Citations

Abstract OBJECTIVE AND SCOPE A panel of clinicians, subject‐matter experts, and guideline methodologists convened by the Alzheimer's Association conducted a systematic review and formulated evidence‐based recommendations for using blood‐based biomarkers (BBMs) in the diagnostic workup of suspected Alzheimer's disease (AD) within specialized care settings. The scope focuses on individuals with objective cognitive impairment, including those with mild cognitive impairment (MCI) or dementia, who are undergoing evaluation by providers trained and experienced in memory disorders, where AD is the suspected underlying etiology. METHODS The panel conducted a systematic review to assess the diagnostic accuracy of BBMs in detecting AD pathology. The BBMs of interest included plasma phosphorylated‐tau (p‐tau) and amyloid‐beta (Aβ) tests measuring the following analytes: p‐tau217, ratio of p‐tau217 to non‐p‐tau217 ×100 (%p‐tau17), p‐tau181, p‐tau231, and ratio of Aβ42 to Aβ40. The reference standard tests included cerebrospinal fluid (CSF) AD biomarkers, amyloid positron emission tomography (PET), or neuropathology. The panel applied the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach to assess the certainty of the evidence and the GRADE evidence‐to‐decision (EtD) Framework to develop its recommendations. RECOMMENDATIONS The key recommendations in this Clinical Practice Guideline (CPG) are: (1) BBM tests with ≥90% sensitivity and ≥75% specificity can be used as a triaging test and (2) BBM tests with ≥90% sensitivity and specificity can serve as a substitute for amyloid PET imaging or CSF AD biomarker testing in patients with cognitive impairment presenting to specialized care for memory disorders. The panel cautions users of this guideline that there is significant variability in diagnostic test accuracy and many commercially available BBM tests do not meet these thresholds, especially using a single cutoff. Additionally, these tests do not serve as a substitute for comprehensive clinical evaluation by a healthcare professional and should be used only as part of a full diagnostic workup of patients with cognitive impairment presenting to specialized care settings, and with careful consideration of pretest probability of AD pathology. CONCLUSIONS AND PRACTICAL IMPLICATIONS This CPG provides performance‐based, brand‐agnostic recommendations for the use of BBMs in the diagnostic workup of suspected AD within specialized care settings. By linking recommendations to a systematic review and associated living updates, and using a robust and transparent methodology, the guideline ensures scientific rigor, adaptability, and sustained relevance as evidence evolves. Clinicians are encouraged to stay informed about emerging paradigms—such as biomarker combinations or ratios and multi‐threshold testing—that may further refine the diagnostic accuracy of BBMs as the field evolves.

Abstract The advances in large language models (LLMs) have demonstrated sophisticated potential for automating complex tasks within the radiology workflow. From radiology report generation and report summarization to data collection for research trials, these models have proven to be powerful tools. However, optimal implementation of these models requires careful adaptation to the specialized medical domain. In addition, these models tend to generate information that is not truthful or factual, which can adversely affect patient care and clinical decisions. Strategies such as fine-tuning and prompt optimization have been shown to be impactful in eliminating these errors. Although these models undergo rapid updates and improvements, understanding the principles of prompt engineering and fine-tuning provides a foundation for evaluating and maintaining the performance of any LLM deployment. The current article aims to review the recent advancements in radiology using fine-tuning and prompt optimization to leverage LLMs’ capabilities. It delves into various techniques within each strategy, their advantages and limitations, and presents a framework to facilitate the practical integration of LLMs into radiology settings.

Blood iron levels are related to many health conditions, affecting hundreds of millions of individuals worldwide. To aid in the prevention and treatment of iron-related disorders, previous research has developed a low-cost, accurate, point-of-care method for measuring iron from a single finger-prick blood sample. This study builds upon that work by introducing an improved imaging method that accurately reads sensor images irrespective of variations in environmental illumination and camera quality. Smartphone cameras were used as analytical tools, demonstrating an average coefficient of variation of 5.13% across different phone models, and absorbance results were found to be improved by 8.80% compared to the method in a previous study. The proposed method successfully enhances iron detection accuracy under diverse lighting conditions, paving the way for smartphone-based sensing of other colorimetric reactions involving various analytes.

Diffuse axonal brain injury (DAI) is a common, debilitating consequence of traumatic brain injury, yet its detection and severity grading remain challenging in clinical and experimental settings. This study evaluated the sensitivity of diffusion tensor imaging (DTI), histology, and neurological severity scoring (NSS) in assessing injury severity in a rat model of isolated DAI. A rotational injury model induced mild, moderate, or severe DAI in male and female rats. Neurological deficits were assessed 48 h after injury via NSS. Magnetic resonance imaging, including DTI metrics, such as fractional anisotropy (FA), relative anisotropy (RA), axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD), was performed prior to tissue collection. Histological analysis used beta amyloid precursor protein immunohistochemistry. Sensitivity and variability of each method were compared across brain regions and the whole brain. Histology was the most sensitive method, requiring very small groups to detect differences. Anisotropy-based MRI metrics, especially whole-brain FA and RA, showed strong correlations with histology and NSS and demonstrated high sensitivity with low variability. NSS identified injury but required larger group sizes. Diffusivity-based MRI metrics, particularly RD, were less sensitive and more variable. Whole-brain FA and RA were the most sensitive MRI measures of DAI severity and were comparable to histology in moderate and severe groups. These findings support combining NSS and anisotropy-based DTI for non-terminal DAI assessment in preclinical studies.

Key Points The growing knowledge of single-gene causes of pediatric-onset kidney diseases necessitates a structured application of genetic testing in practice. The clinical application of a combined nephrogenetics approach for management of kidney diseases is not well described in pediatric settings. Real-world application of a kidney genetics workflow highlights clinical value and challenges to be addressed for its successful implementation. Background The expanding knowledge of identifiable genetic contributions to pediatric inherited kidney diseases, and the increasing availability of genetic testing resources necessitates a combined nephrogenetics clinical approach. Although such models are described for adults, the effect of a structured nephrogenetics workflow on children with inherited kidney disease has not been rigorously evaluated. Methods Clinical and genetic data of patients aged younger than 1–21 years over a 10-year period between 2014 and 2024 from a single-center pediatric inherited kidney disease outpatient program were evaluated. Genetic variants were classified as pathogenic/likely pathogenic and variants of uncertain significance (VUS). Patients were grouped into “informative” or “uninformative” groups based on the effect of genetic test results on disease management and outcomes. Results Of the N =356 patients evaluated for a known or suspected inherited kidney disease, N =188 received clinical genetic testing. Of these, N =147 had an “informative” genetic test affecting at least one positive clinical outcome. Patients with an “informative” genetic test mostly harbored a pathogenic/likely pathogenic variant ( N =122). An additional N =25 had a VUS reclassified as a “VUS-of-interest” affecting a positive outcome measure. Genetic test results led to change in clinical diagnosis (reverse phenotyping, 46%), informed specific diagnosis-based treatment (46%), avoided unnecessary immunosuppression (27%) or kidney biopsy (18%), and guided extrarenal evaluation (72%) in patients with an informative test. Patients with a glomerular (odds ratio [OR]=5.23; 95% confidence interval [CI], 1.96 to 13.96) or a tubular functional disease (OR=2.17; 95% CI, 1.31 to 5.59) were more likely and those with a structural kidney disease (OR=0.39; 95% CI, 0.25 to 0.60) were less likely to receive a genetic test when compared with all other disease categories combined. Conclusions This workflow integrated multidisciplinary care for children with inherited kidney disease and describes a model for actionable clinical care plans after genetic testing. Informative genetic tests were associated with positive outcomes, and notable challenges include access to combined nephrology and genetics expertise for informed testing and an effective result return including VUS interpretation.

Objectives: This study evaluates the efficacy of existing and new aerosol mitigation methods during nebulization (Neb) in combination with high-flow nasal cannula (HFNC) oxygen supplementation and non-invasive ventilation (NIV). Methods: We recorded fugitive aerosol particle concentrations over time and assessed the peak (P) and area (A) efficacy of active and passive mitigation methods, comparing them to a no-mitigation condition. Peak efficacy was measured by the reduction in maximum aerosol concentration, while area efficacy was quantified by the reduction of the area under the aerosol concentration–time curve. Results: For HFNC with Neb, we found that active mitigation using a mask with a biofilter and a fan (referred to as the aerosol barrier mask) significantly outperformed passive mitigation with a face mask. The peak and area efficacy for aerosol reduction were 99.0% and 96.4% for active mitigation and 35.9% and 7.6% for passive mitigation, respectively. For NIV with Neb, the active mitigation method, using a box with a biofilter and fan, also outperformed passive mitigation using only the box. The peak and area efficacy for aerosol reduction were 92.1% and 85.5% for active mitigation and 53.7.0% and 25.4% for passive mitigation, respectively. Conclusion: We concluded that active mitigation set up systems advantageous for effective reduction of airborne aerosols during aerosol generated procedures.

We describe an unpredictable clinical scenario involving an intraoperative vascular injury during an elective total shoulder arthroplasty. Shortly into the procedure, the patient became acutely hypotensive due to frank hemorrhage. The patient experienced a complete transection of the third segment of the axillary artery caused by an unrecognized bone fragment, suspected to have dislodged into the joint space following a traumatic ground-level fall 12 months prior. Emergency vascular surgical intervention was required for hemostasis.