Digital Technologies in Heart Failure Management.

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.

Perspectives on the Use of Digital Health Technologies in Cardiology Among Specialists from an ESC Member Country: Results from a Survey.

OBJECTIVE: In this study, we aimed to identify the reasons for and perceived challenges associated with the use of digital health technologies (DHT) in cardiology. METHOD: We distributed an online survey to Turkish Society of Cardiology member cardiologists (n = 2789) between January 10 and March 3, 2022. RESULTS: A total of 308 subjects responded (27.6% females, 62.0% aged 30-44 years). Of these, 42.5% worked at university hospitals, and 44.8% at state hospitals. Smart devices were used by 44.2% (136/308) for personal health monitoring. Additionally, 40.3% (117/290) used social media to provide medical information to patients, while 64.6% (193/299) did so for communication with other physicians. The self-reported recommendation frequencies of wearables, cardiac implantable electronic device telemonitorization, mobile health applications, and teleconsultation/televisit technologies were lower than the proportion of respondents who found DHT beneficial for both patients and physicians. The most frequently mentioned barriers for physicians were increased work burden and responsibilities (78.8%, 193/245), lack of financial compensation (66.9%, 164/245), and lack of relevant training (66.5%, 163/245). For patients, low technological adaptability (81.6%, 200/245), low health literacy (80.4%, 197/245), and low affordability (79.6%, 195/245) were the most frequently mentioned barriers. Additionally, the cost of technologies (69.4%, 170/245), concerns regarding data privacy and security (57.6%, 141/245), and data storage challenges (48.2%, 118/245) were the most significant technical impediments. CONCLUSION: The findings suggest that although the majority of physicians believe DHT to be beneficial for both themselves and their patients, the frequency of recommendations to patients remains low. A large-scale joint effort is required to address these issues and facilitate the integration of DHT into clinical practice.

Artificial Intelligence-Based Clinical Decision Support Systems in Cardiovascular Diseases.

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.

Evaluation of Intermountain Risk Score for Short- and Long-Term Mortality in ST Elevation Myocardial Infarction Patients.

The aim of this study was to examine the Intermountain Risk Score (IMRS) for short- and long-term mortality in ST elevation myocardial infarction (STEMI) patients and compare it with the well-known risk scores, such as the Thrombolysis in Myocardial Infarction (TIMI) and the Global Registry of Acute Coronary Events (GRACE). In this retrospective and cross-sectional study, 1057 consecutive patients with STEMI were evaluated. The end-points of the study were short- and long-term mortality. The overall mortality rate was 16% (n = 170 patients). The IMRS was significantly higher in STEMI patients who did not survive compared with those who survived. According to multivariable COX proportional regression analysis, the IMRS was independently related to both short- (HR: 1.482, 95% CI: 1.325-1.675, p < .001) and long-term mortality (HR: 1.915, 95% CI: 1.711-2.180, p < .001). The comparison of receiver operating characteristic curves revealed that the IMRS had non-inferior predictive capability for short- and long-term mortality than the TIMI and GRACE risk scores. To the best of our knowledge, this is the first study to show that the IMRS can predict short- and long-term prognosis of patients with STEMI. Further, the IMRS' predictive value for overall mortality was non-inferior compared with TIMI and GRACE scores.

Evaluation of cardiac-electrophysiological balance according to National Institutes of Health Stroke Scale score at admission and discharge in acute ischemic stroke patients: A pilot study.

OBJECTIVE: The main objectives of this investigation were to determine whether there were any relationships between corrected cardiac-electrophysiological balance value and National Institutes of Health Stroke Scale scores at admission and discharge in patients with acute ischemic stroke and to assess whether cardiac-electrophysiological balance value was an independent predictor of high National Institutes of Health Stroke Scale scores (National Institutes of Health Stroke Scale score ≥5). METHODS: In this retrospective and observational study, 231 consecutive adult patients with acute ischemic stroke were evaluated. The cardiac-electrophysiological balance value was obtained by dividing the corrected QT interval by the QRS duration measured from surface electrocardiography. An experienced neurologist used the National Institutes of Health Stroke Scale score to determine the severity of the stroke at the time of admission and before discharge from the neurology care unit. The participants in the study were categorized into two groups: those with minor acute ischemic stroke (National Institutes of Health Stroke Scale score=1-4) and those with moderate-to-severe acute ischemic stroke (National Institutes of Health Stroke Scale scores ≥5). RESULTS: Acute ischemic stroke patients with National Institutes of Health Stroke Scale score ≥5 had higher heart rate, QT, corrected QT interval, T-peak to T-end corrected QT interval, cardiac-electrophysiological balance, and cardiac-electrophysiological balance values compared with those with an National Institutes of Health Stroke Scale score of 1-4. The cardiac-electrophysiological balance value was shown to be independently related to National Institutes of Health Stroke Scale scores ≥5 (OR 1.102, 95%CI 1.036-1.172, p<0.001). There was a moderate correlation between cardiac-electrophysiological balance and National Institutes of Health Stroke Scale scores at admission (r=0.333, p<0.001) and discharge (r=0.329, p<0.001). CONCLUSIONS: The findings of this study demonstrated that the cardiac-electrophysiological balance value was related to National Institutes of Health Stroke Scale scores at admission and discharge. Furthermore, an elevated cardiac-electrophysiological balance value was found to be an independent predictor of National Institutes of Health Stroke Scale score ≥5.

Evaluation of cardiac-electrophysiological balance according to National Institutes of Health Stroke Scale score at admission and discharge in acute ischemic stroke patients: A pilot study

SUMMARY OBJECTIVE: The main objectives of this investigation were to determine whether there were any relationships between corrected cardiac-electrophysiological balance value and National Institutes of Health Stroke Scale scores at admission and discharge in patients with acute ischemic stroke and to assess whether cardiac-electrophysiological balance value was an independent predictor of high National Institutes of Health Stroke Scale scores (National Institutes of Health Stroke Scale score ≥5). METHODS: In this retrospective and observational study, 231 consecutive adult patients with acute ischemic stroke were evaluated. The cardiac-electrophysiological balance value was obtained by dividing the corrected QT interval by the QRS duration measured from surface electrocardiography. An experienced neurologist used the National Institutes of Health Stroke Scale score to determine the severity of the stroke at the time of admission and before discharge from the neurology care unit. The participants in the study were categorized into two groups: those with minor acute ischemic stroke (National Institutes of Health Stroke Scale score=1-4) and those with moderate-to-severe acute ischemic stroke (National Institutes of Health Stroke Scale scores ≥5). RESULTS: Acute ischemic stroke patients with National Institutes of Health Stroke Scale score ≥5 had higher heart rate, QT, corrected QT interval, T-peak to T-end corrected QT interval, cardiac-electrophysiological balance, and cardiac-electrophysiological balance values compared with those with an National Institutes of Health Stroke Scale score of 1-4. The cardiac-electrophysiological balance value was shown to be independently related to National Institutes of Health Stroke Scale scores ≥5 (OR 1.102, 95%CI 1.036-1.172, p<0.001). There was a moderate correlation between cardiac-electrophysiological balance and National Institutes of Health Stroke Scale scores at admission (r=0.333, p<0.001) and discharge (r=0.329, p<0.001). CONCLUSIONS: The findings of this study demonstrated that the cardiac-electrophysiological balance value was related to National Institutes of Health Stroke Scale scores at admission and discharge. Furthermore, an elevated cardiac-electrophysiological balance value was found to be an independent predictor of National Institutes of Health Stroke Scale score ≥5.

Primary cardiac hydatid cyst presenting as noncompaction cardiomyopathy.

We report a case of cyst was initially labeled as left ventricular noncompaction cardiomyopathy. An accurate diagnosis is essential to establish the most effective treatment strategy. In particular, echocardiographic examination assists in identifying the correct diagnosis. In this case, two-dimensional and three-dimensional echocardiography and computed tomography were used for definitive diagnosis of cardiac hydatid cyst.