Promoting Artificial Intelligence for Global Breast Cancer Risk Prediction and Screening in Adult Women: A Scoping Review.

Background: Artificial intelligence (AI) algorithms can be applied in breast cancer risk prediction and prevention by using patient history, scans, imaging information, and analysis of specific genes for cancer classification to reduce overdiagnosis and overtreatment. This scoping review aimed to identify the barriers encountered in applying innovative AI techniques and models in developing breast cancer risk prediction scores and promoting screening behaviors among adult females. Findings may inform and guide future global recommendations for AI application in breast cancer prevention and care for female populations. Methods: The PRISMA-SCR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) was used as a reference checklist throughout this study. The Arksey and O'Malley methodology was used as a framework to guide this review. The framework methodology consisted of five steps: (1) Identify research questions; (2) Search for relevant studies; (3) Selection of studies relevant to the research questions; (4) Chart the data; (5) Collate, summarize, and report the results. Results: In the field of breast cancer risk detection and prevention, the following AI techniques and models have been applied: Machine and Deep Learning Model (ML-DL model) (n = 1), Academic Algorithms (n = 2), Breast Cancer Surveillance Consortium (BCSC), Clinical 5-Year Risk Prediction Model (n = 2), deep-learning computer vision AI algorithms (n = 2), AI-based thermal imaging solution (Thermalytix) (n = 1), RealRisks (n = 2), Breast Cancer Risk NAVIgation (n = 1), MammoRisk (ML-Based Tool) (n = 1), Various MLModels (n = 1), and various machine/deep learning, decision aids, and commercial algorithms (n = 7). In the 11 included studies, a total of 39 barriers to AI applications in breast cancer risk prediction and screening efforts were identified. The most common barriers in the application of innovative AI tools for breast cancer prediction and improved screening rates included lack of external validity and limited generalizability (n = 6), as AI was used in studies with either a small sample size or datasets with missing data. Many studies (n = 5) also encountered selection bias due to exclusion of certain populations based on characteristics such as race/ethnicity, family history, or past medical history. Several recommendations for future research should be considered. AI models need to include a broader spectrum and more complete predictive variables for risk assessment. Investigating long-term outcomes with improved follow-up periods is critical to assess the impacts of AI on clinical decisions beyond just the immediate outcomes. Utilizing AI to improve communication strategies at both a local and organizational level can assist in informed decision-making and compliance, especially in populations with limited literacy levels. Conclusions: The use of AI in patient education and as an adjunctive tool for providers is still early in its incorporation, and future research should explore the implementation of AI-driven resources to enhance understanding and decision-making regarding breast cancer screening, especially in vulnerable populations with limited literacy.

Social determinants of health and health inequities in breast cancer screening: a scoping review.

Introduction: This scoping review aims to highlight key social determinants of health associated with breast cancer screening behavior in United States women aged ≥40 years old, identify public and private databases with SDOH data at city, state, and national levels, and share lessons learned from United States based observational studies in addressing SDOH in underserved women influencing breast cancer screening behaviors. Methods: The Arksey and O'Malley York methodology was used as guidance for this review: (1) identifying research questions; (2) searching for relevant studies; (3) selecting studies relevant to the research questions; (4) charting the data; and (5) collating, summarizing, and reporting results. Results: The 72 included studies were published between 2013 and 2023. Among the various SDOH identified, those related to socioeconomic status (n = 96) exhibited the highest frequency. The Health Care Access and Quality category was reported in the highest number of studies (n = 44; 61%), showing its statistical significance in relation to access to mammography. Insurance status was the most reported sub-categorical factor of Health Care Access and Quality. Discussion: Results may inform future evidence-based interventions aiming to address the underlying factors contributing to low screening rates for breast cancer in the United States.

Handoff Tool Improves Transitions from the Operating Room to the Neonatal Intensive Care Unit.

Introduction: Standardized handoffs reduce medical errors and prevent adverse events or near misses. This article describes a quality improvement initiative implementing a unique standardized handoff tool and process to transition from the operating room to the neonatal intensive care unit (NICU) at a level-four regional center with many inpatients requiring surgical intervention. Before this project, there was no standardized handoff tool or process for postsurgical transitions. The primary aim was to achieve 80% compliance with completing a structured postoperative OR to NICU handoff tool within 12 months of implementation. Methods: An interdisciplinary team developed and implemented a standardized NICU postoperative handoff tool and process that requires face-to-face communication, defines team members who should be present, and highlights communication with the family. In addition, the handoff tool compliance and process measures were monitored, evaluated, and audited. Results: Although not consistent, we achieved eighty percent compliance with the outcome measures using the handoff tool. We did not sustain 80% of appropriate providers present at handoff. In addition, insufficient data assess overall parental satisfaction with the surgical experience. Although improved, the process measure of immediate postoperative family updates did not reach the targeted goal. However, the balancing measure of staff experience and satisfaction did improve. Conclusion: Implementing a standardized handoff tool and process with an interdisciplinary and interdepartmental collaboration improves critical patient transitions from the operating room to the NICU.

Functional characterization of SLC39 family members ZIP5 and ZIP10 in overexpressing HEK293 cells reveals selective copper transport activity.

Zinc is the second most prevalent metal element present in living organisms, and control of its concentration is pivotal to physiology. The amount of zinc available to the cell cytoplasm is regulated by the activity of members of the SLC39 family, the ZIP proteins. Selectivity of ZIP transporters has been the focus of earlier studies which provided a biochemical and structural basis for the selectivity for zinc over other metals such as copper, iron, and manganese. However, several previous studies have shown how certain ZIP proteins exhibit higher selectivity for metal elements other than zinc. Sequence similarities suggest an evolutionary basis for the elemental selectivity within the ZIP family. Here, by engineering HEK293 cells to overexpress ZIP proteins, we have studied the selectivity of two phylogenetic clades of ZIP proteins, that is ZIP8/ZIP14 (previously known to be iron and manganese transporters) and ZIP5/ZIP10. By incubating ZIP over-expressing cells in presence of several divalent metals, we found that ZIP5 and ZIP10 are high affinity copper transporters with greater selectivity over other elements, revealing a novel substrate signature for the ZIP5/ZIP10 clade.

Cardiac Collapse Secondary to Phenytoin Toxicity in a Neonate Treated with Extracorporeal Membrane Oxygenation Support (ECMO).

INTRODUCTION: Although medication toxicity is uncommon in neonates, there are several medications used in this population that pose a risk. Phenytoin has an increased risk of toxicity given its narrow therapeutic window and variations in drug elimination. CASE REPORT: We describe the case of a 3-day-old male infant who developed cardiovascular collapse secondary to severe phenytoin toxicity (max phenytoin level 86 µg/mL) and was placed on extracorporeal membrane oxygenation support (ECMO). Several ancillary treatments were utilized in an attempt to decrease serum phenytoin concentrations and limit toxicity including albumin boluses, phenobarbital administration, intravenous lipid infusion, and folic acid supplementation. DISCUSSION: Although uncommon, drug toxicity should be considered in patients with acute changes who are exposed to medications with potential toxicity. With elevated levels of phenytoin, the half-life can be prolonged resulting in longer exposure to elevated levels of the drug as seen in our patient. This case report highlights the importance of ECMO utilization for cardiac support in neonates with medication toxicity and other potential ancillary treatments to decrease serum phenytoin concentrations.