Background: The coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Prediction models that accurately estimate mortality risk in hospitalized patients could assist... Show moreBackground: The coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Prediction models that accurately estimate mortality risk in hospitalized patients could assist medical staff in treatment and allocating limited resources. Aims: To externally validate two promising previously published risk scores that predict in-hospital mortality among hospitalized COVID-19 patients. Methods: Two prospective cohorts were available; a cohort of 1028 patients admitted to one of nine hospitals in Lombardy, Italy (the Lombardy cohort) and a cohort of 432 patients admitted to a hospital in Leiden, the Netherlands (the Leiden cohort). The endpoint was in-hospital mortality. All patients were adult and testedCOVID-19 PCR-positive. Model discrimination and calibration were assessed. Results: The C-statistic of the 4C mortality score was good in the Lombardy cohort (0.85, 95CI: 0.82-0.89) and in the Leiden cohort (0.87, 95CI: 0.80-0.94). Model calibration was acceptable in the Lombardy cohort but poor in the Leiden cohort due to the model systematically overpredicting the mortality risk for all patients. The C -sta-tistic of the CURB-65 score was good in the Lombardy cohort (0.80, 95CI: 0.75-0.85) and in the Leiden cohort (0.82, 95CI: 0.76-0.88). The mortality rate in the CURB-65 development cohort was much lower than the mortality rate in the Lombardy cohort. A similar but less pronounced trend was found for patients in the Leiden cohort. Conclusion: Although performances did not differ greatly, the 4C mortality score showed the best performance. However, because of quickly changing circumstances, model recalibration may be necessary before using the 4C mortality score. Show less
Hassan, S.; Ferrari, B.; Rossio, R.; Mura, V. la; Artoni, A.; Gualtierotti, R.; ... ; COVID-19 Network Working Grp 2022
Background The coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Identification of predictors of poor outcomes will assist medical staff in treatment and allocating... Show moreBackground The coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Identification of predictors of poor outcomes will assist medical staff in treatment and allocating limited healthcare resources. Aims The primary aim was to study the value of D-dimer as a predictive marker for in-hospital mortality. Methods This was a cohort study. The study population consisted of hospitalized patients (age >18 years), who were diagnosed with COVID-19 based on real-time PCR at 9 hospitals during the first COVID-19 wave in Lombardy, Italy (Feb-May 2020). The primary endpoint was in-hospital mortality. Information was obtained from patient records. Statistical analyses were performed using a Fine-Gray competing risk survival model. Model discrimination was assessed using Harrell's C-index and model calibration was assessed using a calibration plot. Results Out of 1049 patients, 507 patients (46%) had evaluable data. Of these 507 patients, 96 died within 30 days. The cumulative incidence of in-hospital mortality within 30 days was 19% (95CI: 16%-23%), and the majority of deaths occurred within the first 10 days. A prediction model containing D-dimer as the only predictor had a C-index of 0.66 (95%CI: 0.61-0.71). Overall calibration of the model was very poor. The addition of D-dimer to a model containing age, sex and co-morbidities as predictors did not lead to any meaningful improvement in either the C-index or the calibration plot. Conclusion The predictive value of D-dimer alone was moderate, and the addition of D-dimer to a simple model containing basic clinical characteristics did not lead to any improvement in model performance. Show less
Little is known about the characteristics and treatments of patients with severe asthma across Europe, but both are likely to vary. This is the first study in the European Respiratory Society... Show moreLittle is known about the characteristics and treatments of patients with severe asthma across Europe, but both are likely to vary. This is the first study in the European Respiratory Society Severe Heterogeneous Asthma Research collaboration, Patient-centred (SHARP) Clinical Research Collaboration and it is designed to explore these variations. Therefore, we aimed to compare characteristics of patients in European severe asthma registries and treatments before starting biologicals.This was a cross-sectional retrospective analysis of aggregated data from 11 national severe asthma registries that joined SHARP with established patient databases.Analysis of data from 3236 patients showed many differences in characteristics and lifestyle factors. Current smokers ranged from 0% (Poland and Sweden) to 9.5% (Belgium), mean body mass index ranged from 26.2 (Italy) to 30.6 kg.m(-2) (the UK) and the largest difference in mean pre-bronchodilator forced expiratory volume in 1 s % predicted was 20.9% (the Netherlands versus Hungary). Before starting biologicals patients were treated differently between countries: mean inhaled corticosteroid dose ranged from 700 to 1335 mu g.day(-1) between those from Slovenia versus Poland when starting anti-interleukin (IL)5 antibody and from 772 to 1344 mu g.day(-1) in those starting anti-IgE (Slovenia versus Spain). Maintenance oral corticosteroid use ranged from 21.0% (Belgium) to 63.0% (Sweden) and from 9.1% (Denmark) to 56.1% (the UK) in patients starting anti-IL-5 and anti-IgE, respectively.The severe asthmatic population in Europe is heterogeneous and differs in both clinical characteristics and treatment, often appearing not to comply with the current European Respiratory Society/American Thoracic Society guidelines definition of severe asthma. Treatment regimens before starting biologicals were different from inclusion criteria in clinical trials and varied between countries. Show less
Background: Mobile technology may help to better understand the adherence to treatment. MASK-rhinitis (Mobile Airways Sentinel NetworK for allergic rhinitis) is a patient-centred ICT system. A... Show moreBackground: Mobile technology may help to better understand the adherence to treatment. MASK-rhinitis (Mobile Airways Sentinel NetworK for allergic rhinitis) is a patient-centred ICT system. A mobile phone app (the Allergy Diary) central to MASK is available in 22 countries.Objectives: To assess the adherence to treatment in allergic rhinitis patients using the Allergy Diary App.Methods: An observational cross-sectional study was carried out on all users who filled in the Allergy Diary from 1 January 2016 to 1 August 2017. Secondary adherence was assessed by using the modified Medication Possession Ratio (MPR) and the Proportion of days covered (PDC) approach.Results: A total of 12143 users were registered. A total of 6949 users reported at least one VAS data recording. Among them, 1887 users reported >= 7 VAS data. About 1195 subjects were included in the analysis of adherence. One hundred and thirty-six (11.28%) users were adherent (MPR >= 70% and PDC <= 1.25), 51 (4.23%) were partly adherent (MPR >= 70% and PDC = 1.50) and 176 (14.60%) were switchers. On the other hand, 832 (69.05%) users were non-adherent to medications (MPR <70%). Of those, the largest group was non-adherent to medications and the time interval was increased in 442 (36.68%) users.Conclusion and clinical relevance: Adherence to treatment is low. The relative efficacy of continuous vs on-demand treatment for allergic rhinitis symptoms is still a matter of debate. This study shows an approach for measuring retrospective adherence based on a mobile app. This also represents a novel approach for analysing medication-taking behaviour in a real-world setting. Show less
Allergic Rhinitis and its Impact on Asthma (ARIA) has evolved from a guideline by using the best approach to integrated care pathways using mobile technology in patients with allergic rhinitis (AR)... Show moreAllergic Rhinitis and its Impact on Asthma (ARIA) has evolved from a guideline by using the best approach to integrated care pathways using mobile technology in patients with allergic rhinitis (AR) and asthma multimorbidity. The proposed next phase of ARIA is change management, with the aim of providing an active and healthy life to patients with rhinitis and to those with asthma multimorbidity across the lifecycle irrespective of their sex or socioeconomic status to reduce health and social inequities incurred by the disease. ARIA has followed the 8-step model of Kotter to assess and implement the effect of rhinitis on asthma multimorbidity and to propose multimorbid guidelines. A second change management strategy is proposed by ARIA Phase 4 to increase self-medication and shared decision making in rhinitis and asthma multimorbidity. An innovation of ARIA has been the development and validation of information technology evidence-based tools (Mobile Airways Sentinel Network [MASK]) that can inform patient decisions on the basis of a self-care plan proposed by the health care professional. Show less
There is a marked increase in the development and use of electronic nicotine delivery systems or electronic cigarettes (ECIGs). This statement covers electronic cigarettes (ECIGs), defined as ... Show moreThere is a marked increase in the development and use of electronic nicotine delivery systems or electronic cigarettes (ECIGs). This statement covers electronic cigarettes (ECIGs), defined as "electrical devices that generate an aerosol from a liquid" and thus excludes devices that contain tobacco. Database searches identified published articles that were used to summarise the current knowledge on the epidemiology of ECIG use; their ingredients and accompanied health effects; second-hand exposure; use of ECIGs for smoking cessation; behavioural aspects of ECIGs and social impact; in vitro and animal studies; and user perspectives.ECIG aerosol contains potentially toxic chemicals. As compared to conventional cigarettes, these are fewer and generally in lower concentrations. Second-hand exposures to ECIG chemicals may represent a potential risk, especially to vulnerable populations. There is not enough scientific evidence to support ECIGs as an aid to smoking cessation due to a lack of controlled trials, including those that compare ECIGs with licenced stop-smoking treatments. So far, there are conflicting data that use of ECIGs results in a renormalisation of smoking behaviour or for the gateway hypothesis. Experiments in cell cultures and animal studies show that ECIGs can have multiple negative effects. The long-term effects of ECIG use are unknown, and there is therefore no evidence that ECIGs are safer than tobacco in the long term. Based on current knowledge, negative health effects cannot be ruled out. Show less
