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The impact of new-onset atrial fibrillation in the setting of acute coronary syndrome.
J Cardiol
January 2025
Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin, China; Kent and Medway Medical School, Canterbury, Kent, UK; School of Nursing and Health Studies, Hong Kong Metropolitan University, Hong Kong, China.
Approximately 10 % of patients who have suffered from myocardial infarction develop new-onset atrial fibrillation (AF). Coronary artery disease implicating atrial branches has been associated with AF. The following variables have been associated with new-onset AF in the setting of acute coronary syndrome: older age, history of hypertension, history of angina, history of stroke, chronic renal failure, body mass index, no statin use, worse nutritional status, worse Killip class, admission heart rate ≥ 85 bpm, complete atrioventricular block, Glasgow prognostic score, Syntax score, CHEST score > 3, PRECISE-DAPT score ≥ 25, left ventricular ejection fraction ≤40 %, increased left atrial diameter, E/E' ratio > 12, epicardial fat tissue thickness, and thrombolysis in myocardial infarction flow <3.
View Article and Find Full Text PDFIntegrating D-Dimer Thresholds into the Revised Caprini Risk Stratification to Predict Deep Vein Thrombosis Risk in Preoperative Knee Osteoarthritis Patients.
Clin Appl Thromb Hemost
January 2025
Department of Nursing, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Introduction: Preoperative patients with knee osteoarthritis have a significantly increased risk of venous thromboembolism (VTE). While the Caprini risk assessment model offers some clinical guidance in predicting deep vein thrombosis (DVT), it has a relatively low predictive accuracy. Enhancing the model by integrating biomarkers, such as D-dimers, can potentially improve its accuracy.
View Article and Find Full Text PDF[Quantitative analysis of chest CT in coronavirus infected patients and its correlation with clinical features].
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue
December 2024
Department of Critical Care Medicine, Qingdao Municipal Hospital, Qingdao 266001, Shandong, China.
Objective: To explore the quantitative analysis results of different patterns of chest computed tomography (CT) in patients with coronavirus infection and its relationship with viral load and pathophysiological status.
Methods: A retrospective clinical cohort study was conducted. Patients with coronavirus infection admitted to Qingdao Municipal Hospital from June 9 to 15, 2023 (all patients underwent chest CT examination within 24 hours after diagnosis) were enrolled.
Thromboprophylaxis in patients with locally advanced cervical cancer treated with chemoradiation and brachytherapy.
Gynecol Oncol
January 2025
Department of Radiation-Oncology, Catharina Hospital, Eindhoven, the Netherlands.
Objective: To determine the incidence of clinical and subclinical venous thromboembolic events (VTE) in patients with locally advanced cervical cancer (LACC) treated with high-dose thromboprophylaxis during definitive chemoradiation and brachytherapy.
Methods: A prospective observational study was undertaken from August 2021 to December 2023 in patients with primary LACC treated with definitive chemoradiation in two Dutch tertiary hospitals. Patients received high-dose thromboprophylaxis during chemoradiation and brachytherapy.
A Nomogram to Predict Mortality in Patients With Severe Oral and Maxillofacial Space Infections.
Oral Dis
January 2025
Department of Oral Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Objective: This study aimed to explore the risk factors for death in extremely severe oral and maxillofacial space infection (OMSI) patients and to use these findings to establish a nomogram model that can be used to predict individual patient prognosis.
Methods: Patients with extremely severe OMSI seen between 2020 and 2024 were enrolled (N = 102). Univariate and multivariate logistic regression were used to analyse the associations between clinical factors and the risk of death, and a nomogram was developed to visualise the model.
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