Prevalence of Asthma Characteristics in COPD Patients in a Dutch Well-Established Asthma/COPD Service for Primary Care

Purpose: Primary care COPD guidelines indicate that COPD patients with asthma characteristics should be treated as having asthma. This study aims to describe the prevalence of asthma characteristics in patients with a pulmonologist-confirmed working diagnosis of COPD or ACO. Patients and Methods: This retrospective cross-sectional study used real-life data (collected between 2007 and 2017) from a Dutch asthma/COPD-service, a structured web-based system in which pulmonologists support general practitioners in their diagnosis of patients with suspicion of obstructive lung disease. The prevalence of asthma characteristics (history of asthma, atopy, symptoms, and reversibility) and blood eosinophil (Eos) counts were assessed in patients with a working diagnosis of COPD or ACO. Results: Of the 14,141 patients, ≥40 years in the dataset, 4475 (31.6%) were diagnosed with asthma, 3532 (25.0%) with COPD, and 1276 (9.0%) with ACO. Asthma characteristics were present in 65.6% (n=1956) of the COPD and 90.9% (n=1059) of the ACO patients. Eos counts of ≥ 300 cells per μL were found in 35.7% (n=924) of the COPD patients and 35.3% (n=341) of the ACO patients. Conclusion: In this group of COPD and ACO patients remotely diagnosed by pulmonologists, a substantial proportion would be considered to have asthma characteristics according to the guidelines. This may explain the high number of inhaled corticosteroid (ICS) prescriptions found in primary care COPD patients. Prospective studies are necessary to identify patients who may or may not benefit from ICS containing treatment. Hence, personalized care in primary care can be optimized

Aeroallergen sensitisation for detecting asthma in primary care:a diagnostic test accuracy study

peer reviewe

Budesonide/formoterol maintenance and reliever therapy in primary care asthma management: effects on bronchial hyperresponsiveness and asthma control

Background: The management of asthma has changed since the introduction of budesonide/formoterol (Symbicort (R)) as both maintenance and reliever therapy (SMART). SMART and its effects on bronchial hyperresponsiveness (BHR) have not been studied in primary care. Aims: To compare the effects of SMART and guideline-driven usual care (UC) on BHR and clinical asthma severity in primary care practice. Methods: Patients with mild-to-moderate stable asthma were randomised to receive SMART treatment (n=54) (budesonide/formoterol 80/4.5 mu g Turbuhaler (R), two puffs once daily and extra inhalations as needed) or UC treatment (n=48) for 12 months. Diary data, Asthma Control Questionnaire scores, forced expiratory volume in 1 second (FEV1), and peak expiratory flow (PEE) measurements were collected during run-in and after 1, 3, 6, and 12 months of treatment. BHR, measured as the dose of histamine provoking a fall in FEV1 of 20% (PD20-histamine), was determined at randomisation and after 12 months. Results: One hundred and two patients with asthma participated in the study. The change in PD20-histamine during the study was not significantly different between the SMART and UC groups (p=0.26). The mean inhaled corticosteroid (ICS) dose was 326 mu g beclomethasone dipropionate (BDP) equivalents/day (95% Cl 254 to 399) with SMART, which was significantly lower (p Conclusions: Despite a 59% lower dose of ICS, BHR and other clinical outcomes remained stable during SMART treatment while PEF values improved. (C) 2012 Primary Care Respiratory Society UK. All rights reserved. R Riemersma et al. Prim Care Respir J 2012; 21(1): 50-56 http://dx.doi.org/10.4104/pcrj.2011.0009

Automatic construction of feedforward/recurrent fuzzy systems by clustering-aided simplex particle swarm optimization

This paper proposes a new approach for automating the structure and parameter learning of fuzzy systems by clustering-aided simplex particle swarm optimization, called CSPSO. Unlike most evolutionary fuzzy systems, where the structure of the fuzzy system is assigned in advance, an on-line fuzzy clustering approach is proposed for system structure learning. This structure learning not only helps determine the number of rules automatically, but also avoids the generation of highly similar fuzzy sets on each input variable. In addition, it improves subsequent parameter learning performance by assigning suitable initial locations of the fuzzy sets on each input variable. Once a new rule is generated, the corresponding parameters are further tuned by the hybrid of the simplex method and particle swarm optimization (PSO). In CSPSO, each fuzzy system corresponds to a particle in PSO, and the idea of the simplex method is incorporated to improve PSO searching performance. To verify the performance of CSPSO, two simulations on feedforward fuzzy systems design are performed. In addition, design of a recurrent fuzzy controller for a practical experiment on water bath temperature control is performed. Comparisons with other design approaches are also made in these examples. (c) 2007 Elsevier B.V. All rights reserved

An Economic Evaluation of Budesonide/Formoterol for Maintenance and Reliever Treatment in Asthma in General Practice

Introduction: In budesonide/formoterol (Symbicort (R) Turbuhaler (R), AstraZeneca, Lund, Sweden) maintenance and reliever therapy ( SMART), patients with asthma take a daily maintenance dose of budesonide/formoterol, with the option of taking additional doses for symptom relief instead of a short-acting beta(2)-agonist ( SABA). This study assesses the cost-effectiveness of SMART compared with usual care in patients with mild-to-moderate persistent asthma treated by general practitioners in the Netherlands from a societal perspective. Methods: The study was linked to a randomized, active-controlled, open-label, multicenter, 12-month clinical trial, with a prospective collection of resource use. One hundred and two patients >= 18 years with mild-to-moderate persistent asthma and daily inhaled corticosteroids (ICS) prior to the trial were included. SMART was given as two inhalations of budesonide/formoterol (100/6 mu g) once daily, plus additional doses as needed. The control group was treated according to guidelines, which prescribe medium daily doses of ICS plus an SABA if needed. A long-acting beta(2)-agonist (LABA) is added if necessary. Effectiveness was measured as the proportion of asthma-control days, Asthma Control Questionnaire (ACQ) scores, the net proportion of patients with relevant ACQ improvement, and the proportion of well-controlled patients. Costs included asthma medication, physician contacts, and absence from work. Results: Mean total costs for SMART were (sic)134.81 lower (95% CI: -(sic)439.48; (sic)44.85). Production losses were (sic)94.10 ( 95% CI: -(sic)300.60; (sic)0.29) lower for SMART ((sic)10.77 vs. (sic)104.87). No significant differences in health outcomes were seen, with 3.81 fewer asthma-control days per patient-year for SMART (95% CI: -36.8; 30.8), a 0.049 better ACQ score (95% CI: -0.21; 0.29), a 5.8% larger net proportion of improved patients (95% CI: -15.6%; 27.3%), and a 2.1% (95% CI: -25.5; 20.8%) smaller increase in the proportion of well-controlled patients. Conclusions: Treating primary care patients with mild-to-moderate persistent asthma with SMART instead of ICS plus bronchodilators does not affect health outcomes and does not increase costs; therefore, is likely to be an alternative for guideline-directed treatment, from a health and economic perspective

Phenotyping airways disease by cluster analysis in primary care:6 distinct clusters identified

Current obstructive airways disease classification does not sufficiently reflect disease patterns. Cluster analysis is one of the promising approaches to develop a new taxonomy. The majority of current phenotyping studies focus on severe asthma or COPD. Aim To identify phenotypes in a broad spectrum of obstructive airways disease in a primary care population. Methods 952/9225 cases with full data on 13 variables reflecting physiological,lung function,laboratory and questionnaire data from a structured primary care Asthma/COPD service were used to identify clusters using hierarchical clustering. Optimal number of clusters was established by silhouette stats and clinical judgement. Decision rules developed were used to allocate the remaining. Results The optimal number of clusters was 6. 5424 cases had sufficient data to be allocated by the allocation rules based, in order of importance,on smoke exposure,FEV1%pred,ACQ,Age of onset,hyperactivity,bronchitis score,CCQ functional status,FEV1/FVC ratio,CCQ mental status. The clusters identified in order of increasing smoke exposure are:A-Overweight,non smoking,normal lung function,uncertain diagnosis (15% of patients);B-Younger onset allergic asthma(39%);C-Younger onset allergic asthmatic smokers with bronchitis(15%);D-Adult onset,high symptomatic asthma(6%); E-Smoking Non allergic asthma/COPD overlap with obesity and eosinophilia(9%);and F-late onset smoking COPD(17%). Conclusion Six distinct groups could be identified in this primary care population using cluster analysis