Background: Infections of cardiac implantable electronic devices (CIED) are associated with significant morbidity and mortality. Despite many preventive measures, this condition is associated with significant costs for the health care system.
Methods: We retrospectively analyzed all infection cases referred for lead extraction at a single university hospital over 1 year (2015-2016). We then calculated all costs related to the infection episode per patient using hospital databases and charts review.
Results: Thirty-eight patients with CIED infections (29% women-mean age 71 ± 14 years) were referred for lead extraction (27 pocket infections, 11 endocarditis). Devices were mainly pacemakers (60%). When the pathogen was identified, Staphylococcus aureus methicillin sensitive was the main cause. Extraction was performed in all but 3 cases (92%). One death occurred in the nonextracted group. Respective durations of hospitalization and intravenous and antibiotic administration for patients undergoing extraction were 21 and 36 days. The calculated mean total cost for CIED infection management was CAD$29,907 (median: 26,879; range: CAD$4,827-$62,585). Mean hospital charges were CAD$12,291, accounting for 41% of the total costs.
Conclusions: This study represents the first analysis of the direct costs associated with lead extraction in Canada. Device infections are associated with significant costs and increased morbidity. Any preventive measure will have a significant impact on the economic burden of the health care system and patient outcome after lead extraction.
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http://dx.doi.org/10.1016/j.cjca.2018.05.001 | DOI Listing |
J Am Coll Cardiol
December 2024
Electrophysiology Section, Division of Cardiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Sensors (Basel)
December 2024
School of Engineering, Technology and Design, Canterbury Christ Church University, Canterbury CT1 1QU, UK.
The rapid integration of Internet of Things (IoT) systems in various sectors has escalated security risks due to sophisticated multilayer attacks that compromise multiple security layers and lead to significant data loss, personal information theft, financial losses etc. Existing research on multilayer IoT attacks exhibits gaps in real-world applicability, due to reliance on outdated datasets with a limited focus on adaptive, dynamic approaches to address multilayer vulnerabilities. Additionally, the complete reliance on automated processes without integrating human expertise in feature selection and weighting processes may affect the reliability of detection models.
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December 2024
Department of Mechanical Engineering, California Polytechnic State University, San Luis Obispo, CA 93407, USA.
Structural damage identification based on structural health monitoring (SHM) data and machine learning (ML) is currently a rapidly developing research area in structural engineering. Traditional machine learning techniques rely heavily on feature extraction, where weak feature extraction can lead to suboptimal features and poor classification performance. In contrast, ML-based methods, particularly deep learning approaches like convolutional neural networks (CNNs), automatically extract relevant features from raw data, improving the accuracy and adaptability of the damage identification process.
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December 2024
Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, USA.
Understanding sleep stages is crucial for diagnosing sleep disorders, developing treatments, and studying sleep's impact on overall health. With the growing availability of affordable brain monitoring devices, the volume of collected brain data has increased significantly. However, analyzing these data, particularly when using the gold standard multi-lead electroencephalogram (EEG), remains resource-intensive and time-consuming.
View Article and Find Full Text PDFPolymers (Basel)
December 2024
Bioprospecting Research Group, School of Engineering, Universidad de La Sabana, Campus del Puente del Común, Km. 7, Autopista Norte de Bogotá, Chía 140013, Colombia.
Fresh-cutting fruits is a common practice in markets and households, but their short shelf life is a challenge. Active packaging is a prominent strategy for extending food shelf life. A systematic review was conducted following the PRISMA guidelines to explore the performance and materials used in biodegradable active packaging for fresh-cut fruits.
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