ABSTRACT
Although pulmonary events are considered to be frequently associated with malignant haemopathies, they have been sparsely studied in the specific context of myelodysplastic syndromes (MDS). We aimed to describe their different types, their relative proportions and their relative effects on overall survival (OS). We conducted a multicentre retrospective cohort study. Patients with MDS (diagnosed according to the 2016 WHO classification) and pulmonary events were included. The inclusion period was 1 January 2007 to 31 December 2017 and patients were monitored until August 2019. Fifty-five hospitalized patients were included in the analysis. They had 113 separate pulmonary events. Thirteen patients (23.6%) had a systemic autoimmune disease associated with MDS. Median age at diagnosis of MDS was 77 years. Median time to onset of pulmonary events was 13 months. Pulmonary events comprised: 70 infectious diseases (62%); 27 interstitial lung diseases (23.9%), including 13 non-specific interstitial pneumonias and seven secondary organizing pneumonias or respiratory bronchiolitis-interstitial lung diseases; 10 pleural effusions (8.8%), including four cases of chronic organizing pleuritis with exudative effusion; and six pulmonary hypertensions (5.3%). The median OS of the cohort was 29 months after MDS diagnosis but OS was only 10 months after a pulmonary event. The OS was similar to that of the general myelodysplastic population. However, the occurrence of a pulmonary event appeared to be either an accelerating factor of death or an indicator for the worsening of the underlying MDS in our study. More than a third of pulmonary events were non-infectious and could be systemic manifestations of MDS.
ABSTRACT
Necrotizing pneumonia induced by Panton-Valentine leukocidin-secreting Staphylococcus aureus is a rare but life-threatening infection that has been described in patients after they had influenza. We report a fatal case of this superinfection in a young adult who had coronavirus disease.
Subject(s)
Bacterial Toxins/biosynthesis , Betacoronavirus/pathogenicity , Coronavirus Infections/complications , Exotoxins/biosynthesis , Leukocidins/biosynthesis , Necrosis/complications , Pneumonia, Staphylococcal/complications , Pneumonia, Viral/complications , Staphylococcus aureus/pathogenicity , Adult , Anti-Bacterial Agents/therapeutic use , Betacoronavirus/physiology , COVID-19 , COVID-19 Testing , Cefotaxime/therapeutic use , Clindamycin/therapeutic use , Clinical Laboratory Techniques/methods , Coronavirus Infections/diagnosis , Coronavirus Infections/therapy , Fatal Outcome , Humans , Linezolid/therapeutic use , Male , Metronidazole/therapeutic use , Necrosis/diagnosis , Necrosis/therapy , Pandemics , Pneumonia, Staphylococcal/diagnosis , Pneumonia, Staphylococcal/therapy , Pneumonia, Viral/diagnosis , Pneumonia, Viral/therapy , Respiration, Artificial , SARS-CoV-2 , Spiramycin/therapeutic use , Staphylococcus aureus/drug effects , Tomography, X-Ray ComputedABSTRACT
The radiologic community is rapidly integrating a revolution that has not fully entered daily practice. It necessitates a close collaboration between computer scientists and radiologists to move from concepts to practical applications. This article reviews the current littérature on machine learning and deep neural network applications in the field of pulmonary embolism, chronic thromboembolic pulmonary hypertension, aorta, and chronic obstructive pulmonary disease.
