Background: This study developed a surveillance method for healthcare-associated infections (HAIs) in long-term care hospitals (LTCHs) and investigated the current status of HAIs in LTCHs in Korea.
Methods: We applied the HAI-related surveillance criteria for long-term care facilities developed by McGeer in six LTCHs.
Results: The 197 confirmed HAIs corresponded to incidence rates of 30.38/100 inpatients and 1.57/1,000 days of hospitalization and included 84 cases of respiratory tract infection (43.8%), 78 cases of systemic infection (40.6%), 24 cases of gastrointestinal tract infection (12.5%), and 6 cases of skin and soft tissue mucosal infection (2.1%). The subtypes included 78 cases of unexplained febrile illness (40.6%); 40 cases of pneumonia (20.8%); 27 cases of lower respiratory tract infection (14.1%); 21 cases of gastroenteritis (10.9%); 9 cases of influenza-like illness (4.7%); 8 cases of common cold or pharyngitis (4.2%); 4 cases of cellulitis, soft tissue, or wound infection (2.1%); 3 cases of Clostridium difficile infection (1.6%); 1 case of conjunctivitis (0.5%); and 1 case of fungal oral/perioral and skin infection (0.5%).
Conclusion: Establishing an HAI surveillance method for LTCHs and identifying HAI rates and risk factors among LTCH patients may help prevent HAIs in LTCHs in Korea.
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http://dx.doi.org/10.4235/agmr.20.0067 | DOI Listing |
Genet Med
January 2025
Genomics Ethics, and Translational Research Program, RTI International, Research Triangle Park, NC; Department of Translational and Applied Genomics, Kaiser Permanente Center for Health Research, Portland, OR. Electronic address:
Purpose: Limited evidence evaluates parents' perceptions of their child's clinical genomic sequencing (GS) results, particularly among individuals from medically underserved groups. Five Clinical Sequencing Evidence-Generating Research (CSER) consortium studies performed GS in children with suspected genetic conditions with high proportions of individuals from underserved groups to address this evidence gap.
Methods: Parents completed surveys of perceived understanding, personal utility, and test-related distress after GS result disclosure.
Cancer Med
January 2025
Division of Gastroenterology and Nephrology, Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago, Japan.
Background And Aim: In recent years, there has been a rise in cryptogenic hepatocellular carcinoma (c-HCC) cases in Japan, posing a detection challenge due to an unknown etiology. This study aims to enhance diagnostic strategies for c-HCC by analyzing its characteristics and exploring current opportunities for detection.
Methods: A retrospective study was conducted from April 2012 to March 2022, enrolling 372 newly diagnosed hepatocellular carcinoma (HCC) patients.
Circ Genom Precis Med
January 2025
CARIM School for Cardiovascular Diseases (A.I., S.Z., J.W., B.B., H.J.G.M.C., B.H., M.K., S.V., U.S., M.S.), Maastricht University, the Netherlands.
Background: Transcriptional dysregulation, possibly affected by genetic variation, contributes to disease development. Due to dissimilarities in development, function, and remodeling during disease progression, transcriptional differences between the left atrial (LA) and right atrial (RA) may provide insight into diseases such as atrial fibrillation.
Methods: Lateral differences in atrial transcription were evaluated in CATCH ME (Characterizing Atrial fibrillation by Translating its Causes into Health Modifiers in the Elderly) using a 2-stage discovery and replication design.
Stat Methods Med Res
January 2025
CITMAga and Department of Statistics and Operations Research, Universidade de Vigo, Vigo, Galicia, Spain.
The study of the predictive ability of a marker is mainly based on the accuracy measures provided by the so-called confusion matrix. Besides, the area under the receiver operating characteristic curve has become a popular index for summarizing the overall accuracy of a marker. However, the nature of the relationship between the marker and the outcome, and the role that potential confounders play in this relationship could be fundamental in order to extrapolate the observed results.
View Article and Find Full Text PDFPharm Stat
January 2025
Division of Biostatistics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Clinical trials (CTs) often suffer from small sample sizes due to limited budgets and patient enrollment challenges. Using historical data for the CT data analysis may boost statistical power and reduce the required sample size. Existing methods on borrowing information from historical data with right-censored outcomes did not consider matching between historical data and CT data to reduce the heterogeneity.
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