Objective: To assess the impact on hospital admissions produced by trees and other falling objects, to examine these accidents' circumstances, and to investigate the degree of support provided by the data for tree-related accident prevention.
Methods: Admissions to emergency departments in the Hunter Region for the period 2008-2012 allocated the International Classification of Disease 10 code W20 (struck by falling object) were analysed.
Results: Of 620 admissions, 125 files were incorrectly coded leaving an eligible sample of 495 W20 admissions. Males made up 79.4% of admissions. Where recorded, the commonest accident locations were workplaces (63.2%) and homes (31.5%). Trees/branches caused only 24 (4.8%) of such accidents with an age-adjusted admission rate of 0.28 per 10,000 people compared with 6.84 per 10,000 for all falling objects combined. Most tree-related admissions (at least 62.5%) occurred to persons actively interacting with the tree. Being male (p=0.04) and living in an outer regional area (p=0.001) increased the incidence of tree injuries.
Conclusions: Hospital admissions caused by falling objects especially trees are uncommon. Implications for public health: It is difficult to justify any major health promotion expenditure to reduce tree-related accidents, given their especial rarity. Any funds allocated should focus on preventing falling object injuries in workplaces and homes.
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http://dx.doi.org/10.1111/1753-6405.12614 | DOI Listing |
Int J Comput Assist Radiol Surg
January 2025
Medical Informatics, University of Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany.
Purpose: Semantic segmentation and landmark detection are fundamental tasks of medical image processing, facilitating further analysis of anatomical objects. Although deep learning-based pixel-wise classification has set a new-state-of-the-art for segmentation, it falls short in landmark detection, a strength of shape-based approaches.
Methods: In this work, we propose a dense image-to-shape representation that enables the joint learning of landmarks and semantic segmentation by employing a fully convolutional architecture.
Sci Rep
January 2025
Human-Computer Collaborative Robot Joint Laboratory of Anhui Province, Huainan, China.
To address the challenges of low detection accuracy of small objects and weak applicability of the multi-person fall action recognition applications, we propose a hybrid fall detection method based on modified YOLOv8s and AlphaPose called HFDMIA-Pose. Firstly, we use the modified Yolov8s as object detector. It uses SPD-Conv to preserve small object features and adds a small object detection layer, while using BCIOU as the loss function.
View Article and Find Full Text PDFMedicine (Baltimore)
January 2025
Psychiatry Section, Department of Medicine, King Abdulaziz Medical City, Ministry of the National Guard Health Affairs, King Abdullah International Medical Research Center, College of Medicine, King Saud Bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia.
Rationale: Psychogenic tremor (PT) is the most common subtype of psychogenic movement disorder, characterized by involuntary movement, and is usually related to occupational injuries or accidents. Psychogenic movement disorder falls under the category of functional neurological disorders, which are diagnosed based on the criteria outlined in the Diagnostic and Statistical Manual of Mental Disorders.
Patient Concerns: A 25-year-old Saudi male with a history of recurrent superior ventricular tachycardia presented to the emergency department with tremors affecting all his extremities for 8 days.
Sci Rep
January 2025
College of Intelligence and Computing, Tianjin University, Tianjin, 300000, China.
Falling is an emergency situation that can result in serious injury or even death, especially in the absence of immediate assistance. Therefore, developing a model that can accurately and promptly detect falls is crucial for enhancing quality of life and safety. In the field of object detection, while YOLOv8 has recently made notable strides in detection accuracy and speed, it still faces challenges in detecting falls due to variations in lighting, occlusions, and complex human postures.
View Article and Find Full Text PDFJ Occup Environ Med
November 2024
National Institute for Occupational Safety and Health, Cincinnati, Ohio, United States.
Objective: The purpose of this study was to understand federal workplace injury/illness trends.
Methods: Over 1.5 million federal and Postal Service employee workers' compensation (WC) claims from 2007 to 2022 were linked to employment data and analyzed.
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