Suppr超能文献

伊斯坦布尔遗传病中心职业健康与安全水平调查

Investigation of Occupational Health and Safety Levels in Genetic Disease Centers in Istanbul.

作者信息

Caner Vedat, Tanir Ferdi

机构信息

Istanbul Beykent University, Vocational School, Property Protection and Security Department, Occupational Health and Safety Program, Istanbul, Turkey.

School of Medicine, Department of Internal Medicine, Department of Public Health, Cukurova University, Adana, Turkey.

出版信息

J Clin Lab Anal. 2025 Apr;39(7):e70015. doi: 10.1002/jcla.70015. Epub 2025 Mar 26.

Abstract

BACKGROUND

Genetic disorders significantly impact public health and quality of life, necessitating precise and timely diagnosis for effective risk management and treatment. Genetic diagnostic centers (GDCs) play a critical role in this process but face numerous occupational health and safety (OHS) challenges. The classification of GDCs based solely on biosafety levels is insufficient for assessing their overall OHS conditions. This study aims to systematically evaluate OHS practices in GDCs and propose a new classification approach based on hazard dimensions.

METHODS

This cross-sectional study was conducted in 15 GDCs in Istanbul, including two public and 13 private facilities with 75 employees. Data were collected through a structured survey with 49 statements covering seven hazard dimensions. Regression and correlation analyses were used to assess the impacts and interrelationships of these dimensions on risk management. Principal Component Analysis (PCA) was applied for dimensionality reduction, and the k-Nearest Neighbours (k-NN) algorithm classified laboratories into safety levels.

RESULTS

Personal protective equipment had the highest impact on risk management (56.3%), while physical security had the lowest (34.8%). Among the 21 identified hazard relationships, 18 were very strong and three were strong. PCA reduced the data into three primary components, explaining 81.9% of the variance. The k-NN algorithm achieved a classification accuracy of 93.33%, consolidating six hazard dimensions into three and categorizing centers into three safety levels.

CONCLUSION

The findings emphasize the need for an updated OHS classification for GDCs beyond biosafety levels. Integrating hazard dimensions into safety assessments can improve risk management and enhance laboratory safety standards.

摘要

背景

遗传疾病对公众健康和生活质量有重大影响,因此需要进行准确及时的诊断,以实现有效的风险管理和治疗。遗传诊断中心(GDCs)在这一过程中发挥着关键作用,但面临着众多职业健康与安全(OHS)挑战。仅基于生物安全水平对GDCs进行分类不足以评估其整体OHS状况。本研究旨在系统评估GDCs中的OHS实践,并提出一种基于危害维度的新分类方法。

方法

这项横断面研究在伊斯坦布尔的15个GDCs中进行,包括2个公共机构和13个私人机构,共有75名员工。通过一项结构化调查收集数据,该调查包含49条涵盖7个危害维度的陈述。采用回归和相关分析来评估这些维度对风险管理的影响和相互关系。应用主成分分析(PCA)进行降维,并使用k近邻(k-NN)算法将实验室分类为安全级别。

结果

个人防护设备对风险管理的影响最大(56.3%),而物理安全的影响最小(34.8%)。在确定的21种危害关系中,18种非常强,3种较强。PCA将数据简化为三个主要成分,解释了81.9%的方差。k-NN算法实现了93.33%的分类准确率,将六个危害维度整合为三个,并将各中心分为三个安全级别。

结论

研究结果强调,除生物安全水平外,还需要对GDCs进行更新的OHS分类。将危害维度纳入安全评估可以改善风险管理并提高实验室安全标准。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f78e/11981950/21ea8ad32329/JCLA-39-e70015-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验