Outcomes of listing for lung and heart–lung transplantation in pulmonary hypertension: comparative experience in France and the UK

\ua9 The authors 2024.Background Lung or heart–lung transplantation (LT/HLT) for severe pulmonary hypertension (PH) as the primary disease indication carries a high risk of waiting list mortality and post-transplant complications. France and the UK both have coordinated PH patient services but with different referral pathways for accessing LT services. Methods We conducted a comparative analysis of adult PH patients listed for LT/HLT in the UK and France. Results We included 211 PH patients in France (2006–2018) and 170 in the UK (2010–2019). Cumulative incidence of transplant, delisting and waiting list death within 3 years were 81%, 4% and 11% in France versus 58%, 10% and 15% in the UK (p<0.001 for transplant and delisting; p=0.1 for death). Median nonpriority waiting time was 45 days in France versus 165 days in the UK (p<0.001). High-priority listing occurred in 54% and 51% of transplanted patients respectively in France and the UK (p=0.8). Factors associated with achieving transplantation related to recipients’ height, male sex, clinical severity and priority listing status. 1-year post-transplant survival was 78% in France and 72% in the UK (p= 0.04). Conclusion Access to transplantation for PH patients is better in France than in the UK where more patients were delisted due to clinical deterioration because of longer waiting time. High rates of priority listing occurred in both countries. Survival for those achieving transplantation was slightly better in France. Ensuring optimal outcomes after transplant listing for PH patients is challenging and may involve early listing of higher risk patients, increasing donor lung utilisation and improving allocation rules for these specific patients

Nocardia farcinica lung infection in a patient with cystic fibrosis: a case report

<p>Abstract</p> <p>Introduction</p> <p>Respiratory tract infections are the major causes of morbidity and mortality in patients with cystic fibrosis. <it>Nocardia </it>are rarely implicated in these infections and few reports of the involvement of this species are found in the literature.</p> <p>Case presentation</p> <p>We describe a case of lung infection followed by chronic colonization of trimethoprim and sulfamethoxazole resistant <it>Nocardia farcinica </it>in a patient with cystic fibrosis. The chronic colonization of this uncommon bacterium in patients with cystic fibrosis was proved using a newly developed real-time polymerase chain reaction assay, which indicates that this bacterium, despite treatment, is difficult to eradicate.</p> <p>Conclusion</p> <p>Our case report confirms that this organism can be recovered in persons with cystic fibrosis. Its eradication is necessary especially if the patient is to undergo lung transplantation.</p

Выявление понятий и их взаимосвязей в рамках технологии контент-мониторинга

Приведены подходы к решению проблемы выявления фактографической информации из неструктурированных текстовых потоков. Описаны технологические решения, позволяющие извлекать из полнотекстовых документов такие понятия как фирмы, фамилии, географические названия и т.п., а также выявлять силу их взаимосвязей на основе применения двух алгоритмов. Первый из этих алгоритмов основывается на учете совместного вхождения понятий в одни и те же документы, а второй на учете общего для рассматриваемых понятий контекста.Наведено підходи до вирішення проблеми виявлення фактографічної інформації з неструктурованих текстових потоків. Описано технологічні рішення, що дозволяють добути з повнотекстових документів такі поняття як фірми, прізвища, географічні назви тощо, а також виявляти силу їхніх взаємозв’язків на базі застосування двох алгоритмів. Перший з цих алгоритмів базується на врахуванні спільного входження понять до одних і тих самих документів, а другий — на врахуванні загального для понять, що розглядаються, контексту.Approaches to the solution of a problem of revealing factual information from unstructured text flows are given. The technological solutions, allowing to take from text-through documents such concepts as a firm, a surname, place names, etc., and also to reveal force of their interrelations on the basis of application of two algorithms are described. The first of these algorithms is based on the account of joint concepts occurrence in the same documents, and the second one on the account of the context common for considered concepts