Explore the vast range of titles available.

Tiagabine is an antiepileptic drug used for the treatment of partial seizures in humans. Recently, this drug has been found useful in several non-epileptic conditions, including anxiety, chronic pain and sleep disorders. Since tachycardia—an impairment of cardiac rhythm due to cardiac ion channel dysfunction—is one of the most commonly reported non-neurological adverse effects of this drug, in the present paper we have undertaken pharmacological and numerical studies to assess a potential cardiovascular risk associated with the use of tiagabine. A chemical interaction of tiagabine with a model of human voltage-gated ion channels (VGICs) is described using the molecular docking method. The obtained in silico results imply that the adverse effects reported so far in the clinical cardiological of tiagabine could not be directly attributed to its interactions with VGICs. This is also confirmed by the results from the isolated organ studies (i.e., calcium entry blocking properties test) and in vivo (electrocardiogram study) assays of the present research. It was found that tachycardia and other tiagabine-induced cardiac complications are not due to a direct effect of this drug on ventricular depolarization and repolarization.

Background Electrocardiographic markers, as surrogates for sympathetic excitotoxicity, are widely predictive of cardiovascular adverse events, but whether these markers can predict postsurgical sepsis (SS) is unclear. Methods We retrospectively analyzed patients who underwent abdominal surgery from March 2013 to May 2023. We collected basic data, comorbidities, blood samples, echocardiology, electrocardiogram, and surgical data, as well as short-term outcome. The primary endpoints were postsurgical SS, in which logistic regression analyses can identify independent risk factors. The optimal cut-off value predictive postsurgical SS both P wave and PR interval were calculated in the receiver operating characteristic curve (ROC). Results A total of 1988 subjects were analyzed, and the incidence of postsurgical SS was 3.8%. The mean age at enrollment was 68.6 ± 7.1 years, and 53.2% of the participants were men. In the ROC analysis, the areas under the curve (AUC) for P wave and PR interval predictive postsurgical SS were 0.615 (95%CI, 0.548–0.683; p  = 0.001) and 0.618 (95%CI, 0.554–0.682; p  = 0.001), respectively. The P wave and PR interval predicted postoperative sepsis with optimal discrimination of 103 and 157 ms, with a sensitivity of 0.744 and 0.419, and a specificity of 0.427 and 0.760. P-wave less than 103 ms or PR interval less than 157 ms associated with a 2.06 or 2.33 fold increase occurred risk postsurgical SS. Conclusions Shorter P-wave and PR intervals were both independently associated with postsurgical SS. These preoperative electrophysiological markers could have potential useful for early recognition of postoperative SS.

Background/Objectives: Epidemiological evidence suggests a protective effect of moderate alcohol consumption on cardiovascular events. However, studies assessing the association between alcohol intake and intima–media thickness (IMT) as a marker of subclinical atherosclerosis have provided inconsistent results. The aim of this analysis of the Stress Atherosclerosis and ECG Study (STRATEGY study) was to investigate the relation between alcohol intake and IMT in a selectively healthy population. Subjects/Methods: In a cross-sectional study, laboratory values, anthropometric data, nutrition habits and physical activity were assessed in 106 men and 107 women, evenly distributed between 30 and 70 years. Carotid IMT was determined by B-mode ultrasonography according to the standardized protocol of the Study of Health in Pomerania. Results: In men, a significant positive correlation between daily alcohol consumption and IMT was observed (P<0.0001), whereas in women the positive correlation was not significant. The type of beverage consumed did not affect this finding. The mean IMT was significantly higher in men with an alcohol intake above the upper limit of 20 g/day than in men with an alcohol intake <20 g/day (P<0.001). According to a stepwise linear regression model adjusted for age, conventional risk factors, nutrition and physical activity, the IMT increases by 0.0253 mm per 21.4 g/day intake of alcohol in men (P<0.05). Conclusions: The STRATEGY study revealed a positive association between alcohol consumption and carotid IMT in healthy men aged 30–70 years. This relationship remained significant after adjustment for nutrition, physical activity, anthropometry and conventional cardiovascular risk factors.

Aims: Feasibility study of accurate three lead ECG recording (Einthoven I, II and III) using an Apple Watch Series 4. Methods: In 50 healthy subjects (18 male; age: 40 ± 12 years) without known cardiac disorders, a 12-lead ECG and three bipolar ECGs, corresponding to Einthoven leads I, II and III were recorded using an Apple Watch Series 4. Einthoven I was recorded with the watch on the left wrist and the right index finger on the crown, Einthoven II with the watch on the left lower abdomen and the right index finger on the crown, Einthoven III with the watch on the left lower abdomen and the left index finger on the crown. Four experienced cardiologists were independently asked to assign the watch ECGs to Einthoven leads from 12-lead ECG for each subject. Results: All watch ECGs showed an adequate signal quality with 134 ECGs of good (89%) and 16 of moderate signal quality (11%). Ninety-one percent of all watch ECGs were assigned correctly to corresponding leads from 12-lead ECG. Thirty-nine subjects (78%) were assigned correctly by all cardiologists. All assignment errors occurred in patients with similar morphologies and amplitudes in at least two of the three recorded leads. Erroneous assignment of all watch ECGs to leads from standard ECG occurred in no patient. Conclusion: Recording of Einthoven leads I-III by a smartwatch is accurate and highly comparable to standard ECG. This might contribute to an earlier detection of cardiac disorders, which are associated with repolarization abnormalities or arrhythmias.

To assess the diagnostic accuracy of the Spandan Lead II smartphone-based electrocardiogram (ECG) device regarding cardiac arrhythmia, compared with that of the only lead II ECG strip from the gold-standard ECG machine (BPL ECG machine) and the diagnosis by a cardiologist. The study, conducted from August 2, 2022, to June 2, 2023, in the local hospital, included 2799 participants aged 20 years and above. This was a single-blinded, cross-sectional study comparing the Spandan ECG device against the Gold Standard ECG and was diagnosed by a cardiologist. Participants referred for ECG testing by a cardiologist were included, and those with a pacemaker and/or ECG artifacts were excluded. To avoid any bias, the diagnosis was blinded to the cardiologist. Sensitivity, specificity, predictive values, F-score, and Matthew's correlation coefficient of the Spandan device were the parameters on which accuracy was studied. Among 2799 participants (843 females, 1,956 males), the Spandan ECG system demonstrated high accuracy compared to the gold standard ECG machine, with sensitivity (95.5%), specificity (96.3%), positive predictive value (93.2%), negative predictive value (97.6%), F-Score (0.94), and a P = .913, for P > .001. It identified all arrhythmias without discrepancies and closely aligned with the gold standard ECG, which had slightly lower performance metrics. The study concluded that the Spandan Lead II ECG system is clinically applicable, especially in resource-limited settings. The Spandan lead II smartphone-based ECG device offers high accuracy in diagnosing cardiac arrhythmias, comparable to standard ECG machines. Its portability, affordability, and ease of use make it a valuable tool for timely diagnosis in almost all clinical and non-clinical settings.

Wearable health monitoring is an emerging technology for continuous monitoring of vital signs including the electrocardiogram (ECG). This signal is widely adopted to diagnose and assess major health risks and chronic cardiac diseases. This paper focuses on reviewing wearable ECG monitoring systems in the form of wireless, mobile and remote technologies related to older adults. Furthermore, the efficiency, user acceptability, strategies and recommendations on improving current ECG monitoring systems with an overview of the design and modelling are presented. In this paper, over 120 ECG monitoring systems were reviewed and classified into smart wearable, wireless, mobile ECG monitoring systems with related signal processing algorithms. The results of the review suggest that most research in wearable ECG monitoring systems focus on the older adults and this technology has been adopted in aged care facilitates. Moreover, it is shown that how mobile telemedicine systems have evolved and how advances in wearable wireless textile-based systems could ensure better quality of healthcare delivery. The main drawbacks of deployed ECG monitoring systems including imposed limitations on patients, short battery life, lack of user acceptability and medical professional’s feedback, and lack of security and privacy of essential data have been also discussed.

ObjectivePatients with suspected acute myocardial infarction (AMI) in the setting of left bundle branch block (LBBB) present an important diagnostic and therapeutic challenge to the clinician.MethodsWe prospectively evaluated the incidence of AMI and diagnostic performance of specific ECG and high-sensitivity cardiac troponin (hs-cTn) criteria in patients presenting with chest discomfort to 26 emergency departments in three international, prospective, diagnostic studies. The final diagnosis of AMI was centrally adjudicated by two independent cardiologists according to the universal definition of myocardial infarction.ResultsAmong 8830 patients, LBBB was present in 247 (2.8%). AMI was the final diagnosis in 30% of patients with LBBB, with similar incidence in those with known LBBB versus those with presumably new LBBB (29% vs 35%, p=0.42). ECG criteria had low sensitivity (1%–12%) but high specificity (95%–100%) for AMI. The diagnostic accuracy as quantified by the receiver operating characteristics (ROC) curve of hs-cTnT and hs-cTnI concentrations at presentation (area under the ROC curve (AUC) 0.91, 95% CI 0.85 to 0.96 and AUC 0.89, 95% CI 0.83 to 0.95), as well as that of their 0/1-hour and 0/2-hour changes, was very high. A diagnostic algorithm combining ECG criteria with hs-cTnT/I concentrations and their absolute changes at 1 hour or 2 hours derived in cohort 1 (45 of 45(100%) patients with AMI correctly identified) showed high efficacy and accuracy when externally validated in cohorts 2 and 3 (28 of 29 patients, 97%).ConclusionMost patients presenting with suspected AMI and LBBB will be found to have diagnoses other than AMI. Combining ECG criteria with hs-cTnT/I testing at 0/1 hour or 0/2 hours allows early and accurate diagnosis of AMI in LBBB.Trial registration numberAPACE: NCT00470587; ADAPT: ACTRN12611001069943; TRAPID-AMI: RD001107;Results.

Background Atrial fibrillation (AF) screening after ischemic stroke or transient ischemic attack (TIA) is given high priority in clinical guidelines. However, patient selection, electrocardiogram (ECG) modality and screening duration remains undecided and current recommendations vary. Methods The aim of this study was to investigate the clinical practice of AF screening after ischemic stroke or TIA at Swedish stroke units. In collaboration with the stakeholders of the Swedish Stroke Register (Riksstroke) a digital survey was drafted, then tested and revised by three stroke consultants. The survey consisted of 17 multiple choice/ free text questions and was sent by e-mail to the medical directors at all stroke units in Sweden. Results All 72 stroke units in Sweden responded to the survey. Most stroke units reported that ≥ 75% of ischemic stroke (69/72 stroke units) or TIA patients (67/72 stroke units), without previously known AF, were screened for AF. Inpatient telemetry ECG was the method of first-choice in 81% of the units, but 7% reported lack of access. A variety of standard monitoring durations were used for inpatient telemetry ECG. The second most common choice was Holter ECG (17%), also with considerable variations in monitoring duration. Other AF screening modalities were used as a first-choice method (handheld and patch ECG) but less frequently. Conclusions Clinical practice for AF screening after ischemic stroke or TIA differed between Swedish stroke units, both in choice of AF screening methods as well as in monitoring durations. There is an urgent need for evidence and evidence-based recommendations in this field. Trial registration Not applicable.

This study aims to present a novel deep learning algorithm for a sliding shock advisory decision during cardiopulmonary resuscitation (CPR) and its performance evaluation as a function of the cumulative hands-off time. We retrospectively used 13,570 CPR episodes from out-of-hospital cardiac arrest (OHCA) interventions reviewed in a period of interest from 30 s before to 10 s after regular analysis of automated external defibrillators (AEDs). Three convolutional neural networks (CNNs) with raw ECG input (duration of 5, 10, and 15 s) were applied for the shock advisory decision during CPR in 26 sequential analyses shifted by 1 s. The start and stop of chest compressions (CC) can occur at arbitrary times in sequential slides; therefore, the sliding hands-off time (sHOT) quantifies the cumulative CC-free portion of the analyzed ECG. An independent test with CPR episodes in 393 ventricular fibrillations (VF), 177 normal sinus rhythms (NSR), 1848 other non-shockable rhythms (ONR), and 3979 asystoles (ASYS) showed a substantial improvement of VF sensitivity when increasing the analysis duration from 5 s to 10 s. Specificity was not dependent on the ECG analysis duration. The 10 s CNN model presented the best performance: 92–94.4% (VF), 92.2–94% (ASYS), 96–97% (ONR), and 98.2–99.5% (NSR) for sliding decision times during CPR; 98–99% (VF), 98.2–99.8% (ASYS), 98.8–99.1 (ONR), and 100% (NSR) for sliding decision times after end of CPR. We identified the importance of sHOT as a reliable predictor of performance, accounting for the minimal sHOT interval of 2–3 s that provides a reliable rhythm detection satisfying the American Heart Association (AHA) standards for AED rhythm analysis. The presented technology for sliding shock advisory decision during CPR achieved substantial performance improvement in short hands-off periods (>2 s), such as insufflations or pre-shock pauses. The performance was competitive despite 1–2.8% point lower ASYS detection during CPR than the standard requirement (95%) for non-noisy ECG signals. The presented deep learning strategy is a basis for improved CPR practices involving both continuous CC and CC with insufflations, associated with minimal CC interruptions for reconfirmation of non-shockable rhythms (minimum hands-off time) and early treatment of VF (minimal pre-shock pauses).