Evrim Şimşek

Introduction: Tricuspid regurgitation (TR) progression is a recognized complication of cardiac implantable electronic device (CIED) implantation, yet its prognostic impact on long‐term clinical outcomes remains incompletely defined. Methods and Results: In this single‐center retrospective cohort, 303 patients undergoing CIED implantation between 2005 and 2023 were followed for a median of 4.8 years. TR severity was assessed echocardiographically at baseline and 12 months. The primary endpoint was TR progression (≥ 1‐grade worsening); secondary endpoints were all‐cause mortality, cardiovascular hospitalization, their composite, and progression to severe TR, analyzed by Kaplan–Meier and Cox regression. TR progressed in 103 patients (34.0%), regressed in 33 (10.9%), and remained stable in 167 (55.1%), a net rightward shift ( p < 0.001). Progression differed by device type ( p = 0.031): among the larger subgroups, VVI‐ICD showed the greatest net progression (31.8% worsened vs. 6.9% improved; p < 0.001) and CRT‐D the highest regression (18.8%). During follow‐up, 67 patients (22.1%) died and 164 (54.1%) were hospitalized. Overall TR progression was not independently associated with mortality (HR 1.118, p = 0.693) but independently predicted cardiovascular hospitalization (HR 1.640, p = 0.003) and the composite endpoint (HR 1.480, p = 0.014). On unadjusted analysis, progression specifically to severe TR ( n = 15) was associated with increased mortality (HR 1.99, p = 0.024) and cardiovascular hospitalization (HR 2.45, p < 0.001). Conclusion: TR progression occurs in approximately one‐third of CIED recipients within the first year and independently predicts cardiovascular hospitalization. Progression to severe TR identifies a higher‐risk subset, supporting routine post‐implant echocardiographic surveillance.

OBJECTIVES: Mitral annular disjunction is a recognized risk factor for malignant ventricular arrhythmias in patients with mitral valve prolapse. This study aimed to evaluate the impact of mitral valve surgery on the burden of supraventricular and ventricular ectopic activity in patients with mitral annular disjunction. METHODS: Data from 32 patients who underwent mitral valve surgery between 2017 and 2024 were retrospectively analysed. The primary end-point was the change in the burden of supraventricular and ventricular ectopy following surgery. The secondary end-point was to assess whether this change differed according to the extent of the mitral annular disjunction distance. RESULTS: The mean age of the patients was 38.8 ± 14 years, and 53.1% were female. The vast majority (96.9%) underwent successful mitral valve repair. The mean cardiopulmonary bypass and aortic cross-clamp times were 133.3 ± 38 min and 95.8 ± 32 min, respectively. Postoperatively, the mean burden of supraventricular ectopy decreased from 13.8% to 3.7%, and ventricular ectopy burden decreased from 7.1% to 2.1%. Among patients with a mitral annular disjunction distance ≥8.5 mm, both supraventricular and ventricular ectopic activity significantly declined. In contrast, for those with a mitral annular disjunction distance <8.5 mm, a significant reduction was observed only in ventricular ectopy, with no statistically significant change in supraventricular ectopy. CONCLUSIONS: Mitral valve surgery is associated with a substantial reduction in both supraventricular and ventricular ectopic activity in patients with mitral annular disjunction. Furthermore, a mitral annular disjunction distance greater than 8.5 mm appears to be a predictor of a more pronounced reduction in arrhythmic burden following surgery.

Background and aims Cardiac implantable electronic devices (CIED) are frequently used in the treatment of arrhythmias. Maintenance of lead position is a key element for proper functioning of the CIEDs. There are two suturing techniques that are commonly used to anchor the leads to pectoral muscle (simple knot and anchor knot techniques). While there is one in vitro study comparing lead stabilizing efficacy of these two techniques, there is no in vivo study in the literature. In this in vivo study, the efficacy of lead stabilization between these two techniques was compared. Methods Twenty rabbits were included in this study, and they were divided into two equal groups. The anchor knot technique was used in one group, whereas the simple knot technique was used in the other group. The rabbits were followed up for 2 weeks and 4 weeks (acute term and chronic term, respectively). At the end of the acute term, the leads were evaluated for spontaneous dislocation and resistance to at least 10 N of traction force. Whether the leads maintained their position in the sleeve was evaluated by measurement. At the end of 4 weeks, in addition to aforementioned criteria, whether necrosis had occurred was evaluated on pectoral muscle biopsy specimens that included the area where suture was taken. Additionally, the two suturing techniques were also compared for procedural time on the last two rabbits of each group. Results Seven and nine rabbits were evaluated for outcomes throughout acute and chronic terms, respectively. Four rabbits died during follow-up, two of which due to anesthetic complications. No lead- or suture-related complications were observed at postmortem examinations of these rabbits. All leads stabilized by using the anchor knot technique maintained their position in the sleeve and were resistant to at least 10 N of traction force in acute and chronic terms. The leads stabilized by the simple knot technique (three rabbits) maintained their position in the acute term, two of them were dislocated under traction and only one of them was found to be partially resistant to at least 10 N of traction force. 0.5 cm of dislocation was observed between that lead and its sleeve after applying traction. Only two leads (50%) stabilized by using the simple knot technique in chronic term remained their position. Lead and sleeve dislocated together in one subject, while the other lead was found separately dislocated from its sleeve. One of the two other leads was resistant to at least 10 N of traction force and that lead remained in stable in sleeve. Muscle biopsy specimens of eight rabbits were evaluated for necrosis. Two of the three samples were found to have necrosis in the simple knot technique group; however, none of the five rabbits in the anchor knot group had necrosis. The time required for the complete stabilization process in the last two rabbits of each suturing technique group was 215 s and 313.5 s on average for simple knot and anchor knot techniques, respectively. Conclusion The anchor knot technique provided more effective mechanical stabilization compared to the simple knot technique in acute and chronic terms. The simple knot technique was found to be associated with an increased risk of necrosis in chronic term. Applying the simple knot technique was faster than the anchor knot technique by only 98.5 s on average. Nevertheless, this advantage of the simple knot technique was not considered to be adequately significant when compared to lead stabilization efficiency of the anchor knot technique. Graphical Abstract

Remote monitoring of patients is of great importance in terms of early diagnosis of diseases and improving people's quality of life. With the rapid development of deep learning techniques, wearable health technologies have leaped forward. This has made the automatic diagnosis even more important. In this study, we provide a deep learning approach for classifying Atrial Fibrillation (AF) arrhythmia that uses a customized wavelet-based convolutional autoencoder (WCAE) model. WCAE is employed as an anomaly detector, which combines the time-frequency domain examination ability of wavelet and the data-driven feature learning capability of convolutional autoencoders. The proposed approach received average scores of 95.45%, 99.99%, 90.90%, and 95.23% for accuracy, precision, recall, and F1, respectively, on a large selection of publicly available datasets. The outcomes of the experiments demonstrate the significance of using deep learning-based models in diagnosing AF. Moreover, it is observed that utilization of wavelet methods along with autoencoder model has a great potential for biomedical signal processing systems.

Despite all the advancements in science, medical knowledge, healthcare, and the healthcare industry, cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide. The main reasons are the inadequacy of preventive health services and delays in diagnosis due to the increasing population, the failure of physicians to apply guide-based treatments, the lack of continuous patient follow-up, and the low compliance of patients with doctors’ recommendations. Artificial intelligence (AI)-based clinical decision support systems (CDSSs) are systems that support complex decision-making processes by using AI techniques such as data analysis, foresight, and optimization. Artificial intelligence-based CDSSs play an important role in patient care by providing more accurate and personalized information to healthcare professionals in risk assessment, diagnosis, treatment optimization, and monitoring and early warning of CVD. These are just some examples, and the use of AI for CVD decision support systems is rapidly evolving. However, for these systems to be fully reliable and effective, they need to be trained with accurate data and carefully evaluated by medical professionals.

Heart Failure (HF) is an important public health problem in Turkey and in the world. Hospitalizations due to HF decompensation are associated with increased mortality. The use of digital technologies, especially wearable technologies, is increasing. As physicians, with the use of these devices, patients could be closely followed up and hospitalization, mortality are tried to be prevented by increased awareness of decomposition before clinical symptoms or at the beginning of symptoms. In this review, digital biomarkers, digital technologies, remote monitoring systems and the evidence supporting their use, artificial intelligence applications and the reasons limiting their use of digital technologies in clinical practice will be discussed.

Background: Digital health technologies (DHTs) have the potential of facilitating both physicians' and patients' lives with regards to the diagnosis, treatment and follow-up of cardiovascular disease. A huge acceleration in relevant research has been noted particularly after the COVID-19 pandemic. Purpose: The goal of this study was to determine the reasons for using DHTs in cardiology, as well as the perceived barriers to its use. Methods: An electronic survey with 43 question multiple-choice questionnaire was conducted between January 10-March 3, 2022. National cardiac society member cardiology fellows in training and specialists were contacted via e-mail (n=2789). Results: 308/2789 (11.04%) subjects responded to the survey (72.40% males, 62.01% aged 30–44 years). 42.53% and 44.81% were affiliated with university hospitals and state hospitals, respectively. 88/297 (29.63%) stated having at least good understanding of DHTs in cardiology. 44.16% utilized smart devices to track their own health status. 117/290 (40.34%) and 193/299 (64.55%) used social media platforms to share medical information with their patients and other physicians, respectively. WhatsApp and Instagram were the most popular platforms for sharing with patients (92/117, 78.63% and 48/117, 41.03%), while WhatsApp and Twitter were the most popular platforms for sharing with other physicians (151/193, 78.24% and 91/193, 47.15%). Considerations and recommendation/utilization patterns of DHTs by physicians are summarized in Table 1. Perceived barriers to the use of DHTs in cardiology is shown on Figure 1 (A: physician-related, B: patient-related, C: technical). Conclusion: Findings suggest that nearly half of the physicians use DHTs to collect their own health data and use social media to disseminate health information. The majority of physicians believe that DHT is beneficial to both themselves and their patients, and that DHT use in cardiology has increased as a result of the COVID-19 pandemic. To overcome the challenges to the use of DHTs in cardiology, a multilayered collaborative effort involving patient and professional organizations, as well as technical stakeholders and lawmakers, is required. Funding Acknowledgement: Type of funding sources: None.

Tr en Amaç: Ani kardiyak ölüm tip 2 Diabetes Mellitus (DM) hastalarında daha sık görülmektedir. Aritmi riskinin belirlenmesi için elektrokardiografide (EKG) repolarizasyonu gösteren QT intervali ve T dalgasının tepesinden sonuna kadar olan süreyi tanımlayan “T wave peak to end time” (Tpe) intervali yararlı olabilmektedir. Bu parametrelerin tip 2 DM hastalarında genel popülasyona göre değişimi fazla çalışılmamıştır. Hastaların hipergilisemik ve normoglisemik dönemlerinde bu parametreleri içeren karşılaştırma ise daha önce yapılmamıştır. Çalışmanın amacı tip 2 DM hastalarında aritmik riskin göstergesi olabilecek QT ve Tpe parametrelerin sağlıklı kontrol grubuyla karşılaştırılması ve hastaların hiperglisemik ve normoglisemik dönemlerinde bu parametrelerdeki değişimin gösterilmesidir. Gereç ve Yöntem: İnsülin infüzyonu başlanan 30 tip 2 DM hastası ile benzer yaş ve cinsiyette 30 sağlıklı birey çalışmaya alınmıştır. DM hastaların insülin infüzyonu öncesi ve sonrası EKG‟leri çekilmiş, QT, Tpe ve kalp hızları ölçülüp kalp hızına göre düzeltilmiş QT (QTc), sırasıyla kalp hızı ve QTc ye göre düzeltilmiş, Tpec ve TpeQTc değerleri hesaplanıp hem kendi aralarında hem de sağlıklı kontrol grubunun ölçümleri ile karşılaştırılmıştır. Bulgular: Hastaların ortalama yaşı 54,2 yıl ve %53,3‟ü kadındı. Hasta grubunda hiperglisemik ve normoglisemik dönemde kontrol grubuna göre kalp hızı daha yüksek, Tpec ve QTc süreleri istatistiksel olarak daha uzundu. Hiperglisemik dönem ile normoglisemik dönem kendi aralarında karşılaştırldığında QTc, Tpe, Tpec, TpeQTc parametrelerinin hepsi hiperglisemik dönemde daha uzun bulundu. (Sırasıyla QTc:45331‟e karşı 43433 p=0,003, Tpe:95,211,9‟a karşı 82,311,8 p<0,001, Tpec:112,518,1‟e karşı 96,416,1 p<0,001, TpeQTc:0,2100,023‟e karşı 0,1900,02 p<0,001) Sonuç: Tip 2 DM hastalarında QTc, Tpec parametreleri sağlıklı kişilere göre uzunken hiperglisemik dönemde bu parametreler normoglisemik döneme göre daha da uzundur. Bu nedenle DM hastaların aritmik riskleri hiperglisemik dönemde daha da yüksek olabilir. Aim: Sudden cardiac death is more common in patients with type 2 diabetes mellitus (DM). Repolarization parameters on electrocardiography (ECG) including the QT and Tpe interval may be useful for determining the arrhythmic risk. Comparison of these parameters in patients with type 2 DM and healthy individuals has not been studied much. Also, the difference between hyper and normoglycemic periods has not been evaluated before.The aim of this study was to compare the QT and Tpe in type 2 DM patients with control group and to show the differences in the hyper and normoglycemic periods. Materials and Methods: Thirty type 2 DM patients needed insulin infusion and 30 healthy individuals of similar age and sex were included in the study. ECGs performed before and after ınsulin infusion. QT, Tpe and heart rates were measured, and QT corrected for heart rate (QTc), Tpe corrected for heart rate (Tpec) and QTc (TpeQTc) values were calculated. Results of the hyper and normoglycemic status and control group were compared. Results: The mean age of the patients was 54.2 years and 53.3% of them were female. Heart rate was higher and Tpec and QTc periods were statistically longer in the both hyper and normoglycemic period compared to the control group. QTc, Tpe, Tpec, TpeQTc parameters were longer in hyperglycemic period than normoglycemic period (QTc:45331 to 43433 p=0.003, Tpe:95.211.9 to 82.311.8 p<0.001, Tpec:112.518.1 to 96.416.1 p <0.001, TpeQTc:0.2100.023 to 0.1900.02 p<0.001). Conclusion: QTc and Tpec parameters were longer in patients with type 2 DM than in healthy subjects, whereas these parameters were longer in hyperglycemic period than in normoglycemic period. Therefore, arrhythmic risks of DM patients may be even higher in the hyperglycemic period.