Effectiveness of radiation protection systems in the cardiac catheterization laboratory: a comparative study

BACKGROUND As numbers and complexity of percutaneous coronary interventions are constantly increasing, optimal radiation protection is required to ensure operator safety. Suspended radiation protection systems (SRPS) and protective scatter-radiation absorbing drapes (PAD) are novel methods to mitigate fluoroscopic scattered radiation exposure. The aim of the study was to investigate the effectiveness regarding radiation protection of a SRPS and a PAD in comparison with conventional protection. METHODS A total of 229 cardiac catheterization procedures with SRPS (N = 73), PAD (N = 82) and standard radiation protection (N = 74) were prospectively included. Real-time dosimeter data were collected from the first operator and the assistant. Endpoints were the cumulative operator exposure relative to the dose area product [standardized operator exposure (SOE)] for the first operator and the assistant. RESULTS For the first operator, the SRPS and the PAD significantly decreased the overall SOE compared to conventional shielding by 93.9% and 66.4%, respectively (P < 0.001). The protective effect of the SRPS was significantly higher compared to the PAD (P < 0.001). For the assistant, the SRPS and the PAD provided a not statistically significant reduction compared to conventional shielding in the overall SOE by 38.0% and 30.6%, respectively. CONCLUSIONS The SRPS and the PAD enhance radiation protection significantly compared to conventional protection. In most clinical scenarios, the protective effect of SRPS is significantly higher than the additional protection provided by the PAD. Comparison of the additional radiation protection provided by protective scatter-radiation absorbing drapes (PAD) and the suspended radiation protection system (SRPS) system over standard protection with lead aprons

Twenty-five-year trends in incidence, angiographic appearance, and management of spontaneous coronary artery dissection

BACKGROUND Spontaneous coronary artery dissection (SCAD) has been described as an infrequent cause of acute coronary syndrome (ACS). Knowledge about the disease is still limited and SCAD might still be underdiagnosed. OBJECTIVES Trends in incidence, presentation, angiographic appearance, management, and outcomes of SCAD over 25 years were analyzed. METHODS Patients with SCAD between 1997 and 2021 at the University Hospital Zurich, Switzerland, were included. Incidences were assessed as total numbers and proportions of ACS cases. Clinical data were collected from medical records and angiographic findings were reviewed. Major adverse cardiac events (MACE) were defined as the composite of all-cause death, cardiac arrest, SCAD recurrence or progression, other myocardial infarction, and stroke. RESULTS One hundred fifty-six SCAD cases were included in this study. The incidence increased significantly in total (p < 0.001) and relative to ACS cases (p < 0.001). This was based on an increase of shorter lesions (p = 0.004), SCAD type 2 (p < 0.001), and lesions in side branches (p = 0.014), whereas lesions in the left main coronary artery and proximal segments were decreasing (p-values 0.029 and < 0.001, respectively). There was an increase in conservative therapy (p < 0.001). The rate of MACE (24%) was stable, however, there was a reduced proportion of patients with a need for intensive care treatment (p = 0.017). CONCLUSIONS SCAD represents an important entity of ACS that still might be underappreciated. The increasing incidence of SCAD is likely based on better awareness and familiarity with the disease. A lower need for intensive care treatment suggests positive effects of the increasing implementation of conservative management

Coronary microvascular dysfunction in Takotsubo syndrome: an analysis using angiography-derived index of microcirculatory resistance

BACKGROUND Coronary microvascular dysfunction (CMD) has been proposed as a crucial factor in the pathophysiology of Takotsubo syndrome (TTS). The angiography-derived index of microcirculatory resistance (caIMR) offers an alternative to conventional hyperemic wire-based IMR to assess CMD. We aimed to evaluate CMD's prevalence, transience, and impact on in-hospital outcomes in TTS. METHODS All three coronary arteries of 96 patients with TTS were assessed for their coronary angiography derived Index of microcirculatory Resistance (caIMR) and compared to non-obstructed vessels of matched patients with ST-elevation myocardial infarction. Further, the association between caIMR and the TTS-specific combined in-hospital endpoint of death, cardiac arrest, ventricular arrhythmogenic events and cardiogenic shock was investigated. RESULTS Elevated IMR was present in all TTS patients, with significantly elevated caIMR values in all coronary arteries compared to controls. CaIMR did not differ between apical and midventricular TTS types. CaIMR normalized in TTS patients with follow-up angiographies performed at a median of 28 months (median caIMR at event vs follow-up: LAD 34.8 [29.9-41.1] vs 20.3 [16.0-25.3], p < 0.001; LCX: 38.7 [32.9-50.1] vs 23.7 [19.4-30.5], p < 0.001; RCA: 31.7 [25.0-39.1] vs 19.6 [17.1-24.0], p < 0.001). The extent of caIMR elevation significantly correlated with the combined in-hospital endpoint (p = 0.036). CONCLUSION TTS patients had evidence of elevated caIMR in at least one coronary artery with a trend towards higher LAD caIMR in apical type TTS and normalization after recovery. Furthermore, extent of caIMR elevation was associated with increased risk of in-hospital MACE of TTS patients

Machine learning-based prediction of in-hospital death for patients with takotsubo syndrome: The InterTAK-ML model

AIMS Takotsubo syndrome (TTS) is associated with a substantial rate of adverse events. We sought to design a machine learning (ML)-based model to predict the risk of in-hospital death and to perform a clustering of TTS patients to identify different risk profiles. METHODS AND RESULTS A ridge logistic regression-based ML model for predicting in-hospital death was developed on 3482 TTS patients from the International Takotsubo (InterTAK) Registry, randomly split in a train and an internal validation cohort (75% and 25% of the sample size, respectively) and evaluated in an external validation cohort (1037 patients). Thirty-one clinically relevant variables were included in the prediction model. Model performance represented the primary endpoint and was assessed according to area under the curve (AUC), sensitivity and specificity. As secondary endpoint, a K-medoids clustering algorithm was designed to stratify patients into phenotypic groups based on the 10 most relevant features emerging from the main model. The overall incidence of in-hospital death was 5.2%. The InterTAK-ML model showed an AUC of 0.89 (0.85-0.92), a sensitivity of 0.85 (0.78-0.95) and a specificity of 0.76 (0.74-0.79) in the internal validation cohort and an AUC of 0.82 (0.73-0.91), a sensitivity of 0.74 (0.61-0.87) and a specificity of 0.79 (0.77-0.81) in the external cohort for in-hospital death prediction. By exploiting the 10 variables showing the highest feature importance, TTS patients were clustered into six groups associated with different risks of in-hospital death (28.8% vs. 15.5% vs. 5.4% vs. 1.0.8% vs. 0.5%) which were consistent also in the external cohort. CONCLUSION A ML-based approach for the identification of TTS patients at risk of adverse short-term prognosis is feasible and effective. The InterTAK-ML model showed unprecedented discriminative capability for the prediction of in-hospital death

Social media matrix: Matching corporate goals with external social media activities

In this paper we introduce the Social Media Matrix, a practitioner-oriented instrument that supports companies to decide based on their corporate or communication goals which social media activities to execute. The matrix consists of three parts: 1. Social media goals and task areas have been identified and matched. 2. Five types of social media activities have been defined. 3. The matrix provides a structure to assess the suitability of each activity type on each social media platform for each goal. Whereas the first two parts can be generally used, the assessment must be onducted explicitly for an industry sector. A ready to use assessment for the German B2B sector has been exemplarily compiled from expert-interviews with practitioners and by reviewing concrete social media activities. The matrix is used as a basis for social media consultancy projects and evaluated thereby

Abstracts Of The Proceedings And The Posters From The Third Scientific Session Of The Medical College Of Varna

October 2-3, 201

Machine-learning based prediction of in-hospital death for patients with takotsubo syndrome: the InterTAK-ML model

Aims: Takotsubo syndrome (TTS) is associated with a substantial rate of adverse events. We sought to design a machine-learning (ML) based model to predict the risk of in-hospital death and to perform a clustering of TTS patients to identify different risk profiles. Methods and results: A Ridge Logistic Regression-based ML model for predicting in-hospital death was developed on 3482 TTS patients from the International Takotsubo Registry, randomly split in a train and an internal validation cohort (75% and 25% of the sample size, respectively) and evaluated in an external validation cohort (1037 patients). 31 clinically relevant variables were included in the prediction model. Model performance represented the primary endpoint and was assessed according to area under the receiver-operating characteristic curve (AUC), Sensitivity and Specificity. As secondary endpoint, a K-Medoids clustering algorithm was designed to stratify patients into phenotypic groups based on the ten most relevant features emerging from the main model. The overall incidence of in-hospital death was 5.2%. The InterTAK-ML model showed an AUC of 0.89 (0.85-0.92), Sensitivity 0.85 (0.78-0.95) and Specificity 0.76 (0.74-0.79) in the internal validation cohort and an AUC of 0.82 (0.73-0.91), a sensitivity of 0.74 (0.61-0.87) and a specificity of 0.79 (0.77-0.81) in the external cohort for in-hospital death prediction. By exploiting the 10 variables showing the highest feature importance, TTS patients were clustered into six groups associated with different risks of in-hospital death (28.8% vs 15.5% vs 5.4% vs 0.8% vs 0.5%) which were consistent also in the external cohort. Conclusion: A ML-based approach for the identification of TTS patients at risk of adverse short-term prognosis is feasible and effective. The InterTAK-ML model showed unprecedented discriminative capability for the prediction of in-hospital death. This article is protected by copyright. All rights reserved

Grandiose narcissism, unfounded beliefs, and behavioral reactions during the COVID-19 pandemic

A theoretical perspective on grandiose narcissism suggests four forms of it (sanctity, admiration, heroism, rivalry) and states that these forms conduce to different ways of thinking and acting. Guided by this perspective, we examined in a multinational and multicultural study (61 countries; N = 15,039) how narcissism forms are linked to cognitions and behaviors prompted by the COVID-19 pandemic. As expected, differences in cognitions and behaviors across narcissism forms emerged. For example, higher narcissistic rivalry predicted lower likelihood of enactment of COVID-19 prevention behaviors, but higher narcissistic sanctity predicted higher likelihood of enactment of COVID-19 prevention behaviors. Further, whereas the heroism, admiration, and rivalry narcissism forms acted in a typically antisocial manner, with high narcissism predicting greater endorsement of unfounded health beliefs, the sanctity form acted in a prosocial manner, with higher narcissism being linked to lower endorsement of unfounded COVID-19 health beliefs. Thus, the findings (a) support the idea of four narcissism forms acting differently, and (b) show that these differences reflect a double-edged sword, sometimes linking to an anti-social orientation, and sometimes linking to a pro-social orientation.</p