Metaverse-based cardiac magnetic resonance imaging simulation application for overcoming claustrophobia: a preliminary feasibility trial.

Introduction: Cardiac magnetic resonance imaging (CMR) is vital, but claustrophobia affects 10% of patients. The metaverse, an immersive virtual and augmented reality environment, has healthcare potential. We present a metaverse-based CMR simulation for claustrophobic patients. Methods: Three cardiomyopathy patients, initially CMR-refusing due to claustrophobia, received training via a virtual reality headset in a metaverse-based virtual hospital. Training efficacy was assessed through questionnaires and anxiety scales. Results: The patients successfully completed metaverse-based training, adapting to the CMR simulation. On CMR day, all entered the machine without issues and with reduced anxiety. Patients found the training useful, suggesting platform familiarization. Discussion: Our study demonstrates the metaverse's potential in alleviating CMR-related claustrophobia. The immersive nature enhances patient preparation, although usability improvements are needed. Further research should compare this approach with alternatives.

Cardiac magnetic resonance imaging (CMR) is a vital tool for diagnosing heart problems, but some patients cannot undergo it due to claustrophobia. To address this, researchers are exploring new methods like hypnosis and simulations. One emerging technology, the metaverse, a 3D virtual reality (VR) environment, is being tested in healthcare. This study created a metaverse-based simulation to help claustrophobic patients prepare for CMR. Three patients with heart issues were given VR headsets to access a virtual hospital in the metaverse. Inside, they were trained for CMR step by step, experiencing the process and sounds realistically. Training was done 1 week, 3 days, and 1 day before the real CMR. Anxiety levels were measured. All patients completed the virtual training without issues. During the first simulations, some could not complete entering the virtual CMR machine due to anxiety. However, by the final simulation, all succeeded. On CMR day, all completed the scan without problems, and their anxiety levels decreased significantly from the initial training. Patients found the training helpful, but the platform's usability needed improvement. The study demonstrates that metaverse-based simulations can help patients overcome claustrophobia to successfully undergo CMR. This technology holds promise for simulating medical situations, easing patient fears, and improving preparation. However, further work is needed to make it user-friendly and accessible without assistance. This study encourages more research to assess the usefulness of the metaverse for broader patient groups, comparing it with other methods like hypnosis or sedation.

A study of ChatGPT in facilitating Heart Team decisions on severe aortic stenosis.

BACKGROUND: Multidisciplinary Heart Teams (HTs) play a central role in the management of valvular heart diseases. However, the comprehensive evaluation of patients' data can be hindered by logistical challenges, which in turn may affect the care they receive. AIMS: This study aimed to explore the ability of artificial intelligence (AI), particularly large language models (LLMs), to improve clinical decision-making and enhance the efficiency of HTs. METHODS: Data from patients with severe aortic stenosis presented at HT meetings were retrospectively analysed. A standardised multiple-choice questionnaire, with 14 key variables, was processed by the OpenAI Chat Generative Pre-trained Transformer (GPT)-4. AI-generated decisions were then compared to those made by the HT. RESULTS: This study included 150 patients, with ChatGPT agreeing with the HT's decisions 77% of the time. The agreement rate varied depending on treatment modality: 90% for transcatheter valve implantation, 65% for surgical valve replacement, and 65% for medical treatment. CONCLUSIONS: The use of LLMs offers promising opportunities to improve the HT decision-making process. This study showed that ChatGPT's decisions were consistent with those of the HT in a large proportion of cases. This technology could serve as a failsafe, highlighting potential areas of discrepancy when its decisions diverge from those of the HT. Further research is necessary to solidify our understanding of how AI can be integrated to enhance the decision-making processes of HTs.

Transcaval versus Supra-Aortic Vascular Accesses for Transcatheter Aortic Valve Replacement: A Systematic Review with Meta-Analysis.

A growing body of evidence suggests that extrathoracic vascular accesses for transcatheter aortic valve replacement (TAVR) yield favorable outcomes and can be considered as primary alternatives when the gold-standard transfemoral access is contraindicated. Data comparing the transcaval (TCv) to supra-aortic (SAo) approaches (transcarotid, transsubclavian, and transaxillary) for TAVR are lacking. We aimed to compare the outcomes and safety of TCv and SAo accesses for TAVR as alternatives to transfemoral TAVR. A systematic review with meta-analysis was performed by searching PubMed/MEDLINE and EMBASE databases for all articles comparing TCv-TAVR against SAo-TAVR published until September 2023. Outcomes included in-hospital or 30-day all-cause mortality (ACM) and postoperative complications. A total of three studies with 318 TCv-TAVR and 179 SAo-TAVR patients were included. No statistically significant difference was found regarding in-hospital or 30-day ACM (relative risk [RR] 1.04, 95% confidence interval [CI] 0.47-2.34, p = 0.91), major bleeding, the need for blood transfusions, major vascular complications, and acute kidney injury. TCv-TAVR was associated with a non-statistically significant lower rate of neurovascular complications (RR 0.39, 95%CI 0.14-1.09, p = 0.07). These results suggest that both approaches may be considered as first-line alternatives to transfemoral TAVR, depending on local expertise and patients' anatomy. Additional data from long-term cohort studies are needed.

Head-to-head comparison of two angiography-derived fractional flow reserve techniques in patients with high-risk acute coronary syndrome: A multicenter prospective study.

BACKGROUND: FFRangio and QFR are angiography-based technologies that have been validated in patients with stable coronary artery disease. No head-to-head comparison to invasive fractional flow reserve (FFR) has been reported to date in patients with acute coronary syndromes (ACS). METHODS: This study is a subset of a larger prospective multicenter, single-arm study that involved patients diagnosed with high-risk ACS in whom 30-70% stenosis was evaluated by FFR. FFRangio and QFR - both calculated offline by 2 different and blinded operators - were calculated and compared to FFR. The two co-primary endpoints were the comparison of the Pearson correlation coefficient between FFRangio and QFR with FFR and the comparison of their inter-observer variability. RESULTS: Among 134 high-risk ACS screened patients, 59 patients with 84 vessels underwent FFR measurements and were included in this study. The mean FFR value was 0.82 ± 0.40 with 32 (38%) being ≤0.80. The mean FFRangio was 0.82 ± 0.20 and the mean QFR was 0.82 ± 0.30, with 27 (32%) and 25 (29%) being ≤0.80, respectively. The Pearson correlation coefficient was significantly better for FFRangio compared to QFR, with R values of 0.76 and 0.61, respectively (p = 0.01). The inter-observer agreement was also significantly better for FFRangio compared to QFR (0.86 vs 0.79, p < 0.05). FFRangio had 91% sensitivity, 100% specificity, and 96.8% accuracy, while QFR exhibited 86.4% sensitivity, 98.4% specificity, and 93.7% accuracy. CONCLUSION: In patients with high-risk ACS, FFRangio and QFR demonstrated excellent diagnostic performance. FFRangio seems to have better correlation to invasive FFR compared to QFR but further larger validation studies are required.

Successful closure of transcatheter aortic valve replacement-induced Gerbode defect with valve-in-valve technique: A case report.

We present the first documented case of a successful closure of a transcatheter aortic valve replacement (TAVR)-induced Gerbode defect using a valve-in-valve approach. A 90-year-old female with severe aortic stenosis underwent TAVR. Following post-dilatation, the patient experienced hemodynamic deterioration and collapse due to tamponade and sub-annular rupture leading to hemodynamic deterioration and the development of a Gerbode defect with communication between the left ventricle and right atrium. Hemodynamic stabilization was achieved through pericardiocentesis, followed by the low implantation of a second valve, effectively sealing the rupture. This case showcases a valuable alternative for managing rare challenging complications during TAVR procedures.

ChatGPT takes on the European Exam in Core Cardiology: an artificial intelligence success story?

Chat Generative Pre-trained Transformer (ChatGPT) is currently a trending topic worldwide triggering extensive debate about its predictive power, its potential uses, and its wider implications. Recent publications have demonstrated that ChatGPT can correctly answer questions from undergraduate exams such as the United States Medical Licensing Examination. We challenged it to answer questions from a more demanding, post-graduate exam-the European Exam in Core Cardiology (EECC), the final exam for the completion of specialty training in Cardiology in many countries. Our results demonstrate that ChatGPT succeeds in the EECC.

Meta-Analysis of the Prognostic Significance of Carotid Artery Stenosis in Patients Who Underwent Transcatheter Aortic Valve Implantation.

Stroke is a known complication of both transcatheter aortic valve implantation (TAVI) and carotid artery stenosis (CAS). Whether CAS is a predictor of worse prognosis after TAVI is unclear. We performed a meta-analysis to assess the impact of CAS on the incidence of neurovascular complications and mortality after TAVI. We searched PubMed/MEDLINE and EMBASE databases from inception to January 2023. CAS was defined by ≥50% stenosis of at least 1 carotid artery. Studies comparing CAS versus non-CAS TAVI populations were included. Patients' baseline characteristics and 30-day clinical outcomes were extracted. End points included the 30-day incidence of neurovascular complications (stroke or transient ischemic attack) and 30-day all-cause mortality. We identified six studies, totaling 6,763 patients in the CAS group and 23,861 patients in the non-CAS group. Patients with CAS had a higher prevalence of hypertension, diabetes mellitus, dyslipidemia, previous myocardial infarction, coronary artery bypass graft, peripheral artery disease, previous neurovascular disease, and chronic kidney disease. There was no significant difference in the rates of 30-day neurovascular complications between CAS and non-CAS groups (relative risk 1.23, 95% confidence interval 0.63 to 2.40, p = 0.54). CAS was associated with a higher risk of 30-day all-cause mortality (relative risk 1.28, 95% confidence interval 1.12 to 1.47, p <0.001), not found in a sensitivity analysis. In conclusion, patients with CAS presented with a significantly higher co-morbidity burden. CAS was not associated with an increased risk of 30-day neurovascular complications. 30-day mortality was higher in the CAS group but that may be a surrogate of the heavy co-morbidity burden of patients with CAS.

[State of the art management of patients presenting an ischemia with non-obstructive coronary arteries (ANOCA/INOCA)]. / Prise en charge de l'angine de poitrine et/ou de l'ischémie sans maladie coronarienne obstructive (ANOCA/INOCA).

Angor with non-obstructive coronary arteries or ischemia with non-obstructive coronary arteries (ANOCA/INOCA) is a condition where a patient experiences symptoms and/or signs of myocardial ischemia, without significant coronary artery stenoses. This syndrome is often caused by a direct imbalance between supply and demand, leading to inadequate myocardial perfusion due to microvascular limitations or coronary arteries' spasms. Although previously considered benign, there is increasing evidence that ANOCA/INOCA is associated with a poor quality of life, significant burden on the healthcare system, and major adverse cardiac events. This article reviews the definition of ANOCA/INOCA, epidemiology, risk factors, management, and current knowledge gaps and clinical trials.

La maladie coronarienne se présente classiquement sous forme de sténoses au niveau des artères coronariennes épicardiques. Cependant, un grand nombre de patients présentent des douleurs thoraciques et/ou un test non invasif positif pour une ischémie sans sténose coronarienne significative à l'angiographie. Il s'agit d'une maladie coronarienne non obstructive nommée ANOCA ou INOCA (Angina with Non Obstructive Coronary Arteries ou Ischemia with Non Obstructive Coronary Arteries). La cause peut être une atteinte de la microcirculation coronarienne ou un spasme des artères épicardiques. Longtemps considérée comme bénigne, peu de recherches ont été consacrées à l'ANOCA/INOCA. Cependant, de plus en plus de données montrent un impact sur les événements cardiaques majeurs, la qualité de vie et les coûts du système de santé.

[Can smart devices and AI in cardiology improve clinical practice?] / Les dispositifs intelligents et l'IA en cardiologie peuvent-ils améliorer la pratique clinique ?

Remote monitoring is becoming increasingly popular among healthcare professionals and patients for diagnosing and treating heart disease. Several smart devices connected to smartphones have been developed and validated in recent years, but their clinical use is still limited. Significant advances in the field of artificial intelligence (AI) are also revolutionizing several fields, yet the impact that these innovations could have on routine clinical practice is still unknown. We review the evidence and uses of the main smart devices currently available as well as the latest applications of AI in the field of cardiology, with the aim to ultimately evaluate the potential of this technology to transform modern clinical practice.

Le monitorage à distance devient de plus en plus populaire parmi les praticiens de la santé pour le diagnostic et la surveillance des maladies cardiaques. Plusieurs dispositifs « intelligents ¼ et connectés aux smartphones ont été développés et validés durant ces dernières années, mais leur utilisation clinique est toujours limitée. Bien que les progrès de l'intelligence artificielle (IA) soient en train de révolutionner plusieurs domaines, l'impact que ces innovations pourront avoir dans le monde médical est toujours inconnu. Le but de cet article est de passer en revue les principaux dispositifs disponibles et de comprendre les applications actuelles de l'IA en cardiologie, afin de mieux saisir dans quelle mesure ils sont susceptibles de transformer notre pratique clinique quotidienne.

Structural analysis of an endogenous 4-megadalton succinyl-CoA-generating metabolon.

The oxoglutarate dehydrogenase complex (OGDHc) participates in the tricarboxylic acid cycle and, in a multi-step reaction, decarboxylates α-ketoglutarate, transfers succinyl to CoA, and reduces NAD+. Due to its pivotal role in metabolism, OGDHc enzymatic components have been studied in isolation; however, their interactions within the endogenous OGDHc remain elusive. Here, we discern the organization of a thermophilic, eukaryotic, native OGDHc in its active state. By combining biochemical, biophysical, and bioinformatic methods, we resolve its composition, 3D architecture, and molecular function at 3.35 Å resolution. We further report the high-resolution cryo-EM structure of the OGDHc core (E2o), which displays various structural adaptations. These include hydrogen bonding patterns confining interactions of OGDHc participating enzymes (E1o-E2o-E3), electrostatic tunneling that drives inter-subunit communication, and the presence of a flexible subunit (E3BPo), connecting E2o and E3. This multi-scale analysis of a succinyl-CoA-producing native cell extract provides a blueprint for structure-function studies of complex mixtures of medical and biotechnological value.

Real-World Use and Predictors of Response to Disopyramide in Patients with Obstructive Hypertrophic Cardiomyopathy.

Background: Although disopyramide has been widely used to reduce left ventricular outflow obstruction (LVOTO) and to improve symptoms in patients with obstructive hypertrophic cardiomyopathy (oHCM), its use in real world as well as patient characteristics associated with a positive treatment response are still unclear. Methods: From 1980 to 2021, 1527 patients with HCM were evaluated and 372 (23%) had a LVOTO with active follow-up. The efficacy and safety of disopyramide were assessed systematically during 12 months (2-, 6-, and 12-month visits). Responders were patients with a final NYHA = I and a LVOTO < 30 mmHg; incomplete responders were those patients with NYHA > I and a LVOTO < 30 mmHg; and non-responders were symptomatic patients with no change in functional class NYHA and a LVOT gradient > 30 mmHg. Results: Two-hundred-fifty-four (66%) patients were in functional class NYHA I/II and 118 (34%) in NYHA III/IV. A total of 118/372 (32%, 55 ± 16 years) underwent disopyramide therapy. Twenty-eight (24%) patients responded to therapy, 39 (33%) were incomplete responders, and 51 (43%) did not respond. Responder were mainly patients in functional NYHA class I/II (24/28, 86%), whereas incomplete responders and non-responders were more often in functional NYHA class III/IV (50/54 (93%)). An independent predictor of response to disopyramide treatment was the presence of NYHA I/II at the initiation of therapy (HR 1.5 (95% CI 1.1-4.5), p = 0.03). No major life-threatening arrhythmic events or syncope occurred, despite 19 (16%) patients showing reduced QTc from baseline, 19 (16%) having no difference, while 80 (69%) patients had prolonged QTc interval. Thirty-one (26%) patients experienced side effects, in particular, 29 of the anticholinergic type. Conclusions: Disopyramide was underused in oHCM but effective in reducing LVOTO gradients and symptoms in slightly symptomatic patients with less severe disease phenotype with a safe pro-arrhythmic profile.

Enabling cryo-EM density interpretation from yeast native cell extracts by proteomics data and AlphaFold structures.

In the cellular context, proteins participate in communities to perform their function. The detection and identification of these communities as well as in-community interactions has long been the subject of investigation, mainly through proteomics analysis with mass spectrometry. With the advent of cryogenic electron microscopy and the "resolution revolution," their visualization has recently been made possible, even in complex, native samples. The advances in both fields have resulted in the generation of large amounts of data, whose analysis requires advanced computation, often employing machine learning approaches to reach the desired outcome. In this work, we first performed a robust proteomics analysis of mass spectrometry (MS) data derived from a yeast native cell extract and used this information to identify protein communities and inter-protein interactions. Cryo-EM analysis of the cell extract provided a reconstruction of a biomolecule at medium resolution (∼8 Å (FSC = 0.143)). Utilizing MS-derived proteomics data and systematic fitting of AlphaFold-predicted atomic models, this density was assigned to the 2.6 MDa complex of yeast fatty acid synthase. Our proposed workflow identifies protein complexes in native cell extracts from Saccharomyces cerevisiae by combining proteomics, cryo-EM, and AI-guided protein structure prediction.

Validation of a multiple­lead smartphone-based electrocardiograph with automated lead placement for layman use in patients with hypertrophic cardiomyopathy.

BACKGROUND: A smartphone 12-Lead ECG that enables layman ECG screening is still lacking. We aimed to validate D-Heart ECG device, a smartphone 8/12 Lead electrocardiograph with an image processing algorithm to guide secure electrode placement by non-professional users. METHODS: One-hundred-fourty-five patients with HCM were enrolled. Two uncovered chest images were acquired using the smartphone camera. An image with virtual electrodes placement by imaging processing algorithm software was compared to the 'gold standard' electrode placement by a doctor. D-Heart 8 and 12-Lead ECG were obtained, immediately followed by 12­lead ECGs and were assessed by 2 independent observers. Burden of ECG abnormalities was defined by a score based on the sum of 9 criteria, identifying four classes of increasing severity. RESULTS: A total of 87(60%) patients presented a normal/mildly abnormal ECG, whereas 58(40%) had moderate or severe ECG alteration. Eight(6%) patients had ≥1 misplaced electrode. D-Heart 8-Lead and 12­lead ECGs concordance according to Cohen's weighted kappa test was 0,948 (p < 0,001, agreement of 97.93%). Concordance was high for the Romhilt-Estes score (kw = 0,912; p < 0.01). Concordance between D-Heart 12-Lead ECG and standard 12-Lead ECG was perfect (kw = 1). PR and QRS intervals measurements comparison with Bland-Altman method showed good accuracy (95% limit of agreement ±18 ms for PR and ± 9 ms for QRS). CONCLUSIONS: D-Heart 8/12-Lead ECGs proved accurate, allowing an assessment of ECG abnormalities comparable to the standard 12­lead ECG in patients with HCM. The image processing algorithm provided accurate electrode placement, standardizing exam quality, potentially opening perspectives for layman ECG screening campaigns.