BACKGROUND:These recommendations provide guidance on the optimal duration of antibiotics in patients with complicated urinary tract infection (cUTI), especially in presence of associated Gram-negative bacteremia. METHODS:The panel's recommendations are based upon evidence derived from systematic literature reviews which focused on comparative benefits and harms of shorter (5-7 days) vs prolonged (10-14 days) duration of antibiotics, including publications since 2000. These recommendations adhere to a standardized methodology for rating the certainty of evidence and strength of recommendation according to the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach. RESULTS:The guidelines panel suggests that patients with cUTI who are improving on effective therapy can be treated with shorter duration of antimicrobials (either 5-7 days of a fluoroquinolone or 7 days of a non-fluoroquinolone) rather than longer courses of antibiotics, regardless of the presence of associated Gram-negative bacteremia. An effective antimicrobial agent achieves therapeutic levels in the urine and relevant tissue and is active against the causative pathogen. However, men with febrile UTI in whom acute bacterial prostatitis is suspected may benefit from a longer treatment duration (10-14 days), and a short courses of oral beta lactams may require higher doses for efficacy. CONCLUSIONS:Shorter durations of antibiotics for cUTI provide similar efficacy as longer courses, except in men with febrile UTI in whom acute bacterial prostatitis is suspected. This recommendation places a high value on antibiotic stewardship considerations as well as reducing the burden of antimicrobial administration from a healthcare perspective and reducing the burden of taking antibiotics from a patient perspective.
Purpose:Acute coronary syndrome (ACS) is a major cause of cardiovascular mortality. While coronary angiography enables definitive diagnosis and intervention, its invasiveness and limited availability delay treatment, disproportionately affecting rural and remote communities. Development of noninvasive, predictive tools for early revascularization may improve triage and outcomes.Methods:We propose TREAT-Netv2, a regional wall motion-informed video-tabular fusion network for ACS treatment prediction that integrates echocardiograms (echo) and electronic medical records. The model extracts regional wall motion features from echo sequences and applies the transformer-based multiple instance learning to capture nuanced disease representations. TREAT-Netv2 does not require diagnostic details such as level of occlusion or ACS subtype, eliminating the need for additional procedures and improving its robustness.Results:TREAT-Netv2 achieved an AUROC of 72.5% and balanced accuracy of 68.6%, outperforming unimodal, multimodal, and state-of-the-art baselines. ACS subgroup analysis showed that TREAT-Netv2 achieved the highest accuracy for non-ST-elevated myocardial infarction and unstable angina (NSTEMI/UA) patients, the most clinically challenging cases where the need for invasive intervention is often uncertain.Conclusion:By the complete elimination of ACS-specific diagnostic inputs and incorporation of transformer-based fusion, TREAT-Netv2 enables noninvasive and resource-free ACS risk stratification, particularly in clinically ambiguous cases. Our code will be made publicly available at URL: github.com/DeepRCL/TREAT-Netv2.
Trauma remains the leading cause of mortality in the United States for those <45 years of age, and it is the fourth leading cause of death overall. Polytrauma is defined as an injury to at least two body parts, including the head, neck, chest, abdomen, pelvis, or an extremity, with any one or a combination of these injuries being potentially fatal. This document covers imaging of major blunt trauma or polytrauma resulting in multiple organ injuries. Burn injuries, and injuries to pediatric patients are excluded. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.
Purpose: Fusion-positive myoepithelial tumors (MET) are clinicopathologically heterogeneous and variably termed mixed tumors and myoepithelial carcinomas. As FET-rearranged METs lack ductal/epithelial differentiation, we test whether FET-rearranged METs are epigenetically distinct from adnexal PLAG1-rearranged METs, which we hypothesize to be analogues of salivary gland METs. Experimental Design: DNA methylation profiling from a multi-institutional cohort of 52 fusion-positive skin, soft-tissue, and bone MET cases was performed and compared with diverse tumor types, including salivary METs. The MET subgroups harbored EWSR1::KLF15, EWSR1/FUS::KLF17, EWSR1::PBX1, EWSR1::PBX3, EWSR1/FUS::POU5F1, SS18::POU5F1, EWSR1::ZNF444, and PLAG1 rearrangements. Pooled clinicopathologic and outcome analysis with new and published cases (total 185) was performed. Results: The MET subgroups showed significant heterogeneity in age, site, and histology. Specifically, EWSR1::KLF15 METs affected predominantly young children (<5 years); EWSR1::PBX1/PBX3 METs were enriched in skin/bone; and EWSR1/FUS::POU5F1, SS18::POU5F1, and EWSR1::KLF15 METs tended to display malignant histology. Conversely, PLAG1-rearranged tumors were predominantly benign, arising in older adults and located in the skin. DNA methylation profiling revealed that FET-rearranged METs were epigenetically related to SS18::POU5F1 METs and FET::NFATC2 sarcomas but entirely distinct from PLAG1-rearranged adnexal and salivary METs. Histologic features were correlated with the degree of genome-wide copy-number variation. The median disease-specific survival was shortest in SS18::POU5F1 (31 months), EWSR1::PBX3 (38 months), and EWSR1::KLF15 (45 months) METs. On multivariate analysis, age <25 years was a significant predictor of worse progression-free survival. Conclusions: FET-rearranged METs are epigenetically unrelated to cutaneous and salivary gland METs, and their malignant counterparts are best classified as sarcomas rather than carcinomas.
PURPOSE:Echocardiographic interpretation requires video-level reasoning and guideline-based measurement analysis, which current deep learning models for cardiac ultrasound do not support. We present EchoAgent, a framework that enables structured, interpretable automation for this domain. METHODS:EchoAgent orchestrates specialized vision tools under large language model (LLM) control to perform temporal localization, spatial measurement, and clinical interpretation. A key contribution is a measurement-feasibility prediction model that determines whether anatomical structures are reliably measurable in each frame, enabling autonomous tool selection. We curated a benchmark of diverse, clinically validated video-query pairs for evaluation. To assess robustness across institutions, we further evaluate EchoAgent on a curated subset of the publicly available MIMIC-IV-EchoQA benchmark, specifically targeting questions answerable via linear measurements to remain within the current framework's scope. RESULTS:EchoAgent outperforms current medical VLMs and cardiac foundation models in video-level reasoning, demonstrating superior accuracy and interpretability on both our internal benchmark and the external MIMIC-IV-EchoQA subset. Outputs are grounded in visual evidence and clinical guidelines, supporting transparency and traceability. CONCLUSION:This work demonstrates the feasibility of agentic, guideline-aligned reasoning for echocardiographic video analysis, enabled by task-specific tools and full video-level automation. EchoAgent provides a framework for enhancing transparency and guideline-adherence, representing a step toward more trustworthy AI in cardiac ultrasound. Our code will be made publicly available at https://github.com/DeepRCL/EchoAgent .
