Systematic review tools and approaches developed for clinical medicine are often difficult to apply "off the shelf" in order to meet the needs of chemical risk assessments. To address such, we propose an approach that can be used by practitioners for using evidence-based methods to facilitate the risk assessment process. The framework builds on and combines efforts conducted to date by a number of agencies and researchers; the novelty is in combining these efforts with a practical understanding of risk assessment, and translating such into a 'step-by-step' guide. The approach relies on three key components: problem formulation, systematic evidence mapping, and systematic review, applied using a stepwise approach. Unique to this framework is the consideration of exposure in selecting, prioritizing, and evaluating data (e.g., dose-relevance, routes of exposure, etc.). Using the proposed step-by-step process, critical appraisal of individual studies (e.g., formal and structured assessment of both relevance and reliability) and integration efforts are considered in context of specified risk assessment objectives (e.g., mode of action, dose-response) as well as chemical-specific considerations. The resulting framework provides a logical approach of how evidence-based methods can be used to facilitate risk assessment, and elevates the use of systematic methods beyond hazard identification to directly facilitating transparent and objective selection of candidate studies and/or datasets used to quantitatively characterize risk, and to better use the underlying process to inform the approaches used to develop toxicity values.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.yrtph.2020.104790 | DOI Listing |
J Neurosurg
January 2025
13Department of Neurosurgery, Shimane Prefectural Central Hospital, Shimane, Japan.
Objective: Aneurysmal subarachnoid hemorrhage (SAH) is associated with high morbidity and mortality rates. In particular, functional outcomes of SAH caused by large or giant (≥ 10 mm) ruptured intracranial aneurysms are worsened by high procedure-related complication rates. However, studies describing the risk factors for poor functional outcomes specific to ruptured large/giant aneurysms are sparse.
View Article and Find Full Text PDFJ Occup Environ Med
January 2025
Department of Biostatistics, Florida International University, Miami, FL, United States.
Objective: To assess factors influencing Neonatal Respiratory Distress Syndrome (RDS) risk, incorporating maternal demographics, behaviors, medical conditions, pregnancy-related factors, and PM2.5 speciation pollutants exposures.
Methods: Using Florida de-identified birth records, logistic regression analyses were conducted to assess associations between maternal exposure to PM2.
Otol Neurotol
February 2025
Department of Otolaryngology-Head and Neck Surgery.
Objective: To compare fall risk scores of hearing aids embedded with inertial measurement units (IMU-HAs) and powered by artificial intelligence (AI) algorithms with scores by trained observers.
Study Design: Prospective, double-blinded, observational study of fall risk scores between trained observers and those of IMU-HAs.
Setting: Tertiary referral center.
PLoS One
January 2025
College of Business, Southern University of Science and Technology, Shenzhen, China.
In credit risk assessment, unsupervised classification techniques can be introduced to reduce human resource expenses and expedite decision-making. Despite the efficacy of unsupervised learning methods in handling unlabeled datasets, their performance remains limited owing to challenges such as imbalanced data, local optima, and parameter adjustment complexities. Thus, this paper introduces a novel hybrid unsupervised classification method, named the two-stage hybrid system with spectral clustering and semi-supervised support vector machine (TSC-SVM), which effectively addresses the unsupervised imbalance problem in credit risk assessment by targeting global optimal solutions.
View Article and Find Full Text PDFMedicine (Baltimore)
January 2025
Department of Breast, Haining Maternity and Child Health Care Hospital, Haining, Zhejieng, China.
Endosomes play a pivotal role in cellular biology, orchestrating processes such as endocytosis, molecular trafficking, signal transduction, and recycling of cellular materials. This study aims to construct an endosome-related gene (ERG)-derived risk signature for breast cancer prognosis. Transcriptomic and clinical data were retrieved from The Cancer Genome Atlas and the University of California Santa Cruz databases to build and validate the model.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!