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Filename: models/Detail_model.php
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Function: strpos
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Function: insertAPISummary
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Filename: helpers/my_audit_helper.php
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Function: formatAIDetailSummary
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Objectives: International guidelines only advocate the use of inhaled corticosteroids (ICSs) in patients with chronic obstructive pulmonary disease (COPD) experiencing recurring exacerbations and eosinophilic inflammation. However, ICSs are commonly used in patients with COPD and without exacerbations and signs of eosinophilic inflammation, thus possibly increasing the risk of hospitalization for pneumonia. Thus, we aimed to determine the risk of hospitalization for pneumonia associated with increasing cumulated ICS doses among patients with COPD to establish whether there is dose dependency.
Methods: A retrospective cohort study included all patients with COPD treated at a respiratory outpatient clinic in Denmark. The patients were divided into four groups based on their average daily ICS exposure. The dose-response relationship was investigated using a multivariable Cox proportional hazard regression analysis.
Results: In total, 52 100 patients were included, who were divided into the no-use (n = 15 755), low-dose (n = 12 050), moderate-dose (n = 12 488), and high-dose (n = 11 807) groups. ICS use was strongly associated with hospitalization for pneumonia (hazard ratio [HR], 1.3; CI, 1.2-1.3) (ICS vs. no ICS). The risk of hospitalization for pneumonia increased with every dosing group step: low dose: HR, 1.1 (CI, 1.0-1.2); moderate dose: HR, 1.2 (CI, 1.1-1.3), and high dose: HR, 1.5 (CI, 1.4-1.6); "no use" was the reference. Sensitivity analyses confirmed these findings.
Conclusions: In the dose-response relationship analysis, ICS dose were associated with a substantially increased risk of hospitalization for pneumonia of up to 50%. Our data support that ICSs should be administered at the lowest possible dose and only to patients with COPD who have a documented need.
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http://dx.doi.org/10.1016/j.cmi.2022.11.029 | DOI Listing |
Pneumonia (Nathan)
December 2024
School of Pharmaceutical Sciences, Lovely Professional University, Phagwara, India.
Background: Pneumococcal disease, caused by Streptococcus pneumoniae, imposes a significant global health burden, particularly affecting vulnerable groups such as the elderly and immunocompromised. The 23-valent pneumococcal polysaccharide vaccine (PPV23) is designed to protect against 23 serotypes of Streptococcus pneumoniae. However, there is ongoing debate about its effectiveness in reducing all-cause mortality.
View Article and Find Full Text PDFAntimicrob Resist Infect Control
December 2024
Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Infection prevention and control (IPC) programs form the basis of minimizing spread of pathogens in the healthcare setting and beyond. The COVID-19 pandemic amplified the demand for IPC. However, the environmental impact of IPC practices has yet to be addressed and attempts to quantify its climate implications have been sparse.
View Article and Find Full Text PDFBMC Ophthalmol
December 2024
National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, 3250027, China.
Objectives: To analyze the influence of daily activity-related factors associated with COVID-19 infection on the occurrence of acute angle closure (AAC).
Methods: A multicenter hospital-based study was conducted at 23 ophthalmic centers in 17 provincial-level regions across China to recruit patients with confirmed AAC during the post-lockdown time of COVID-19 (P-TOC) from Dec 7, 2022, to Jan 17, 2023, and three lockdown time of COVID-19 (TOC) periods, which included the TOC-2022 (Sep 7, 2022 - Dec 6, 2022), TOC-2021(Sep 7, 2021 - Jan 6, 2022) and TOC-2020 (Sep 7, 2020 - Jan 6, 2021). Patient information, including demographic, a questionnaire on daily activity changes during the AAC period, COVID-19 history, and eye examination results, was collected.
J Transl Med
December 2024
Department of Rheumatology and Immunology, Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Tianhe District, Guangzhou, China.
Background: Corona virus disease 2019 (COVID-19) reinfection, particularly short-term reinfection, poses challenges to the management of rheumatic diseases and may increase adverse clinical outcomes. This study aims to develop machine learning models to predict and identify the risk of short-term COVID-19 reinfection in patients with rheumatic diseases.
Methods: We developed four prediction models using explainable machine learning to assess the risk of short-term COVID-19 reinfection in 543 patients with rheumatic diseases.
Hypertens Res
December 2024
Department of General Practice, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, China.
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