AI techniques have recently been put under the spotlight for analyzing electrocardiograms (ECGs). However, the performance of AI-based models relies on the accumulation of large-scale labeled datasets, which is challenging. To increase the performance of AI-based models, data augmentation (DA) strategies have been developed recently. The study presented a comprehensive systematic literature review of DA for ECG signals. We conducted a systematic search and categorized the selected documents by AI application, number of leads involved, DA method, classifier, performance improvements after DA, and datasets employed. With such information, this study provided a better understanding of the potential of ECG augmentation in enhancing the performance of AI-based ECG applications. This study adhered to the rigorous PRISMA guidelines for systematic reviews. To ensure comprehensive coverage, publications between 2013 and 2023 were searched across multiple databases, including IEEE Explore, PubMed, and Web of Science. The records were meticulously reviewed to determine their relevance to the study’s objective, and those that met the inclusion criteria were selected for further analysis. Consequently, 119 papers were deemed relevant for further review. Overall, this study shed light on the potential of DA to advance the field of ECG diagnosis and monitoring.

Mitochondrial disorders are a clinically, biochemically and genetically heterogeneous group of multi-system diseases, with an unmet medical need for treatment. KH176 is an orally bio-available small molecule under development for the treatment of mitochondrial(−related) diseases. The compound is a member of a new class of drugs, acting as a potent intracellular redox-modulating agent essential for the control of oxidative and redox pathologies. The aim of this randomized, placebo controlled, double-blinded phase 1 study was to test safety, tolerability and pharmacokinetics of single and multiple doses of KH176 in healthy male volunteers. Putative effects on redox related biomarkers were explored. KH176 was well tolerated up to and including a single dose of 800 mg and multiple doses of 400 mg b.i.d. for 7 Days. However, when the QT interval was corrected for heart rate, administration of single doses of 800 and 2000 mg and at a multiple dose of 400 mg KH176 had marked effects. Post-hoc analysis of the ECGs showed clear changes in cardiac electrophysiology at single doses of 800 and 2000 mg and multiple doses of 400 mg b.i.d.. At lower doses, detailed ECG analysis showed no changes in electrophysiology compared to placebo. Exposure-response modelling of the cardiac intervals revealed an exposure range of KH176 without effects on cardiac conduction and provided a threshold of 1000 ng/mL above which changes in intervals could occur. After single- and multiple-dose administration, the pharmacokinetics of KH176 was more than dose proportional. KH176 accumulated to a small extent and food only slightly affected the pharmacokinetics of KH176, which was considered clinically irrelevant. Renal excretion of unchanged KH176 and its metabolite represents a minor pathway in the elimination of KH176. As expected in healthy volunteers no effects on redox biomarkers were observed. The study deemed that KH176 is well tolerated up to single doses of 800 mg and multiple doses of 400 mg b.i.d. and has a pharmacokinetic profile supportive for a twice daily dosing. Only at high doses, KH176 causes clinically relevant changes in cardiac electrophysiology, including prolonged QTc interval and changes in T wave morphology. A Phase 2 clinical trial (100 mg b.i.d., orally) has been conducted recently of which the final results are expected Q1 2018. NCT02544217 . Registered. ISRCTN43372293 . Retrospectively registered.

Background: Continuous 12‐lead ECG monitoring (Holter) in early‐phase pharmaceutical studies is today widely used as an ideal platform to extract discrete ECGs for analysis. The extraction process is typically performed manually by trained readers using commercial Holter processing systems. Methods: Antares, a novel method for automatic 12‐lead extraction from continuous Holter recordings applying minimal noise criteria and heart‐rate stability conditions is presented. A set of 12‐lead Holter recordings from healthy subjects administered with sotalol is used to compare ECG extractions at fixed time points with ECG extractions generated by Antares optimizing noise and heart rate inside 5 minute windows centered around each expected time point of interest. Results: Global, low‐ and high‐frequency noise content of extracted ECGs was significantly reduced via optimized approach by Antares. Heart rate was also slightly reduced (from 69 ± 13 to 64 ± 13 bpm, P < 0.05). Similarly, the corrected QT interval from optimized extractions was significantly reduced (QTcB from 414 ± 32 to 402 ± 30 ms, P < 0.05). Using only baseline data, and after adjusting for intersubject variability, the standard deviation (SD) of QT intervals was highly reduced with optimized extraction (SD of QTcF from 11 ± 8 to 7 ± 2 ms, P < 0.05). Conclusions: Extraction of discrete 12‐lead ECG strips from continuous Holter generates less noisy and more stable ECGs leading to more robust QTc data, thereby potentially facilitating the assessment of ECG effects on clinical trials.