxidative stress and antioxidant biomarkers. Furthermore, zinc concentration level and histopathological examination of heart tissues were determined. ZnO NPs showed a dose-dependent effect, as the 100 mg/kg bw ZnO NPs treated group showed the most significant changes in ECGs parameters: R-R distance, P-R interval, R and T amplitudes, and increased levels of heart enzymes Creatine Kinase- MB (CK-MB) and Lactate dehydrogenase (LDH). On the other hand, elevated zinc concentration levels, oxidative stress biomarkers MDA and NO, and decreased GSH levels were found also in a dose-dependent manner, the results were supported by impairment in the histopathological structure of heart tissues. While the dose of 100 mg/kg bw of ZnO bulk group showed no significant effects on heart function. The present study concluded that ZnO NPs could induce cardiac dysfunctions and pathological lesions mainly in the high dose.

Exploratory analysis of predictors of ventricular aneurysm in a cohort of 291 patients with acute myocardial infarction.

OBJECTIVE: In this study, we explored the determinants of ventricular aneurysm development following acute myocardial infarction (AMI), thereby prompting timely interventions to enhance patient prognosis. METHODS: In this retrospective cohort analysis, we evaluated 297 AMI patients admitted to the First People's Hospital of Changzhou. The study was structured as follows. Comprehensive baseline data collection included hematological evaluations, ECG, echocardiography, and coronary angiography upon admission. Within 3 months post-AMI, cardiac ultrasounds were administered to detect ventricular aneurysm development. Univariate and multivariate logistic regression analysis were employed to pinpoint the determinants of ventricular aneurysm formation. Subsequently, a predictive model was formulated for ventricular aneurysm post-AMI. Moreover, the diagnostic efficacy of this model was appraised using the ROC curves. RESULTS: In our analysis of 291 AMI patients, spanning an age range of 32-91 years, 247 were male (84.9%). At the conclusion of a 3-month observational period, the cohort bifurcated into two subsets: 278 patients without ventricular aneurysm and 13 with evident ventricular aneurysm. Distinguishing features of the ventricular aneurysm subgroup were markedly higher values for age, B-type natriuretic peptide(BNP), Left atrium(LA), Left ventricular end-diastolic dimension (LEVDD), left ventricular end systolic diameter (LVEWD), E-wave velocity (E), Left atrial volume (LAV), E/A ratio (E/A), E/e ratio (E/e), ECG with elevated adjacent four leads(4 ST-Elevation), and anterior wall myocardial infarction(AWMI) compared to their counterparts (p < 0.05). Among the singular predictive factors, total cholesterol (TC) emerged as the most significant predictor for ventricular aneurysm development, exhibiting an AUC of 0.704. However, upon crafting a multifactorial model that incorporated gender, TC, an elevated ST-segment in adjacent four leads, and anterior wall infarction, its diagnostic capability: notably surpassed that of the standalone TC, yielding an AUC of 0.883 (z = -9.405, p = 0.000) as opposed to 0.704. Multivariate predictive model included gender, total cholesterol, ST elevation in 4 adjacent leads, anterior myocardial infarction, the multivariate predictive model showed better diagnostic efficacy than single factor index TC (AUC: 0. 883 vs. 0.704,z =-9.405, p = 0.000), it also improved predictive power for correctly reclassifying ventricular aneurysm occurrence in patients with AMI, NRI = 28.42% (95% CI: 6.29-50.55%; p = 0.012). Decision curve analysis showed that the use of combination model had a positive net benefit. CONCLUSION: Lipid combined with ECG model after myocardial infarction could be used to predict the formation of ventricular aneurysm and aimed to optimize and adjust treatment strategies.

Effects of baroreflex activation therapy on cardiac function and morphology.

AIMS: Arterial hypertension (aHTN) plays a fundamental role in the pathogenesis and prognosis of heart failure with preserved ejection fraction (HFpEF). The risk of heart failure increases with therapy-resistant arterial hypertension (trHTN), defined as inadequate blood pressure (BP) control ≥140/90 mmHg despite taking ≥3 antihypertensive medications including a diuretic. This study investigates the effects of the BP lowering baroreflex activation therapy (BAT) on cardiac function and morphology in patients with trHTN with and without HFpEF. METHODS: Sixty-four consecutive patients who had been diagnosed with trHTN and received BAT implantation between 2012 and 2016 were prospectively observed. Office BP, electrocardiographic and echocardiographic data were collected before and after BAT implantation. RESULTS: Mean patients' age was 59.1 years, 46.9% were male, and mean body mass index (BMI) was 33.2 kg/m2. The prevalence of diabetes mellitus was 38.8%, atrial fibrillation was 12.2%, and chronic kidney disease (CKD) stage ≥3 was 40.8%. Twenty-eight patients had trHTN with HFpEF, and 21 patients had trHTN without HFpEF. Patients with HFpEF were significantly older (64.7 vs. 51.6 years, P < 0.0001), had a lower BMI (30.0 vs. 37.2 kg/m2, P < 0.0001), and suffered more often from CKD-stage ≥3 (64 vs. 20%, P = 0.0032). After BAT implantation, mean office BP dropped in patients with and without HFpEF (from 169 ± 5/86 ± 4 to 143 ± 4/77 ± 3 mmHg [P = 0.0019 for systolic BP and 0.0403 for diastolic BP] and from 170 ± 5/95 ± 4 to 149 ± 6/88 ± 5 mmHg [P = 0.0019 for systolic BP and 0.0763 for diastolic BP]), while a significant reduction of the intake of calcium-antagonists, α2-agonists and direct vasodilators, as well as a decrease in average dosage of ACE-inhibitors and α2-agonists could be seen. Within the study population, a decrease in heart rate from 74 ± 2 to 67 ± 2 min-1 (P = 0.0062) and lengthening of QRS-time from 96 ± 3 to 106 ± 4 ms (P = 0.0027) and QTc-duration from 422 ± 5 to 432 ± 5 ms (P = 0.0184) were detectable. The PQ duration was virtually unchanged. In patients without HF, no significant changes of echocardiographic parameters could be seen. In patients with HFpEF, posterior wall diameter decreased significantly from 14.0 ± 0.5 to 12.7 ± 0.3 mm (P = 0.0125), left ventricular mass (LVM) declined from 278.1 ± 15.8 to 243.9 ± 13.4 g (P = 0.0203), and e' lateral increased from 8.2 ± 0.4 to 9.0 ± 0.4 cm/s (P = 0.0471). CONCLUSIONS: BAT reduced systolic and diastolic BP and was associated with morphological and functional improvement of HFpEF.

Certain investigation on hybrid neural network method for classification of ECG signal with the suitable a FIR filter.

The Electrocardiogram (ECG) records are crucial for predicting heart diseases and evaluating patient's health conditions. ECG signals provide essential peak values that reflect reliable health information. Analyzing ECG signals is a fundamental technique for computerized prediction with advancements in Very Large-Scale Integration (VLSI) technology and significantly impacts in biomedical signal processing. VLSI advancements focus on high-speed circuit functionality while minimizing power consumption and area occupancy. In ECG signal denoising, digital filters like Infinite Impulse Response (IIR) and Finite Impulse Response (FIR) are commonly used. The FIR filters are preferred for their higher-order performance and stability over IIR filters, especially in real-time applications. The Modified FIR (MFIR) blocks were reconstructed using the optimized adder-multiplier block for better noise reduction performance. The MIT-BIT database is used as reference where the noises are filtered by the MFIR based on Optimized Kogge Stone Adder (OKSA). Features are extracted and analyzed using Discrete wavelet transform (DWT) and Cross Correlation (CC). At this modern era, Hybrid methods of Machine Learning (HMLM) methods are preferred because of their combined performance which is better than non-fused methods. The accuracy of the Hybrid Neural Network (HNN) model reached 92.3%, surpassing other models such as Generalized Sequential Neural Networks (GSNN), Artificial Neural Networks (ANN), Support Vector Machine with linear kernel (SVM linear), and Support Vector Machine with Radial Basis Function kernel (SVM RBF) by margins of 3.3%, 5.3%, 23.3%, and 24.3%, respectively. While the precision of the HNN is 91.1%, it was slightly lower than GSNN and ANN but higher than both SVM linear and SVM -RBF. The HNN with various features are incorporated to improve the ECG classification. The accuracy of the HNN is switched to 95.99% when the DWT and CC are combined. Also, it improvises other parameters such as precision 93.88%, recall is 0.94, F1 score is 0.88, Kappa is 0.89, kurtosis is 1.54, skewness is 1.52 and error rate 0.076. These parameters are higher than recently developed models whose algorithms and methods accuracy is more than 90%.

Prolonged ventricular repolarization associated with mild cognitive impairment and white matter hyperintensities: a cross-sectional study.

Prolonged ventricular repolarization has been associated with cardiovascular disease. We sought to investigate the association of prolonged ventricular repolarization with mild cognitive impairment (MCI) and the potential underlying neuropathological mechanisms in older adults. This cross-sectional study included 4328 dementia-free participants (age ≥ 65 years; 56.8% female) in the baseline examination of the Multidomain INterventions to delay dementia and Disability in rural China; of these, 989 undertook structural brain magnetic resonance imaging (MRI) scans. QT, QTc, JT, JTc, and QRS intervals were derived from 12-lead electrocardiograph. MCI, amnestic MCI (aMCI), and non-amnestic MCI (naMCI) were defined following the Petersen's criteria. Volumes of gray matter (GM), white matter, cerebrospinal fluid, total white matter hyperintensities (WMH), periventricular WMH (PWMH), and deep WMH (DWMH) were automatically estimated. Data were analyzed using logistic and general linear regression models. Prolonged QT, QTc, JT, and JTc intervals were significantly associated with an increased likelihood of MCI and aMCI, but not naMCI (p < 0.05). In the MRI subsample, QT, QTc, JT, and JTc intervals were significantly associated with larger total WMH and PWMH volumes (p < 0.05), but not with DWMH volume. Statistical interactions were detected, such that prolonged QT and JT intervals were significantly associated with reduced GM volume only among participants with coronary heart disease or without APOE ε4 allele (p < 0.05). Prolonged ventricular repolarization is associated with MCI and cerebral microvascular lesions in a general population of older adults. This underlies the importance of cognitive assessments and brain MRI examination among older adults with prolonged QT interval.

Case report: Phosphoinositide 3-kinase inhibitor with fulvestrant in a patient with ER+/HER2- metastatic breast carcinoma induced fatal arrhythmias: a preventable event?

Phosphoinositide 3-kinase (PI3K) inhibitors have shown synergistic anticancer effects with endocrine therapy against ER+/PIK3CA-mutated breast cancer. PI3K inhibitors for cancer therapy are becoming more common. There is an increasing need to understand their cardiac adverse events. In this report, we describe the features of near-fatal mixed arrhythmias in a patient who was undergoing a phase Ib clinical study of PI3Kα inhibitor with fulvestrant. Subsequently, the patient survived by cardiopulmonary resuscitation and therefore did not die. This case highlights that PI3K inhibitors can induce QT/QTc prolongation and predispose patients to TdP. The combination of QT/QTc prolongation in combination with prolonged cardiac repolarization, such as an AV block during treatment with PI3Kα inhibitor, may aggravate the occurrence of TdP. It is likely to be a safer strategy to adjust the standard of discontinuing drugs and continuing drugs (QTc interval was <500 and <60 ms at baseline) or choose other types of alternative treatment options. This report provided some ideas for clinicians to identify early and prevent the occurrence of fatal arrhythmias during anticancer treatment.

Pediatric Electrocardiogram-Based Deep Learning to Predict Secundum Atrial Septal Defects.

Secundum atrial septal defect (ASD2) detection is often delayed, with the potential for late diagnosis complications. Recent work demonstrated artificial intelligence-enhanced ECG analysis shows promise to detect ASD2 in adults. However, its application to pediatric populations remains underexplored. In this study, we trained a convolutional neural network (AI-pECG) on paired ECG-echocardiograms (≤ 2 days apart) to detect ASD2 from patients ≤ 18 years old without major congenital heart disease. Model performance was evaluated on the first ECG-echocardiogram pair per patient for Boston Children's Hospital internal testing and emergency department cohorts using area under the receiver operating (AUROC) and precision-recall (AUPRC) curves. The training cohort comprised of 92,377 ECG-echocardiogram pairs (46,261 patients; median age 8.2 years) with an ASD2 prevalence of 6.7%. Test groups included internal testing (12,631 patients; median age 7.4 years; 6.9% prevalence) and emergency department (2,830 patients; median age 7.5 years; 4.9% prevalence) cohorts. Model performance was higher in the internal test (AUROC 0.84, AUPRC 0.46) cohort than the emergency department cohort (AUROC 0.80, AUPRC 0.30). In both cohorts, AI-pECG outperformed ECG findings of incomplete right bundle branch block. Model explainability analyses suggest high-risk limb lead features include greater amplitude P waves (suggestive of right atrial enlargement) and V1 RSR' (suggestive of RBBB). Our findings demonstrate the promise of AI-pECG to inexpensively screen and/or detect ASD2 in pediatric patients. Future multicenter validation and prospective trials to inform clinical decision making are warranted.

pECGreview: Assessment of a Novel Tool to Evaluate the Accuracy of Pediatric ECG Interpretation Skills.

The skill of interpretation of the electrocardiogram (ECG) remains poor despite existing educational initiatives. We sought to evaluate the validity of using a subjective scoring system to assess the accuracy of ECG interpretations submitted by pediatric cardiology fellows, trainees, and faculty to the Pediatric ECG Review (pECGreview), a web-based ECG interpretation training program. We conducted a retrospective, cross-sectional study of responses submitted to pECGreview. ECG interpretations were assessed independently by four individuals with a range of experience. Accuracy was assessed using a 3-point scale: 100% for generally correct interpretations, 50% for over- or underdiagnosis of minor ECG abnormalities, and 0% for over- or underdiagnosis of major ECG abnormalities. Inter-rater agreement was assessed using expanded Bland-Altman plots, Pearson correlation coefficients, and Intraclass Correlation Coefficients (ICC). 1460 ECG interpretations by 192 participants were analyzed. 107 participants interpreted at least five ECGs. The mean accuracy score was 76.6 ± 13.7%. Participants were correct in 66.1 ± 5.1%, had minor over- or underdiagnosis in 21.5 ± 4.6% and major over- or underdiagnosis in 12.3 ± 3.9% of interpretations. Validation of agreement between evaluators demonstrated limits of agreement of 11.3%. Inter-rater agreement exhibited consistent patterns (all correlations ≥ 0.75). Absolute agreement was 0.74 (95% CI 0.69-0.80), and average measures agreement was 0.92 (95% CI 0.89-0.94). Accuracy score analysis of as few as five ECG interpretations submitted to pECGreview yielded good inter-rater reliability for assessing and ranking ECG interpretation skills in pediatric cardiology fellows in training.

Acceleration index predicts efficacy of orthostatic training on postural orthostatic tachycardia syndrome in children.

The objective of this study was to examine the utility of the acceleration index observed in an electrocardiogram (ECG) for the prediction of the effectiveness of orthostatic training in pediatric patients diagnosed with postural orthostatic tachycardia syndrome (POTS). This investigation focused on children diagnosed with POTS and undergoing orthostatic training at the Department of Pediatrics of Peking University First Hospital from January 2012 to October 2022. Specifically, patients hospitalized from January 2012 to December 2019 were included in the training set (54 cases), while those hospitalized from January 2020 to October 2022 were included in the external validation set (37 cases). All children received a 3-month orthostatic training, and the baseline symptom score (SS) was calculated in agreement with the pretreatment orthostatic intolerance symptom frequency. Additionally, we determined post-treatment SS during follow-up via telephone after the 3-month treatment. Children with a decrease in post-treatment SS by ≥ 50% of the baseline were considered as responders; otherwise, they were considered as non-responders. Demographic data (age, sex, and body mass index), hemodynamic parameters (supine blood pressure, time to achieve a positive standing test, maximum increase in heart rate during the standing test, maximal heart rate reached during the standing test, and blood pressure at the point of maximal heart rate during the standing test), and electrocardiographic parameters (RR interval in the supine position, shortest RR interval in the upright position, and acceleration index) were collected from all the children prior to treatment. Univariate and multivariate regression analysis were conducted to investigate factors associated with the efficacy of orthostatic training. The predictive value of these indicators for the therapeutic effectiveness of orthostatic training in children with POTS was evaluated using receiver operating characteristic (ROC) analysis, and the indicators were validated using the validation set. Among the 54 children in the training set, 28 responded to orthostatic training, and 26 were nonresponsive. Compared with the non-responders, the responders demonstrated a significant reduction in acceleration index (P < 0.01). The ROC curve for the predictive value of the acceleration index exhibited an area under the curve = 0.81 (95% confidence interval: 0.685-0.926). With the acceleration index threshold < 27.93%, the sensitivity and specificity in the prediction of orthostatic training efficacy among children with POTS were 85.7% and 69.2%, respectively. The external validation results demonstrated that using acceleration index < 27.93% as the threshold, the sensitivity, specificity, and accuracy of predicting orthostatic training efficacy among children with POTS were 89.5%, 77.8%, and 83.8%, respectively. CONCLUSIONS: Electrocardiographic acceleration index can be used to predict the effectiveness of orthostatic training in treating children with POTS. WHAT IS KNOWN: • Postural orthostatic tachycardia syndrome (POTS) is a chronic orthostatic intolerance involving multiple mechanisms. Autonomic dysfunction is one of the main mechanisms of POTS in children and could be treated with orthostatic training. • In order to improve the efficacy of orthostatic training in children with POTS, it is particularly important to identify the patients with autonomic dysfunction as the main mechanism before the treatment. WHAT IS NEW: • We found acceleration index of the electrocardiogram (ECG) can be used as a satisfactory index to predict the efficacy of orthostatic training in the treatment of POTS in children. • Using the acceleration index to predict the efficacy of orthostatic training on POTS in children is easy to be popularized in hospitals at all levels because it is non-invasive, convenient, and not expensive.

Pulmonary embolism in patients with chronic coronary syndrome masquerading as acute coronary syndrome: a case report and literature review.

BACKGROUND: Pulmonary embolisms (PEs) exhibit clinical features similar to those of acute coronary syndrome (ACS), including electrocardiographic abnormalities and elevated troponin levels, which frequently lead to misdiagnoses in emergency situations. CASE PRESENTATION: Here, we report a case of PE coinciding with chronic coronary syndrome in which the patient's condition was obscured by symptoms mimicking ACS. A 68-year-old female with syncope presented to the hospital. Upon admission, she was found to have elevated troponin levels and an electrocardiogram showing ST-segment changes across multiple leads, which initially led to a diagnosis of ACS. Emergency coronary arteriography revealed occlusion of the posterior branches of the left ventricle of the right coronary artery, but based on the complexity of the intervention, the occlusion was considered chronic rather than acute. On the 3rd day after admission, the patient experienced recurrent chest tightness and shortness of breath, which was confirmed as acute PE by emergency computed tomography pulmonary angiography. Following standardized anticoagulation treatment, the patient improved and was subsequently discharged. CONCLUSIONS: This case report highlights the importance of recognizing the nonspecific features of PE. Clinicians should be vigilant when identifying other clinical features that are difficult to explain accompanying the expected disease, and it is necessary to carefully identify the causes to prevent missed diagnoses or misdiagnoses.

Impact of baseline ECG characteristics on changes in cardiac biomarkers and echocardiographic metrices after acute myocardial infarction treated with Empagliflozin.

The EMMY trial was a multicentre, investigator-initiated, placebo-controlled, double-blind trial, which enrolled 476 patients immediately following AMI and the first study demonstrating a significant reduction in NT-proBNP-levels as well as significant improvements in cardiac structure and function in patients after acute myocardial infarction treated with empagliflozin vs. placebo. However, hardly any data are available investigating the prognostic role of baseline electrocardiogram metrics in SGLT2-inhibitor-treated patients. This post-hoc analysis investigated the association of baseline ECG metrics collected in one centre of the trial (181 patients) with changes in structural and functional cardiac parameters as well as cardiac biomarkers in response to Empagliflozin treatment. A total of 181 patients (146 men; mean age 58 ± 14 years) were included. Median PQ-interval was 156 (IQR 144-174) milliseconds (ms), QRS width 92 (84-98) ms, QTc interval 453 (428-478) ms, Q-wave duration 45 (40-60) ms, Q-wave amplitude 0.40 (0.30-0.70) millivolt (mV), and heart rate was 71 (64-85) bpm. For functional cardiac parameters (LVEF and E/e') of the entire cohort, a greater decrease of E/e' from baseline to week 26 was observed in shorter QRS width (P = 0.005).Structural cardiac endpoints were only found to have a significant positive correlation between LVEDD and Q wave duration (P = 0.037). Higher heart rate was significantly correlated with better response in LVEF (P = 0.001), E/e' (P = 0.021), and NT-proBNP (P = 0.005). Empagliflozin-treatment showed no interaction with the results. Baseline ECG characteristics post AMI are neither predictive for beneficial NTproBNP effects of Empagliflozin post AMI, nor for functional or structural changes within 26 weeks post AMI.

Diagnostic accuracy of artificial intelligence in detecting left ventricular hypertrophy by electrocardiograph: a systematic review and meta-analysis.

Several studies suggested the utility of artificial intelligence (AI) in screening left ventricular hypertrophy (LVH). We hence conducted systematic review and meta-analysis comparing diagnostic accuracy of AI to Sokolow-Lyon's and Cornell's criteria. Our aim was to provide a comprehensive overview of the newly developed AI tools for diagnosing LVH. We searched MEDLINE, EMBASE, and Cochrane databases for relevant studies until May 2023. Included were observational studies evaluating AI's accuracy in LVH detection. The area under the receiver operating characteristic curves (ROC) and pooled sensitivities and specificities assessed AI's performance against standard criteria. A total of 66,479 participants, with and without LVH, were included. Use of AI was associated with improved diagnostic accuracy with summary ROC (SROC) of 0.87. Sokolow-Lyon's and Cornell's criteria had lower accuracy (0.68 and 0.60). AI had sensitivity and specificity of 69% and 87%. In comparison, Sokolow-Lyon's specificity was 92% with a sensitivity of 25%, while Cornell's specificity was 94% with a sensitivity of 19%. This indicating its superior diagnostic accuracy of AI based algorithm in LVH detection. Our study demonstrates that AI-based methods for diagnosing LVH exhibit higher diagnostic accuracy compared to conventional criteria, with notable increases in sensitivity. These findings contribute to the validation of AI as a promising tool for LVH detection.

Comparison of electrocardiogram and blood pressure recording methods in non-rodent toxicology studies: A retrospective analysis.

Our study retrospectively examines 51 non-rodent general toxicology studies conducted over the past 8 years to ascertain the influence of recording methodologies on baseline cardiovascular (CV) parameters and statistical sensitivity. Specifically, our work aims to evaluate the frequency of cardiovascular parameter recording categorized by therapeutic modality and study type, to assess the variability in these parameters based on measurement techniques, and to determine the sample sizes needed for detecting relevant changes in heart rate (HR), blood pressure (BP), and QTc interval in non-human primate (NHP) studies. Results indicate that electrocardiogram (ECG) measurements in dogs and NHP were recorded in 63% of studies, combined with BP recording in 18% of studies, while BP was never recorded alone. Trend analysis reveals a decline in the utilisation of restraint-based methods for ECG measurements post-2017, to the benefit of telemetry-based recordings, particularly Jacketed External Telemetry (JET). There was a marked difference in baseline values, with restraint-based methods showing significantly higher HR and QTc values compared to JET, likely linked to animal stress. Further analysis suggests an unrealistic and unethical sample size requirement in NHP studies for detecting biologically meaningful CV parameter changes using restraint-based methods, while JET methods necessitate significantly smaller sample sizes. This retrospective study indicates a notable shift from snapshots short-duration, restraint-based methods towards telemetry approaches over the recent years, especially with an increased usage of implanted telemetry. The transition contributes to potential consensus within industry or regulatory frameworks for optimal practices in assessing ECG, HR, and BP in general toxicology studies.

Newborn heart rate monitoring methods at birth and clinical outcomes: A systematic review.

Aim: Compare heart rate assessment methods in the delivery room on newborn clinical outcomes. Methods: A search of Medline, SCOPUS, CINAHL and Cochrane was conducted between January 1, 1946, to until August 16, 2023. (CRD 42021283438) Study Selection was based on predetermined criteria. Reviewers independently extracted data, appraised risk of bias and assessed certainty of evidence. Results: Two randomized controlled trials involving 91 newborns and 1 nonrandomized study involving 632 newborns comparing electrocardiogram (ECG) to auscultation plus pulse oximetry were included. No studies were found that compared any other heart rate measurement methods and reported clinical outcomes. There was no difference between the ECG and control group for duration of positive pressure ventilation, time to heart rate ≥ 100 beats per minute, epinephrine use or death before discharge. In the randomized studies, there was no difference in rate of tracheal intubation [RR 1.34, 95% CI (0.69-2.59)]. No participants received chest compressions. In the nonrandomized study, fewer infants were intubated in the ECG group [RR 0.75, 95% CI (0.62-0.90)]; however, for chest compressions, benefit or harm could not be excluded. [RR 2.14, 95% (CI 0.98-4.70)]. Conclusion: There is insufficient evidence to ascertain clinical benefits or harms associated with the use of ECG versus pulse oximetry plus auscultation for heart rate assessment in newborns in the delivery room.