CUTE EXACERBATIONS OF chronic obstructive pulmonary disease (COPD) are a risk factor for disease deterioration, 1 and patients with frequent exacerbations have increased mortality. 2 In the general practitioner-based Swiss COPD cohort, approximately 23% to 25% of patients with COPD experienced exacerbations requiring pharmacological treatment within 1 year. 3,4 International guidelines and systematic reviews advocate systemic glucocorticoid therapy in the management of acute exacerbations of COPD (eg, 30-40 mg of oral prednisolone for 10-14 days). 5-7 Randomized clinical Author Affiliations are listed at the end of this article.
BackgroundThe burden of asthma and COPD among patients is high and people affected are frequently hospitalized due to exacerbations. There are numerous reasons for the lack of disease control in asthma and COPD patients. It is associated with non-adherence to guidelines on the part of the health care provider and with poor inhalation technique and/or non-adherence to the prescribed treatment plan by the patient. This study aims to present data on inhaler technique and its impact on quality of life (QoL) and symptom control in a typical population of patients with chronic lung disease from a randomized controlled trial on medication adherence.MethodsFor this cross-sectional analysis, 165 asthma and COPD patients were analyzed. Correct application of inhaler devices was tested using pre-defined checklists for each inhaler type. QoL and symptom control were investigated using COPD Assessment Test (CAT) and Asthma Control Test (ACT). Spirometry was used to measure forced vital capacity (FVC) and forced expiratory volume in one second (FEV1).ResultsOverall, incorrect inhalation technique ranged from 0 to 53% depending on the type of inhaler. COPD patients with incorrect device application had a higher CAT sum score compared to those with a correct device application (P = .02). Moreover, COPD patients with incorrect device application were more likely to suffer from cough (P = .03) and were more breathless while walking uphill or a flight of stairs (P = .02). While there was no significance found in asthma patients, COPD patients who used their devices correctly had a significantly better mean FEV1% predicted at baseline compared to those who applied their devices incorrectly (P = .04).ConclusionsCorrect inhalation of prescribed medication is associated with improved health status and lung function. These findings should encourage health professionals to provide instructions on correct inhalation technique and to regularly re-evaluate the patients’ inhalation technique.Trial registrationClinicalTrials.gov: NCT0238672, Registered 14 February 2014.
Several studies have demonstrated that fully automated pattern recognition methods applied to structural magnetic resonance imaging (MRI) aid in the diagnosis of dementia, but these conclusions are based on highly preselected samples that significantly differ from that seen in a dementia clinic. At a single dementia clinic, we evaluated the ability of a linear support vector machine trained with completely unrelated data to differentiate between Alzheimer’s disease (AD), frontotemporal dementia (FTD), Lewy body dementia, and healthy aging based on 3D-T1 weighted MRI data sets. Furthermore, we predicted progression to AD in subjects with mild cognitive impairment (MCI) at baseline and automatically quantified white matter hyperintensities from FLAIR-images. Separating additionally recruited healthy elderly from those with dementia was accurate with an area under the curve (AUC) of 0.97 (according to Fig. 4). Multi-class separation of patients with either AD or FTD from other included groups was good on the training set (AUC > 0.9) but substantially less accurate (AUC = 0.76 for AD, AUC = 0.78 for FTD) on 134 cases from the local clinic. Longitudinal data from 28 cases with MCI at baseline and appropriate follow-up data were available. The computer tool discriminated progressive from stable MCI with AUC = 0.73, compared to AUC = 0.80 for the training set. A relatively low accuracy by clinicians (AUC = 0.81) illustrates the difficulties of predicting conversion in this heterogeneous cohort. This first application of a MRI-based pattern recognition method to a routine sample demonstrates feasibility, but also illustrates that automated multi-class differential diagnoses have to be the focus of future methodological developments and application studies
Background: The occurrence of both chronic obstructive pulmonary disease (COPD) and obstructive sleep apnea (OSA) in an individual patient has been described as ‘overlap syndrome', which has been associated with poor prognosis. Little is known about the possible predictors of the overlap syndrome and its association with comorbidities contributing to impaired outcome. Objectives: This study aimed to evaluate the prevalence and possible predictors of the overlap syndrome and its association with comorbidities in a cohort of COPD patients. Methods: Individuals with COPD (GOLD stages I-IV, risk groups A-D) were recruited from outpatient clinics. Information on age, gender, body mass index (BMI), smoking status, Epworth sleepiness scale (ESS), COPD assessment test, comorbidities, medications and exacerbations in the past year was collected and a spirometry was performed. Participants underwent a nocturnal polygraphy using the ApneaLink™ device at home. An apnea-hypopnea index (AHI) >10 per hour was considered to indicate OSA. Results: We enrolled 177 COPD patients (112 men) with a mean age of 64 years (range 42-90), of whom 35 (20%) had an ESS score above 10. During nocturnal polygraphy, 33 patients (19%) had evidence of OSA. In multivariate analysis, BMI and pack years were positively associated with AHI, independent of other significant AHI determinants from univariate analysis. Arterial hypertension and diabetes were more common in patients with the overlap syndrome. Conclusions: Almost 20% of COPD patients also have OSA. BMI and smoking history seem to be predictors of the overlap syndrome, and these patients may be more often affected by hypertension and diabetes.
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