Background: Influenza vaccines are the main tool to prevent morbidity and mortality of the disease; however, egg adaptations associated with the choice of the manufacturing process may reduce their effectiveness. This study aimed to estimate the impact of egg adaptations and antigenic drift on the effectiveness of trivalent (TIV) and quadrivalent (QIV) influenza vaccines. Methods: Nine experts in influenza virology were recruited into a Delphi-style exercise. In the first round, the experts were asked to answer questions on the impact of antigenic drift and egg adaptations on vaccine match (VM) and influenza vaccine effectiveness (IVE). In the second round, the experts were presented with the data from a systematic literature review on the same subject and aggregated experts’ responses to round one questions. The experts were asked to review and confirm or amend their responses before the final summary statistics were calculated. Results: The experts estimated that, across Europe, the egg adaptations reduce, on average, VM to circulating viruses by 7–21% and reduce IVE by 4–16%. According to the experts, antigenic drift results in a similar impact on VM (8–24%) and IVE (5–20%). The highest reduction in IVE was estimated for the influenza virus A(H3N2) subtype for the under 65 age group. When asked about the frequency of the phenomena, the experts indicated that, on average, between the 2014 and 19 seasons, egg adaptation and antigenic drift were significant enough to impact IVE that occurred in two and three out of five seasons, respectively. They also agreed that this pattern is likely to reoccur in future seasons. Conclusions: Expert estimates suggest there is a potential for 9% on average (weighted average of “All strains” over three age groups adjusted by population size) and up to a 16% increase in IVE (against A(H3N2), the <65 age group) if egg adaptations that arise when employing the traditional egg-based manufacturing process are avoided.

ObjectiveThe objective of this study was to examine how COPD patients were classified by the Global Initiative for Chronic Obstructive Lung Disease (GOLD) spirometry-based severity system and the distribution of COPD severity using the new GOLD 2011 assessment framework.Materials and methodsThis was an observational, retrospective cohort study conducted in a single tertiary center on a prospective database, which aimed to evaluate the prevalence, incidence, severity, and comorbidities of COPD. Inclusion criteria were age ≥40 years and COPD diagnosis according to GOLD 2007 classification. Clinical factors were compared between the categories in GOLD 2007 and 2011 groups by using the χ2 test for categorical data and the analysis of variance for continuous data.ResultsIn total, 420 COPD patients were included in the analysis. The distribution of patients into GOLD 2007 categories was as follows: 6.4% (n=27) of them were classified into subgroup I, 42.1% (n=177) into subgroup II, 37.9% (n=159) into subgroup III, and 13.6% (n=57) into subgroup IV. The distribution of patients into GOLD 2011 categories was as follows: 16.4% (n=69) of them were classified into subgroup A (low risk and fewer symptoms), 32.1% (n=135) into subgroup B (low risk and more symptoms), 21.6% (n=91) into subgroup C (high risk and fewer symptoms), and 29.7% (n=125) into subgroup D (high risk and more symptoms). After the application of the new GOLD 2011 (modified Medical Research Council [mMRC] system), 22% (n=94) of patients were upgraded to a higher level than their spirometry level, and 16.2% (n=68) of them were downgraded in their severity category, meaning that almost 40% of patients changed their severity assessment category. In total, 22% of patients in stage I were allocated to group B, and 35% of patients in stage IV were allocated to group C. Patients in stage III were the most frequently upgraded to a higher risk group (D), taking into account mMRC and exacerbation history.ConclusionClassifying patients using the new GOLD 2011 criteria reallocated a relevant proportion of patients to a different risk category and identified larger proportions of patients in the mildest and more severe groups compared with GOLD 2007 classification.

Background: Endothelial dysfunction is central to PAH. In this study, we simultaneously analysed circulating levels of endothelial microvesicles (EMVs) and progenitor cells (PCs) in PAH and in controls, as biomarkers of pulmonary endothelial integrity and evaluated differences among PAH subtypes and as a response to treatment. Methods: Forty-seven controls and 144 patients with PAH (52 idiopathic, 9 heritable, 31 associated with systemic sclerosis, 15 associated with other connective tissue diseases, 20 associated with HIV and 17 associated with portal hypertension) were evaluated. Forty-four patients with scleroderma and 22 with HIV infection, but without PAH, were also studied. Circulating levels of EMVs, total (CD31+CD42b−) and activated (CD31+CD42b−CD62E+), as well as circulating PCs (CD34+CD133+CD45low) were measured by flow cytometry and the EMVs/PCs ratio was computed. In treatment-naïve patients, measurements were repeated after 3 months of PAH therapy. Results: Patients with PAH showed higher numbers of EMVs and a lower percentage of PCs, compared with healthy controls. The EMV/PC ratio was increased in PAH patients, and in patients with SSc or HIV without PAH. After starting PAH therapy, individual changes in EMVs and PCs were variable, without significant differences being observed as a group. Conclusion: PAH patients present disturbed vascular homeostasis, reflected in changes in circulating EMV and PC levels, which are not restored with PAH targeted therapy. Combined measurement of circulating EMVs and PCs could be foreseen as a potential biomarker of endothelial dysfunction in PAH.

There is a wide range of sequelae affecting COVID-19 survivors, including impaired physical capacity. These sequelae can affect the quality of life and return to work of the active population. Therefore, one of the pillars of following-up is the evaluation of physical capacity, which can be assessed with field tests (such as the six-minute walk test, the one-minute standing test, the Chester step test, and the shuttle walking test) or laboratory tests (such as the cardiopulmonary exercise test). These tests can be performed in different contexts and have amply demonstrated their usefulness in the assessment of physical capacity both in post-COVID-19 patients and in other chronic respiratory, metabolic, cardiologic, or neurologic diseases. However, when traditional tests cannot be performed, physical function can be a good substitute, especially for assessing the effects of an intervention. For example, the Short Physical Performance Battery assessment and the Timed Up and Go assessment are widely accepted in older adults. Thus, the test should be chosen according to the characteristics of each subject.