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Participants in the long-running bioethical debate over human germline genetic modification (HGGM) tend to imagine future people abstractly and on the basis of conventionalized characteristics familiar from science fiction, such as intelligence, disease resistance and height. In order to distinguish these from scientifically meaningful terms like "phenotype" and "trait," this article proposes the term "persemes" to describe the units of difference for hypothetical people. In the HGGM debate, persemes are frequently conceptualized as similar, modular entities, like building blocks to be assembled into genetically modified people. They are discussed as though they each would be chosen individually without affecting other persemes and as though they existed as components within future people rather than being imposed through social context. This modular conceptual framework appears to influence bioethical approaches to HGGM by reinforcing the idea of human capacities as natural primary goods subject to distributive justice and supporting the use of objective list theories of well-being. As a result, assumptions of modularity may limit the ability of stakeholders with other perspectives to present them in the HGGM debate. This article examines the historical trends behind the modular framework for genetically modified people, its likely psychological basis, and its philosophical ramifications.
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This article reviews the application of artificial intelligence (AI) in acute cardiac care, highlighting its potential to transform patient outcomes in the face of the global burden of cardiovascular diseases. It explores how AI algorithms can rapidly and accurately process data for the prediction and diagnosis of acute cardiac conditions. The review examines AI's impact on patient health across various diagnostic tools such as echocardiography, electrocardiography, coronary angiography, cardiac computed tomography, and magnetic resonance imaging, discusses the regulatory landscape for AI in health care, and categorises AI algorithms by their risk levels. Furthermore, it addresses the challenges of data quality, generalisability, bias, transparency, and regulatory considerations, underscoring the necessity for inclusive data and robust validation processes. The review concludes with future perspectives on integrating AI into clinical workflows and the ongoing need for research, regulation, and innovation to harness AI's full potential in improving acute cardiac care.
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The potential of artificial intelligence (AI) in medicine lies in its ability to enhance clinicians' capacity to analyse medical images, thereby improving diagnostic precision and accuracy and thus enhancing current tests. However, the integration of AI within health care is fraught with difficulties. Heterogeneity among health care system applications, reliance on proprietary closed-source software, and rising cybersecurity threats pose significant challenges. Moreover, before their deployment in clinical settings, AI models must demonstrate their effectiveness across a wide range of scenarios and must be validated by prospective studies, but doing so requires testing in an environment mirroring the clinical workflow, which is difficult to achieve without dedicated software. Finally, the use of AI techniques in health care raises significant legal and ethical issues, such as the protection of patient privacy, the prevention of bias, and the monitoring of the device's safety and effectiveness for regulatory compliance. This review describes challenges to AI integration in health care and provides guidelines on how to move forward. We describe an open-source solution that we developed that integrates AI models into the Picture Archives Communication System (PACS), called PACS-AI. This approach aims to increase the evaluation of AI models by facilitating their integration and validation with existing medical imaging databases. PACS-AI may overcome many current barriers to AI deployment and offer a pathway toward responsible, fair, and effective deployment of AI models in health care. In addition, we propose a list of criteria and guidelines that AI researchers should adopt when publishing a medical AI model to enhance standardisation and reproducibility.
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BACKGROUND: Wide interhospital variations exist in cardiovascular intensive care unit (CICU) admission practices and the use of critical care restricted therapies (CCRx), but little is known about the differences in patient acuity, CCRx utilization, and the associated outcomes within tertiary centers. METHODS: The Critical Care Cardiology Trials Network is a multicenter registry of tertiary and academic CICUs in the United States and Canada that captured consecutive admissions in 2-month periods between 2017 and 2022. This analysis included 17â 843 admissions across 34 sites and compared interhospital tertiles of CCRx (eg, mechanical ventilation, mechanical circulatory support, continuous renal replacement therapy) utilization and its adjusted association with in-hospital survival using logistic regression. The Pratt index was used to quantify patient-related and institutional factors associated with CCRx variability. RESULTS: The median age of the study population was 66 (56-77) years and 37% were female. CCRx was provided to 62.2% (interhospital range of 21.3%-87.1%) of CICU patients. Admissions to CICUs with the highest tertile of CCRx utilization had a greater burden of comorbidities, had more diagnoses of ST-elevation myocardial infarction, cardiac arrest, or cardiogenic shock, and had higher Sequential Organ Failure Assessment scores. The unadjusted in-hospital mortality (median, 12.7%) was 9.6%, 11.1%, and 18.7% in low, intermediate, and high CCRx tertiles, respectively. No clinically meaningful differences in adjusted mortality were observed across tertiles when admissions were stratified by the provision of CCRx. Baseline patient-level variables and institutional differences accounted for 80% and 5.3% of the observed CCRx variability, respectively. CONCLUSIONS: In a large registry of tertiary and academic CICUs, there was a >4-fold interhospital variation in the provision of CCRx that was primarily driven by differences in patient acuity compared with institutional differences. No differences were observed in adjusted mortality between low, intermediate, and high CCRx utilization sites.
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Cardiologia , Monitorização Hemodinâmica , Idoso , Feminino , Humanos , Masculino , Unidades de Cuidados Coronarianos , Cuidados Críticos , Mortalidade Hospitalar , Unidades de Terapia Intensiva , Sistema de Registros , Estados Unidos/epidemiologia , Pessoa de Meia-Idade , Estudos Multicêntricos como Assunto , Ensaios Clínicos como AssuntoRESUMO
Antiplatelet therapy (APT) is the foundation of treatment and prevention of atherothrombotic events in patients with atherosclerotic cardiovascular disease. Selecting the optimal APT strategies to reduce major adverse cardiovascular events, while balancing bleeding risk, requires ongoing review of clinical trials. Appended, the focused update of the Canadian Cardiovascular Society/Canadian Association of Interventional Cardiology guidelines for the use of APT provides recommendations on the following topics: (1) use of acetylsalicylic acid in primary prevention of atherosclerotic cardiovascular disease; (2) dual APT (DAPT) duration after percutaneous coronary intervention (PCI) in patients at high bleeding risk; (3) potent DAPT (P2Y12 inhibitor) choice in patients who present with an acute coronary syndrome (ACS) and possible DAPT de-escalation strategies after PCI; (4) choice and duration of DAPT in ACS patients who are medically treated without revascularization; (5) pretreatment with DAPT (P2Y12 inhibitor) before elective or nonelective coronary angiography; (6) perioperative and longer-term APT management in patients who require coronary artery bypass grafting surgery; and (7) use of APT in patients with atrial fibrillation who require oral anticoagulation after PCI or medically managed ACS. These recommendations are all on the basis of systematic reviews and meta-analyses conducted as part of the development of these guidelines, provided in the Supplementary Material.
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Síndrome Coronariana Aguda , Cardiologia , Intervenção Coronária Percutânea , Humanos , Inibidores da Agregação Plaquetária , Canadá , Revisões Sistemáticas como Assunto , Síndrome Coronariana Aguda/tratamento farmacológico , Resultado do TratamentoRESUMO
BACKGROUND: Little is known about the prevalence and post-surgical outcomes associated with cardiac intensive care unit (CICU) therapeutics among CICU patients referred for cardiac surgery. OBJECTIVES: The purpose of this study was to investigate the clinical characteristics and outcomes of CICU patients referred for cardiac surgery from the intensive care unit. METHODS: We analyzed characteristics and outcomes of CICU admissions referred from the CICU for cardiac surgery during 2017 to 2020 across 29 centers. The primary outcome was in-hospital mortality. RESULTS: Among 10,321 CICU admissions, 887 (8.6%) underwent cardiac surgery, including 406 (46%) coronary artery bypass graftings, 201 (23%) transplants or ventricular assist devices, 171 (19%) valve surgeries, and 109 (12%) other procedures. Common indications for CICU admission included shock (33.5%) and respiratory insufficiency (24.9%). Preoperative CICU therapies included vasoactive therapy in 52.2%, mechanical circulatory support in 35.9%, renal replacement in 8.2%, mechanical ventilation in 35.7%, and 17.5% with high-flow nasal cannula or noninvasive positive pressure ventilation. In-hospital mortality was 11.7% among all CICU admissions and 9.1% among patients treated with cardiac surgery. After multivariable adjustment, pre-op mechanical circulatory support and renal replacement therapy were associated with mortality, while respiratory support and vasoactive therapy were not. CONCLUSIONS: Nearly 1 in 12 contemporary CICU patients receive cardiac surgery. Despite high preoperative disease severity, CICU admissions undergoing cardiac surgery had a comparable mortality rate to CICU patients overall; highlighting the ability of clinicians to select higher acuity patients with a reasonable perioperative risk.