BackgroundEmployment rates among those with chronic obstructive pulmonary disease (COPD) are lower than those without COPD, but little is known about the factors that affect COPD patients’ ability to work.MethodsMultivariable analysis of the Birmingham COPD Cohort Study baseline data was used to assess the associations between lifestyle, clinical, and occupational characteristics and likelihood of being in paid employment among working-age COPD patients.ResultsIn total, 608 of 1,889 COPD participants were of working age, of whom 248 (40.8%) were in work. Older age (60–64 years vs 30–49 years: odds ratio [OR] =0.28; 95% confidence interval [CI] =0.12–0.65), lower educational level (no formal qualification vs degree/higher level: OR =0.43; 95% CI =0.19–0.97), poorer prognostic score (highest vs lowest quartile of modified body mass index, airflow obstruction, dyspnea, and exercise (BODE) score: OR =0.10; 95% CI =0.03–0.33), and history of high occupational exposure to vapors, gases, dusts, or fumes (VGDF; high VGDF vs no VGDF exposure: OR =0.32; 95% CI =0.12–0.85) were associated with a lower probability of being employed. Only the degree of breathlessness of BODE was significantly associated with employment.ConclusionThis is the first study to comprehensively assess the characteristics associated with employment in a community sample of people with COPD. Future interventions should focus on managing breathlessness and reducing occupational exposures to VGDF to improve the work capability among those with COPD.
This is the first study to identify important factors associated with poor work productivity among patients with COPD. Future studies should evaluate interventions aimed at managing breathlessness and reducing occupational exposures to VGDF on work productivity among patients with COPD.
Objective: To create case definitions for confirmed COVID diagnoses, COVID vaccination status, and three separate definitions of high risk of severe COVID, as well as to assess whether the implementation of these definitions in a cohort reflected the sociodemographic and clinical characteristics of COVID epidemiology in England. Design: Retrospective cohort study Setting: Electronic healthcare records from primary care (Clinical Practice Research Datalink, or CPRD) linked to secondary care data (Hospital Episode Statistics, or HES) data covering 24% of the population in England Participants: 2,271,072 persons aged 1 year and older diagnosed with COVID in CPRD Aurum between August 1, 2020 through January 31, 2022. Main Outcome Measures: Age, sex, and regional distribution of COVID cases and COVID vaccine doses received prior to diagnosis were assessed separately for the cohorts of cases identified in primary care and those hospitalized for COVID (primary diagnosis code of ICD-10 U07.1 COVID-19). Smoking status, body mass index and Charlson Comorbidity Index were compared for the two cohorts, as well as for three separate definitions of high risk of severe disease used in the United Kingdom (NHS Highest Risk, PANORAMIC trial eligibility, UK Health Security Agency Clinical Risk prioritization for vaccination). Results: Compared to national estimates, CPRD case estimates underrepresented older adults in both the primary care (age 65-84: 6% in CPRD vs 9% nationally) and hospitalized (31% vs 40%) cohorts, and overrepresented people living in regions with the highest median wealth areas of England (20% primary care and 20% hospital admitted cases in South East, vs 15% nationally). The majority of non-hospitalized cases and all hospitalized cases had not completed primary series vaccination. In primary care, persons meeting high risk definitions were older, more often smokers, overweight or obese, and had higher Charlson Comorbidity Index score. Conclusions: CPRD primary care data is a robust real-world data source and can be used for some COVID research questions, however limitations of the data availability should be carefully considered. Included in this publication are supplemental files for a total of over 28,000 codes to define each of three definitions of high risk of severe disease.
In this mini-review, we examine very recent (≤3 years) endeavors in electrochemical genosensor design and applications. Electrochemical genosensors are engineered working electrodes modified with sequences of bases that are selective toward the analyte pursuit, where the analyte bears complementary sequence to of bases. Our focus is purely from electrochemistry and current fluxes as signalers of detection. We explore developments in transducers and the electrochemical surface as applied toward detection of viruses for example, dengue, hepatitis, influenza and human immunodeficiency viruses, bacteria, for example Escherichia, Salmonella, Streptococcus, Meningitis and Brucella. We also include a section on detection of major diseases through RNA-targets, for example Parkinson's and Alzheimer's and ovarian and breast cancer disease biomarkers. Finally, we conclude the review with a brief appraisal of the technologies adopted in recent times and possible future directions in genosensor design.
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