The aim of this study was to estimate the prevalence of patients diagnosed with chronic obstructive pulmonary disease (COPD) according to age, gender, and residence in Greenland and to investigate the associated quality of care. The study was performed as an observational cross-sectional study using data on patients diagnosed with COPD, extracted from the electronical medical record (EMR) in Greenland. The total prevalence of patients aged 20-79 years diagnosed with COPD in Greenland in 2022 was 2.2%. The prevalence was significantly higher in the capital Nuuk compared to the remaining parts of Greenland (2.4% vs. 2.0%, respectively). Significantly more women than men were diagnosed with COPD, but the lung function of men was found to be significantly reduced/impaired compared to women. The prevalence of patients aged 40 years or above was 3.8%. The quality of care was significantly higher among patients living in Nuuk compared to the remaining parts of Greenland for eight out of ten quality indicators. The prevalence of COPD in Greenland is lower than in other comparable populations and might be underestimated. Continued focus on early detection of new cases and initiatives to improve and expand monitoring of quality-of-care measurements, including both additional clinical and patient reported outcomes, are recommended.
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http://dx.doi.org/10.3390/ijerph20095624 | DOI Listing |
Ann Intern Med
January 2025
Renal-Electrolyte Division, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (M.C.-P., R.B.M., C.M.P.).
Background: Prior studies indicate that 1% to 4% of Epstein-Barr virus (EBV)-seronegative recipients of EBV-seropositive donor (EBV D+/R-) kidneys develop posttransplant lymphoproliferative disorder (PTLD). However, these estimates are based on limited data that lack granularity.
Objective: To determine the associations between pretransplant EBV D+/R- and recipient EBV-seropositive status (R+) and the outcomes of PTLD and graft and patient survival among adult kidney transplant recipients.
Ann Intern Med
January 2025
Clinical Epidemiology and Research Center (CERC), Department of Biomedical Sciences, Humanitas University, and IRCCS Humanitas Research Hospital, Milan, Italy, and Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Allergology and Immunology, Berlin, Germany (H.J.S.).
Description: Artificial intelligence (AI) has been defined by the High-Level Expert Group on AI of the European Commission as "systems that display intelligent behaviour by analysing their environment and taking actions-with some degree of autonomy-to achieve specific goals." Artificial intelligence has the potential to support guideline planning, development and adaptation, reporting, implementation, impact evaluation, certification, and appraisal of recommendations, which we will refer to as "guideline enterprise." Considering this potential, as well as the lack of guidance for the use of AI in guidelines, the Guidelines International Network (GIN) proposes a set of principles for the development and use of AI tools or processes to support the health guideline enterprise.
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