Citations

Purpose of review This paper reviews the current understanding of coronary vascular dysfunction (CVDys) in patients with angina and no obstructive coronary artery disease (ANOCA), based on recent findings from a comprehensive, large-scale study. It also discusses potential future directions for research and clinical practice. Recent findings CVDys involves enhanced vasoconstriction or impaired vasodilation caused by endothelium-dependent and/or -independent dysfunction in the epicardial or microvascular coronary arteries. It is classified into four subtypes based on anatomical location and underlying mechanisms, and can be assessed using coronary reactivity testing (CRT). Previous studies have evaluated their prognostic implications separately or in limited populations. A recent study assessed all subtypes within a single ANOCA cohort and confirmed that endothelium-dependent epicardial dysfunction and both types of microvascular dysfunction are associated with worse prognosis. Moreover, it demonstrated that microvascular function – both endothelium-dependent and -independent – serves as an independent prognostic factor for major adverse cardiovascular events. These findings emphasize the value of CRT-based comprehensive evaluation for risk stratification. Summary While evidence regarding the prognostic impact of CVDys has become increasingly robust, effective treatment strategies remain undefined. Future efforts should focus on developing CRT-guided interventions targeting coronary dysfunction, with the goal of improving clinical outcomes.

This retrospective propensity-matched cohort study assessed the association between sodium-glucose co-transporter-2 inhibitor (SGLT2i) use and cardiovascular outcomes in patients with acute myocardial infarction (AMI) without a history of heart failure. Using the TriNetX U.S. Collaborative Network, we identified 1440 matched patients (720 SGLT2i+ vs 720 SGLT2i−) with preserved ejection fraction and no prior heart failure. Nearly 90% of patients had diabetes. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of MI, stroke, heart failure, and all-cause mortality. At 1 year, MACE occurred in 17.4% of SGLT2i+ versus 22.0% of SGLT2i− patients (odds ratio [OR] 0.746, 95% CI 0.574-0.969; P = .028), and all-cause mortality occurred in 3.1% versus 7.6%, respectively (OR 0.389, 95% CI 0.234-0.645; P < .001). SGLT2i use was also associated with lower risks of major bleeding. Findings were consistent over long-term follow-up. While the observed associations suggest potential cardioprotective effects of SGLT2i post-MI in patients without heart failure, residual confounding cannot be excluded. The observed reduction in bleeding events is novel and warrants further investigation in prospective studies.

Abstract Objective Sleeper stretching (SS) and cross‐body stretching (CS) are common nonsurgical interventions for the management of glenohumeral internal rotation deficit (GIRD) in overhead athletes such as baseball and volleyball players. However, the effectiveness of these stretching interventions in enhancing the range of motion (ROM) of shoulder internal rotation (IR) in overhead athletes with GIRD remains a subject of uncertainty. This systematic review and meta‐analysis aim to critically assess the efficacy of SS and CS in the ROM of the IR among overhead athletes with GIRD, thereby providing evidence‐based recommendations for their use. Literature Survey A comprehensive search of MEDLINE, Embase, and Scopus databases up to November 2024 was conducted to identify randomized controlled trials investigating the influence of SS and CS on the ROM of shoulder IR in overhead athletes with GIRD. Methodology Data including study characteristics and outcomes were extracted. Risk of bias assessment and random‐effects model meta‐analysis were performed. Synthesis Six eligible studies involving 255 athletes with GIRD were included. The meta‐analysis demonstrated statistically significant differences between stretching and control groups in terms of enhancing the ROM of IR (mean difference [MD], 7°; 95% confidence interval [CI], 1°–13°; p = .02) and horizontal adduction (HAD) ([MD], 6°; [CI], 1°–11°; p = .03). Conclusion SS or combination of SS and CS interventions significantly enhanced the ROM of IR compared to the control group in overhead athletes diagnosed with GIRD. Furthermore, the review confirmed that SS alone also markedly enhances the ROM of HAD. These findings highlight the potential benefits of SS and CS in managing GIRD and suggest a need for further research to optimize these interventions for broader application in overhead athletes.

Abstract Context Data on diagnostic accuracy of dehydroepiandrosterone sulfate (DHEA-S) for mild autonomous cortisol secretion (MACS) and adrenal insufficiency (AI) are discrepant. Objective We conducted a systematic review and meta-analysis of published studies assessing the accuracy of DHEA-S in diagnosing MACS or AI. Methods From inception to January 8, 2024, we searched databases for original studies of at least 20 participants with MACS or AI. MACS was defined as postdexamethasone cortisol greater than 1.8 mcg/dL or postsurgical hypocortisolism. AI was defined by abnormal dynamic testing. QUADAS-2 was used to assess the risk of bias. Bivariate random effects meta-analysis was used to generate pooled diagnostic accuracy estimates. Results Seven studies on DHEA-S accuracy in diagnosing MACS (574 patients with MACS, 830 referent individuals), and 2 studies on DHEA-S accuracy in diagnosing AI (52 patients with AI, 59 referent individuals) were included. A meta-analysis of studies using DHEA-S cutoff between 60 and 70 mcg/dL to diagnose MACS demonstrated a sensitivity of 82% (95% CI, 64%-93%) and a specificity of 82% (95% CI, 74%-88%). In the 2 studies evaluating DHEA-S in diagnosing AI, the reference standard was a 1-mcg cosyntropin stimulation test. The sensitivity of DHEA-S for diagnosing AI ranged from 70.3% to 86.7%, and the specificity was 87.1%. Most studies were at a moderate risk of bias. Conclusion Based on limited heterogeneous evidence, measurement of DHEA-S provides additional value in diagnosing MACS, as well as AI.

Background: Acute disseminated encephalomyelitis (ADEM) is a demyelinating syndrome observed in myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) but there are limited data on application of this definition to its cerebral attacks or in adults with this disease. Methods: We analyzed patients from the Mayo Clinic MOGAD cohort ( n = 263) with cerebral attacks. We assessed whether children (<18 years-old) and adults (⩾18 years-old) fulfilled the 2013 ADEM definition. Results: We identified 89 patients (children, 34; adults, 55) and 55/89 (62%) were of female sex. Acute magnetic resonance imaging (MRI) abnormalities included: poorly demarcated T2 lesions (white matter, 85 (96%); deep gray matter, 41 (46%); T1-hypointense lesions (42 (47%)). Forty-two patients did not fulfill the ADEM definition due to: monofocal syndrome, 9; or no encephalopathy, 33. The remaining 47 patients (53%: children, 27/34 (79%); adults, 20/55 (36%)) fulfilled the ADEM definition, and 14 had preceding attacks, and 34 had subsequent attacks relative to ADEM episode. The features in children and adults with ADEM were broadly comparable. Conclusion: Applying the ADEM definition to MOGAD cerebral attacks highlighted that an update of the 2013 ADEM definition would be beneficial and could explicitly state its application to both adults and children and allow it to be applied to attacks at any time during the disease course.

Background: Lung cancer ranks as the leading cause of cancer-related mortality worldwide. The complexity of tumor delineation, crucial for radiation therapy, requires expertise often unavailable in resource-limited settings. Artificial Intelligence (AI), particularly with advancements in deep learning (DL) and natural language processing (NLP), offers potential solutions yet is challenged by high false positive rates. Purpose: The Oncology Contouring Copilot (OCC) system is developed to leverage oncologist expertise for precise tumor contouring using textual descriptions, aiming to increase the efficiency of oncological workflows by combining the strengths of AI with human oversight. Methods: Our OCC system initially identifies nodule candidates from CT scans. Employing Language Vision Models (LVMs) like GPT-4V, OCC then effectively reduces false positives with clinical descriptive texts, merging textual and visual data to automate tumor delineation, designed to elevate the quality of oncology care by incorporating knowledge from experienced domain experts. Results: The deployment of the OCC system resulted in a 35.0% reduction in the false discovery rate, a 72.4% decrease in false positives per scan, and an F1-score of 0.652 across our dataset for unbiased evaluation. Conclusions: OCC represents a significant advance in oncology care, particularly through the use of the latest LVMs, improving contouring results by (1) streamlining oncology treatment workflows by optimizing tumor delineation and reducing manual processes; (2) offering a scalable and intuitive framework to reduce false positives in radiotherapy planning using LVMs; (3) introducing novel medical language vision prompt techniques to minimize LVM hallucinations with ablation study; and (4) conducting a comparative analysis of LVMs, highlighting their potential in addressing medical language vision challenges.

Abstract Molecular characterization of high-grade B-cell lymphoma, not otherwise specified (HGBCL-NOS), is hindered by its rarity, evolving definition, and poor diagnostic reproducibility. To address this challenge, we analyzed 92 HGBCL-NOS tumors collected across Lymphoma/Leukemia Molecular Profiling Project sites. Leveraging comparison cohorts of diffuse large B-cell lymphoma, NOS (DLBCL-NOS) and Burkitt lymphoma (BL), and molecular frameworks described in these entities, our analysis revealed a heterogenous molecular landscape, reminiscent of DLBCL-NOS but with an enrichment of BL features. By cell-of-origin classification, 59% were germinal center B-cell–like (GCB), and 25% were activated B-cell–like (ABC). LymphGen, a genetic classifier for DLBCL-NOS, assigned a genetic subtype to 34% of HGBCL-NOS. Although classification rate was lower than in DLBCL-NOS (66%), assigned subtypes spanned the spectrum of LymphGen classes, including 31% of ABCs classified as MCD. Features differentiating HGBCL-NOS from DLBCL-NOS included MYC rearrangement (47% vs 6%); dark zone signature (DZsig) expression (45% vs 7%); and more frequent mutation of ID3, MYC, CCND3, and TP53, all common to BL. A genetic classifier that differentiates DLBCL-NOS from BL classified 53% of DZsig+ tumors as BL-like, and those classified as DLBCL-like were frequently BCL2-rearranged. Among DZsig− GCB tumors, 95% were DLBCL-like. Centralized pathology review reclassified almost half of tumors as DLBCL-NOS but did not identify a more homogenous HGBCL-NOS population, with no difference in features between confirmed and reclassified tumors. In conclusion, molecular testing enables a subset of HGBCL-NOS to be assigned to established categories. Based on rarity and diagnostic challenges, broader inclusion of HGBCL-NOS should be considered in biomarker-driven DLBCL trials.