Predicting the risk of early intensive care unit admission for patients hospitalized with acute pancreatitis using supervised machine learning
CONCLUSIONS: This supervised machine learning-based model can help recognize high-risk AP hospitalizations. Clinicians may use the IAPR score to identify patients with AP at high risk of ICU admission within the first week of hospitalization.PMID:38628340 | PMC:PMC11018057 | DOI:10.1080/08998280.2024.2326371 (Source: Baylor University Medical Center Proceedings)
Source: Baylor University Medical Center Proceedings - April 17, 2024 Category: Universities & Medical Training Authors: Hassam Ali Faisal Inayat Rubaid Dhillon Pratik Patel Arslan Afzal Christin Wilkinson Attiq Ur Rehman Muhammad Sajeel Anwar Gul Nawaz Ahtshamullah Chaudhry Junaid Rasul Awan Muhammad Sohaib Afzal Jayanta Samanta Douglas G Adler Babu P Mohan Source Type: research
Predicting the risk of early intensive care unit admission for patients hospitalized with acute pancreatitis using supervised machine learning
CONCLUSIONS: This supervised machine learning-based model can help recognize high-risk AP hospitalizations. Clinicians may use the IAPR score to identify patients with AP at high risk of ICU admission within the first week of hospitalization.PMID:38628340 | PMC:PMC11018057 | DOI:10.1080/08998280.2024.2326371 (Source: Baylor University Medical Center Proceedings)
Source: Baylor University Medical Center Proceedings - April 17, 2024 Category: Universities & Medical Training Authors: Hassam Ali Faisal Inayat Rubaid Dhillon Pratik Patel Arslan Afzal Christin Wilkinson Attiq Ur Rehman Muhammad Sajeel Anwar Gul Nawaz Ahtshamullah Chaudhry Junaid Rasul Awan Muhammad Sohaib Afzal Jayanta Samanta Douglas G Adler Babu P Mohan Source Type: research
Predicting the risk of early intensive care unit admission for patients hospitalized with acute pancreatitis using supervised machine learning
CONCLUSIONS: This supervised machine learning-based model can help recognize high-risk AP hospitalizations. Clinicians may use the IAPR score to identify patients with AP at high risk of ICU admission within the first week of hospitalization.PMID:38628340 | PMC:PMC11018057 | DOI:10.1080/08998280.2024.2326371 (Source: Baylor University Medical Center Proceedings)
Source: Baylor University Medical Center Proceedings - April 17, 2024 Category: Universities & Medical Training Authors: Hassam Ali Faisal Inayat Rubaid Dhillon Pratik Patel Arslan Afzal Christin Wilkinson Attiq Ur Rehman Muhammad Sajeel Anwar Gul Nawaz Ahtshamullah Chaudhry Junaid Rasul Awan Muhammad Sohaib Afzal Jayanta Samanta Douglas G Adler Babu P Mohan Source Type: research
Predicting the risk of early intensive care unit admission for patients hospitalized with acute pancreatitis using supervised machine learning
CONCLUSIONS: This supervised machine learning-based model can help recognize high-risk AP hospitalizations. Clinicians may use the IAPR score to identify patients with AP at high risk of ICU admission within the first week of hospitalization.PMID:38628340 | PMC:PMC11018057 | DOI:10.1080/08998280.2024.2326371 (Source: Baylor University Medical Center Proceedings)
Source: Baylor University Medical Center Proceedings - April 17, 2024 Category: Universities & Medical Training Authors: Hassam Ali Faisal Inayat Rubaid Dhillon Pratik Patel Arslan Afzal Christin Wilkinson Attiq Ur Rehman Muhammad Sajeel Anwar Gul Nawaz Ahtshamullah Chaudhry Junaid Rasul Awan Muhammad Sohaib Afzal Jayanta Samanta Douglas G Adler Babu P Mohan Source Type: research
Predicting the risk of early intensive care unit admission for patients hospitalized with acute pancreatitis using supervised machine learning
CONCLUSIONS: This supervised machine learning-based model can help recognize high-risk AP hospitalizations. Clinicians may use the IAPR score to identify patients with AP at high risk of ICU admission within the first week of hospitalization.PMID:38628340 | PMC:PMC11018057 | DOI:10.1080/08998280.2024.2326371 (Source: Baylor University Medical Center Proceedings)
Source: Baylor University Medical Center Proceedings - April 17, 2024 Category: Universities & Medical Training Authors: Hassam Ali Faisal Inayat Rubaid Dhillon Pratik Patel Arslan Afzal Christin Wilkinson Attiq Ur Rehman Muhammad Sajeel Anwar Gul Nawaz Ahtshamullah Chaudhry Junaid Rasul Awan Muhammad Sohaib Afzal Jayanta Samanta Douglas G Adler Babu P Mohan Source Type: research
Predicting the risk of early intensive care unit admission for patients hospitalized with acute pancreatitis using supervised machine learning
CONCLUSIONS: This supervised machine learning-based model can help recognize high-risk AP hospitalizations. Clinicians may use the IAPR score to identify patients with AP at high risk of ICU admission within the first week of hospitalization.PMID:38628340 | PMC:PMC11018057 | DOI:10.1080/08998280.2024.2326371 (Source: Baylor University Medical Center Proceedings)
Source: Baylor University Medical Center Proceedings - April 17, 2024 Category: Universities & Medical Training Authors: Hassam Ali Faisal Inayat Rubaid Dhillon Pratik Patel Arslan Afzal Christin Wilkinson Attiq Ur Rehman Muhammad Sajeel Anwar Gul Nawaz Ahtshamullah Chaudhry Junaid Rasul Awan Muhammad Sohaib Afzal Jayanta Samanta Douglas G Adler Babu P Mohan Source Type: research
Predicting the risk of early intensive care unit admission for patients hospitalized with acute pancreatitis using supervised machine learning
CONCLUSIONS: This supervised machine learning-based model can help recognize high-risk AP hospitalizations. Clinicians may use the IAPR score to identify patients with AP at high risk of ICU admission within the first week of hospitalization.PMID:38628340 | PMC:PMC11018057 | DOI:10.1080/08998280.2024.2326371 (Source: Baylor University Medical Center Proceedings)
Source: Baylor University Medical Center Proceedings - April 17, 2024 Category: Universities & Medical Training Authors: Hassam Ali Faisal Inayat Rubaid Dhillon Pratik Patel Arslan Afzal Christin Wilkinson Attiq Ur Rehman Muhammad Sajeel Anwar Gul Nawaz Ahtshamullah Chaudhry Junaid Rasul Awan Muhammad Sohaib Afzal Jayanta Samanta Douglas G Adler Babu P Mohan Source Type: research
Predicting the risk of early intensive care unit admission for patients hospitalized with acute pancreatitis using supervised machine learning
CONCLUSIONS: This supervised machine learning-based model can help recognize high-risk AP hospitalizations. Clinicians may use the IAPR score to identify patients with AP at high risk of ICU admission within the first week of hospitalization.PMID:38628340 | PMC:PMC11018057 | DOI:10.1080/08998280.2024.2326371 (Source: Baylor University Medical Center Proceedings)
Source: Baylor University Medical Center Proceedings - April 17, 2024 Category: Universities & Medical Training Authors: Hassam Ali Faisal Inayat Rubaid Dhillon Pratik Patel Arslan Afzal Christin Wilkinson Attiq Ur Rehman Muhammad Sajeel Anwar Gul Nawaz Ahtshamullah Chaudhry Junaid Rasul Awan Muhammad Sohaib Afzal Jayanta Samanta Douglas G Adler Babu P Mohan Source Type: research
Atrial fibrillation: real-life experience of a rhythm control with electrical cardioversion in a community hospital
Atrial fibrillation is the most prevalent sustained cardiac arrhythmia. Electrical cardioversion, a well-established part of the rhythm control strategy, is probably underused in community settings. Here, we d... (Source: BMC Cardiovascular Disorders)
Source: BMC Cardiovascular Disorders - April 17, 2024 Category: Cardiology Authors: Artemiy Okhotin, Maxim Osipov, Vasilij Osipov and Anton Barchuk Tags: Research Source Type: research
Pressure waveform analysis for occlusion assessment significantly reduces contrast medium use in cryoballoon pulmonary vein isolation
ConclusionCB-PVI utilizing a fully integrated pressure waveform analysis tool to assess PV occlusion is feasible and safe and significantly reduces the amount of contrast medium without impact on procedural parameters and freedom from arrhythmia recurrence.Graphical Abstract (Source: Journal of Interventional Cardiac Electrophysiology)
Source: Journal of Interventional Cardiac Electrophysiology - April 17, 2024 Category: Cardiology Source Type: research
Leukocyte Ig-like receptor B4 (Lilrb4a) alleviates cardiac dysfunction and isoproterenol-induced arrhythmogenic remodeling associated with cardiac fibrosis and inflammation
Heart failure (HF) is usually accompanied by the activation of the sympathetic nerve, and the excessive activation of the sympathetic nerve also promotes cardiac remodeling and cardiac dysfunction. In the isoproterenol (ISO) induced animal model, it is often accompanied by myocardial hypertrophy, fibrosis, and inflammation. Leukocyte immunoglobulin-like receptor B4a (Lilrb4a) is an immunosuppressive regulatory receptor and plays a vital role in cardiovascular disease. However, the effect of Lilrb4a on ventricular arrhythmias from ISO-induced mice model remains unclear. (Source: Heart Rhythm)
Source: Heart Rhythm - April 16, 2024 Category: Cardiology Authors: Hui Fu, Bin Kong, Wei Shuai, Jun Zhu, Xi Wang, Yanhong Tang, He Huang, Congxin Huang Source Type: research
Regional conduction velocities determined by non-invasive mapping are associated with arrhythmia-free survival after atrial fibrillation ablation
Atrial arrhythmogenic substrate is a key determinant of atrial fibrillation (AF) recurrence after pulmonary vein isolation (PVI), and reduced conduction-velocities have been linked to adverse outcome. However, a non-invasive method to assess such electrophysiological substrate is not available to date. (Source: Heart Rhythm)
Source: Heart Rhythm - April 16, 2024 Category: Cardiology Authors: Eric Invers-Rubio, Ismael Hern ández-Romero, Jana Reventos-Presmanes, Elisenda Ferro, Jean-Baptiste Guichard, Mariona Regany-Closa, Berta Pellicer-Sendra, Roger Borras, Susanna Prat-Gonzalez, Jose Maria Tolosana, Andreu Porta-Sanchez, Elena Arbelo, Eduar Source Type: research
Photoplethysmography based atrial fibrillation detection: a continually growing field
Objective. Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with significant health ramifications, including an elevated susceptibility to ischemic stroke, heart disease, and heightened mortality. Photoplethysmography (PPG) has emerged as a promising technology for continuous AF monitoring for its cost-effectiveness and widespread integration into wearable devices. Our team previously conducted an exhaustive review on PPG-based AF detection before June 2019. However, since then, more advanced technologies have emerged in this field. Approach. This paper offers a comprehensive review of the latest advan...
Source: Physiological Measurement - April 16, 2024 Category: Physiology Authors: Cheng Ding, Ran Xiao, Weijia Wang, Elizabeth Holdsworth and Xiao Hu Source Type: research
Extracellular acidification reveals the antiarrhythmic properties of amiodarone related to late sodium current-induced atrial arrhythmia
CONCLUSION: The pharmacological properties of AMIO concerning healthy rat atrial tissue are not dependent on pHe. However, the prevention of arrhythmias induced by INa-Late is pHe-dependent. The development of drugs analogous to AMIO with charge stabilization may help to create more effective drugs to treat arrhythmias related to the INa-Late.PMID:38619735 | DOI:10.1007/s43440-024-00597-2 (Source: Pharmacological Reports)
Source: Pharmacological Reports - April 15, 2024 Category: Drugs & Pharmacology Authors: Michael Ramon de Lima Concei ção Jorge Lucas Teixeira-Fonseca Leisiane Pereira Marques Diego Santos Souza Fabiana da Silva Alc ântara Diego Jose Belato Orts Danilo Roman-Campos Source Type: research
