17
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Effect of Bronchodilator and Steroid Use on Heart Disease and Stroke Risks in a Bronchiectasis–Chronic Obstructive Pulmonary Disease Overlap Cohort: A Propensity Score Matching Study

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background: To determine the effects of bronchodilator, steroid, and anti-arrhythmia drug use on the risk of heart disease/stroke (HDS) in patients with bronchiectasis–chronic obstructive pulmonary disease overlap syndrome (BCOS).

          Methods: We retrospectively enrolled patients with BCOS (BCOS cohort, n = 1,493) and patients without bronchiectasis and chronic obstructive pulmonary disease (COPD) (non-BCOS cohort, n = 5,972). The cumulative incidence of HDS was analyzed through Cox proportional regression. We calculated adjusted hazard ratios (aHRs) and their 95% confidence intervals (CIs) for HDS after adjustments for sex, age, comorbidities, long-acting β2-agonist or long-acting muscarinic antagonist (LABAs/LAMAs) use, short-acting β2-agonist or short-acting muscarinic antagonist (SABAs/SAMAs) use, oral steroid (OSs) or inhaled corticosteroid steroid (ICSs) use, and anti-arrhythmia drugs use.

          Results: The aHR (95% CI) for HDS was 1.08 (0.28–4.06) for patients using LAMAs compared with those not using drugs. Regarding drug use days, the aHRs (95% CIs) were 32.2 (1.79–773.0), 1.85 (1.01–3.39), and 31.1 (3.25–297.80) for those with recent SABAs use, past ICSs use, and past anti-arrythmia drugs use, respectively. Regarding cumulative drug dose, the aHRs (95% CIs) were 2.12 (1.46–3.10), 3.48 (1.13–10.6), 3.19 (2.04–4.99), 28.1 (1.42–555.7), 2.09 (1.32–3.29), 2.28 (1.53–3.40), and 1.93 (1.36–2.74) for those with a low dose of SABAs, medium dose of SABAs, low dose of SAMAs, low dose of ICSs, medium dose of ICSs, low dose of OSs, and medium dose of OSs, respectively.

          Conclusions: Compared with patients without bronchiectasis and COPD, BCOS patients with recent SABAs, past ICSs, and past anti-arrhythmia drugs use; a low or medium SABAs ICSs, and OSs dose; and a low SAMAs dose had a higher risk of HDS. LAMAs were not associated with HDS.

          Related collections

          Most cited references35

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Validation of Acute Myocardial Infarction Cases in the National Health Insurance Research Database in Taiwan

          Background The aim of this study was to determine the validity of acute myocardial infarction (AMI) diagnosis coding in the National Health Insurance Research Database (NHIRD) by cross-comparisons of discharge diagnoses listed in the NHIRD with those in the medical records obtained from a medical center in Taiwan. Methods This was a cross-sectional study comparing records in the NHIRD and discharge notes in one medical center (DNMC) in the year 2008. Positive predictive values (PPVs) for AMI diagnoses were evaluated by reviewing the relevant clinical and laboratory data recorded in the discharge notes of the medical center. Agreement in comorbidities, cardiac procedures, and antiplatelet agent (aspirin or clopidogrel) prescriptions between the two databases was evaluated. Results We matched 341 cases of AMI hospitalizations from the two databases, and 338 cases underwent complete chart review. Of these 338 AMI cases, 297 were confirmed with clinical and lab data, which yielded a PPV of 0.88. The consistency rate for coronary intervention, stenting, and antiplatelet prescription at admission was high, yielding a PPV over 0.90. The percentage of consistency in comorbidity diagnoses was 95.9% (324/338) among matched AMI cases. Conclusions The NHIRD appears to be a valid resource for population research in cardiovascular diseases.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Problem of immortal time bias in cohort studies: example using statins for preventing progression of diabetes.

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Advances in bronchiectasis: endotyping, genetics, microbiome, and disease heterogeneity

              Bronchiectasis is a condition characterized by pathological dilation of the airways. More specifically, the radiographic demonstration of airways enlargement is the common feature of a heterogeneous set of conditions and clinical presentations. There are no approved therapies for the condition other than for bronchiectasis caused by cystic fibrosis. The heterogeneity of bronchiectasis is the major challenge in clinical practice and the major reason for difficulty in achieving endpoints in clinical trials. Recent observations have improved our knowledge regarding bronchiectasis such that it may be more effective to describe patients according to a heterogeneous group of endotypes, defined by a distinct functional or pathobiological mechanism, or clinical phenotypes, defined by relevant and common features of disease. In doing so, we may finally develop more specific therapies needed to effectively treat our patients. Here we describe some of the recent advances in endotyping, genetics and disease heterogeneity of bronchiectasis including observations related to the microbiome.
                Bookmark

                Author and article information

                Contributors
                Journal
                Front Pharmacol
                Front Pharmacol
                Front. Pharmacol.
                Frontiers in Pharmacology
                Frontiers Media S.A.
                1663-9812
                27 November 2019
                2019
                : 10
                : 1409
                Affiliations
                [1] 1Department of Family Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital , Chiayi, Taiwan
                [2] 2Department of Early Childhood Education and Nursery, Chia Nan University of Pharmacy and Science , Tainan, Taiwan
                [3] 3College of Medicine, China Medical University , Taichung, Taiwan
                [4] 4Management Office for Health Data, China Medical University Hospital , Taichung, Taiwan
                [5] 5Graduate Institute of Biomedical Sciences and School of Medicine, College of Medicine, China Medical University , Taichung, Taiwan
                [6] 6Department of Nuclear Medicine, China Medical University Hospital , Taichung, Taiwan
                [7] 7Department of Bioinformatics and Medical Engineering, Asia University , Taichung, Taiwan
                [8] 8Center of Augmented Intelligence in Healthcare, China Medical University Hospital , Taichung, Taiwan
                Author notes

                Edited by: Leonello Fuso, Catholic University of the Sacred Heart, Italy

                Reviewed by: Antonio Molino, University of Naples Federico II, Italy; Daniele Magnini, Catholic University of the Sacred Heart, Italy

                This article was submitted to Respiratory Pharmacology, a section of the journal Frontiers in Pharmacology

                Article
                10.3389/fphar.2019.01409
                6895570
                d3429dd8-8ff1-45dd-b15f-73967c32e751
                Copyright © 2019 Yeh, Yang, Hsu and Kao

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 25 February 2019
                : 05 November 2019
                Page count
                Figures: 1, Tables: 4, Equations: 0, References: 49, Pages: 11, Words: 7096
                Categories
                Pharmacology
                Original Research

                Pharmacology & Pharmaceutical medicine
                heart disease,stroke,bronchiectasis–chronic obstructive pulmonary disease overlap syndrome,bronchodilator,steroid

                Comments

                Comment on this article