It was the objective of this study to confirm the hypothesis that women experience an increased risk of pulmonary embolism (PE) and/or thromboembolic events after long-distance air travel. We systematically reviewed the records of all patients with confirmed pulmonary embolism after arrival at Roissy-Charles-de-Gaulle (CDG) Airport (Paris, France) during a 13-year period. The incidence of PE was calculated as a function of distance travelled and gender using Bayesian conditional probabilities obtained in part from a control population of long-distance travellers arriving in French Polynesia (Tahiti). A total of 287.6 million passengers landed at CDG airport during the study period. The proportion of male to female long-distance travellers was estimated to be 50.5% to 49.5%. Overall, 116 patients experienced PE after landing [90 females (78%), 26 males (22%)]. The estimated incidence of PE was 0.61 (0.61-0.61) cases per million passengers in females and 0.2 (0.20-0.20) in males, and reached 7.24 (7.17-7.31) and 2.35 (2.33-2.38) cases, respectively, in passengers travelling over 10,000 km. Our study strongly suggests that there is a relationship between risk of PE after air travel and gender. This relationship needs to be confirmed in order to develop the best strategy for prophylaxis.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1160/TH09-06-0407 | DOI Listing |
J Cardiothorac Surg
January 2025
Réanimation Médicale et Chirurgicale, CHU de Guadeloupe, Les Abymes, Guadeloupe, 97139, France.
Background: The medico-surgical management of cardiac tumors when there is a suspicion of malignancy is complex. Moreover, in a critically ill setting, the choice of diagnostic tools seems crucial.
Case Presentation: We present the case of a sixty-four-year-old patient with no prior medical history who was admitted to the intensive care unit with obstructive shock secondary to a right heart mass and pulmonary embolism.
Sci Rep
January 2025
Department of Respiratory and Critical Care Medicine, Changhai Hospital, The Second Military Medical University, Shanghai, People's Republic of China.
In recent years, large amounts of researches showed that pulmonary embolism (PE) has become a common disease, and PE remains a clinical challenge because of its high mortality, high disability, high missed and high misdiagnosed rates. To address this, we employed an artificial intelligence-based machine learning algorithm (MLA) to construct a robust predictive model for PE. We retrospectively analyzed 1480 suspected PE patients hospitalized in West China Hospital of Sichuan University between May 2015 and April 2020.
View Article and Find Full Text PDFBMJ Case Rep
January 2025
Department of Pulmonary Medicine, Sri Ramachandra Medical College and Research Institute, Chennai, Tamil Nadu, India.
Curr Probl Cardiol
January 2025
Cardiology, RVM Institute of Medical Sciences and Research Center, Laxmakkapally, India.
Background: Diastolic wall strain (DWS), also referred to as right ventricular (RV) dysfunction, is a significant predictor of pulmonary embolism (PE) and heart failure (HF). Rooted in linear elastic theory, DWS reflects decreased wall thinning during diastole, indicating reduced left ventricular (LV) compliance and increased diastolic stiffness. Elevated diastolic stiffness is associated with worse outcomes, particularly in PE and HF with preserved ejection fraction (HFpEF).
View Article and Find Full Text PDFJ Cardiothorac Surg
January 2025
Department of Respiratory Medicine, Anhui Medical University Clinical College of Chest & Anhui Chest Hospital, Hefei, 230022, People's Republic of China.
Pulmonary embolism (PE), a form of venous thromboembolism, is a frequently observed complication in malignancies, with a notably high incidence in individuals with lung cancer. The presence of PE markedly reduces the quality of life and has a significant impact on the prognosis of those diagnosed with both lung cancer and PE. As a result, timely diagnosis and intervention are of paramount importance.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!