Citations

Background: Incidental thyroid nodules (ITNs) detected on nonthyroid imaging contribute to thyroid cancer overdiagnosis, largely through downstream evaluation initiated by thyroid ultrasound (TUS). However, TUS follow-up rates for ITNs and their drivers in routine practice remain unclear. We quantified TUS utilization after ITN detection and identified patient, imaging, nodule, and reporting factors associated with this first step in the diagnostic cascade. Methods: We conducted a retrospective cohort study of adults without prior thyroid disease who underwent imaging that incidentally captured the thyroid at Mayo Clinic sites (2017–2023). A validated natural language processing pipeline identified ITNs and extracted nodule characteristics from radiology reports across multiple imaging modalities. The main outcome was the rate of TUS within 180 days after ITN detection. Clinical outcomes, including thyroid biopsy, thyroidectomy, and thyroid cancer diagnosis, were compared between patients who underwent TUS and those who did not. Factors associated with TUS utilization were assessed using multivariable logistic regression with penalized variable selection. Results: Among 115,683 patients who underwent thyroid-capturing imaging, 8426 (7.3%) had an ITN. These patients were predominantly female (64.6%) and White (89.7%), with a mean age of 61.7 years (standard deviation 15.2). Most nodules were detected on computed tomography (80.8%), most commonly from chest imaging (52.3%). Overall, 1677 patients with ITNs (19.9%) underwent TUS. In multivariable analysis, TUS use was independently associated with higher body mass index (odds ratio [OR], 1.20 per 10-unit increase; confidence interval [CI] [1.08–1.33]), nodule size ≥1.5 cm (OR, 1.79; CI [1.52–2.10]), and a radiologist recommendation (OR, 2.51; CI [2.12–2.98]), whereas older age was associated with lower odds of TUS (OR, 0.89 per 10-year increase; CI [0.84–0.93]). Patients undergoing TUS had higher rates of thyroid biopsy, partial thyroidectomy, and total thyroidectomy compared with those without it. All detected thyroid cancers (103 cases) occurred in the TUS group, representing 6.1% of that cohort. Conclusions: One in five patients with ITNs underwent TUS, representing a critical gateway to downstream diagnostic procedures and thyroid cancer detection. Factors associated with TUS utilization highlight opportunities to better define appropriateness of ultrasound after incidental nodule detection and to reduce unnecessary testing and treatment.

Objective: Patients with limited English proficiency often face barriers to accessing timely care. We evaluated whether Spanish-language Fast Pass messaging, combined with two-way Short Message Service (SMS) functionality, increased appointment acceptance rates among Spanish-preferring patients while maintaining equitable outcomes for English-preferring patients. Methods: A pre/post-quality improvement project was conducted at Mayo Clinic from November 2023 to June 2025. Epic’s Fast Pass, an automated appointment waitlist system, was enhanced with Spanish-language templates and bidirectional SMS in lieu of patient portal utilization. The primary outcome was the Fast Pass acceptance rate for Spanish-preferring patients. Balancing measures included acceptance among English-preferring patients. Secondary outcomes included scheduler efficiency and cost savings. Results: Prior to implementation, Spanish-preferring patients accepted 4.69% of Fast Pass offers compared with 7.57% for English-preferring patients. Post-implementation, acceptance rates for Spanish-preferring patients increased from 4.69% to 8.05%, a 71.6% improvement in the acceptance rate, exceeding the initial target of a 7.57% acceptance rate. Acceptance rates for English-preferring patients also improved, rising from 7.57% to 9.5%, or a 25.5% improvement in the acceptance rate. The intervention resulted in 344 additional Spanish-language accepted appointments and 29,883 additional English-language accepted appointments, both measured by unique patient appointments. The intervention also improved operational efficiency, saving more than 4,000 hours of scheduler time and reducing scheduling-related costs. Conclusions: Spanish-language concordant and SMS-enabled Fast Pass messages improved patient equity in appointment access while increasing scheduling efficiency and reducing operational costs. Health systems should adopt language-concordant digital communication strategies. Future research should expand to include additional languages and explore artifical intelligence–based scheduling support.

Odontogenic myxoma (OM) is an uncommon, locally aggressive odontogenic neoplasm with characteristic histologic and clinico-radiographic features but with potential for histologic overlap with other odontogenic and non-odontogenic entities and a non-specific immunoprofile. Widespread loss of heterozygosity (LOH) has been recently described in rare cases of OM. The aim of this study was to determine whether widespread LOH represents a recurrent molecular signature that can be leveraged for clinical decision-making. Allele-specific copy number variation data from chromosomal microarray were generated from 7 OM, comprising a combined prospective and retrospective cohort. Four tumors arose in the mandible and 3 in the maxilla in patients ranging in age from 18 to 94 years (median: 44), with tumor size ranging from 2.2 to 13.0 cm. Variable amounts of fibrous stroma (odontogenic “fibromyxoma”) were present in 4/7 OM, and hypercellularity not typically appreciated in conventional OM was present in 3/7 cases. All OM (7/7) demonstrated widespread LOH, with 5 cases showing a near-haploid/low hypodiploid genomes (multiple monosomies) and 2 cases showing evidence of pseudo-hyperdiploidy due to probable endoreduplication. Both pseudo-hyperdiploid cases were ≥10 cm in size; 1 represented local recurrence. Chromosomes 1 to 3, 6, 9, 11, 13, 15, and 22 demonstrated LOH in ≥75% of cases (chromosomes 1 to 3, 6, and 9 in 100% of cases), while chromosomes 5, 12, 19, and 20 universally retained heterozygosity. Altogether, widespread LOH is a recurrent event in OM and a novel finding in odontogenic pathology, and allele-specific copy number variation analysis can serve as a diagnostic adjunct in challenging cases.

BACKGROUND: It is unknown whether cardiac resynchronization therapy (CRT) improves systemic metabolomic profile by enhancing left ventricular function. The observational cohort study aimed to investigate the effect of CRT on left ventricular ejection fraction (LVEF) and circulating plasma metabolites in patients who had heart failure with reduced LVEF. METHODS: We prospectively screened patients with ischemic cardiomyopathy and nonischemic cardiomyopathy who received CRT with a defibrillator for LVEF ≤35% according to current guidelines. Clinical assessment included echocardiography and device interrogation. Blood samples for metabolomic analysis were collected before CRT and at 6-month follow-up. Plasma was subjected to gas chromatography-mass spectrometry and 1 H nuclear magnetic resonance-based metabolomic analysis. RESULTS: Totally 92 patients were enrolled, with a mean age of 67.3±11.3 years (37.0% female). LVEF was significantly improved from 28.9±7.6% at baseline to 36.0±11.3% at 6 months ( P <0.001) and to 40.1±12.6% at 12 months ( P <0.001). After CRT, 42 metabolite features were significantly decreased compared with the baseline. The ketone bodies, including 3-hydroxybutyrate ( P <0.001) and acetone ( P =0.01), were reduced. A branched-chain amino acid, isoleucine, was also decreased after CRT ( P =0.01). These metabolomic changes were mainly observed in the nonischemic cardiomyopathy group, while the metabolomic profile in the ischemic cardiomyopathy group was characterized by enhanced amino acid oxidation and elevated levels of lactate and pyruvate. The improvement in LVEF positively correlated with the ratio of changes in ketone bodies and isoleucine. CONCLUSIONS: CRT may modulate the systemic plasma metabolomic profile, which correlated with improvement in left ventricular function in patients with severe heart failure with reduced ejection fraction.

The advent of high-throughput sequencing technologies has revolutionized cardiovascular genetics, generating vast amounts of data. A major challenge in the genomic era is the efficient and accurate identification of causative genetic variants associated with cardiovascular disease. Artificial intelligence (AI)-driven computational approaches offer a powerful solution by enabling the automation of variant classification, improving consistency and reproducibility, and enhancing predictive accuracy. These methods may guide not only variant classification, variant effect prediction, and clinical prioritization, but also open the door to data-driven precision medicine, enabling more accurate and individualized diagnoses and targeted therapeutic strategies tailored to each patient’s unique genetic and clinical profile. This state-of-the-art review provides a structured overview of AI methodologies applied to cardiovascular genomics, beginning with rule-based expert systems that encode standardized guidelines for consistent variant interpretation. Next, we examine machine learning approaches capable of identifying complex patterns in annotated multimodal clinical and multi-omic datasets. The role of deep learning algorithms is highlighted for their ability to extract features from high-dimensional, unstructured data relevant to cardiovascular disease. In addition, the potential of generative AI is explored, including applications in synthetic data generation, variant impact prediction, and automated summarization of biomedical literature. Despite advances, several challenges remain, including data heterogeneity, the need for explainable AI models to elucidate the decision mechanisms, and the complexity linked to the integration of AI-based tools into clinical workflows. Addressing these issues requires interdisciplinary collaboration among clinicians, geneticists, data scientists, and bioinformaticians to ensure the effective translation of AI-generated insights into clinical practice. This review aims to provide a comprehensive perspective on the evolving role of AI in cardiovascular genomics and its implications for advancing precision medicine.

Importance Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C–related burden is critical for guiding prevention and treatment strategies. Objectives To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. Design, Setting, and Population This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Exposure Population-level LDL-C concentrations. Main Outcomes and Measures Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C–attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. Results In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C–attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Conclusions and Relevance Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.

ABSTRACT Tissue‐resident memory T cells (TRMs) are a distinct memory T‐cell subset that permanently reside in tissues such as the skin. In chronic immune‐mediated dermatoses, including psoriasis, atopic dermatitis, and vitiligo, TRMs are implicated in site‐specific “disease memory,” contributing to persistence and relapse at previously affected sites. This review synthesizes emerging concepts on TRMs in chronic inflammatory skin diseases and discusses clinical and translational implications, including TRM‐targeted therapies. Original human, animal, or in vitro studies evaluating TRMs in the pathogenesis or persistence of dermatologic diseases were included. In psoriasis, CD8 + TRMs (CD69 + CD103 + ) persisted in clinically healed skin. For atopic dermatitis, both CD4 + and CD8 + TRMs are implicated in maintaining Th2/Th22 inflammation. In vitiligo, autoreactive CD8 + TRMs at lesional margins mediate melanocyte destruction. Across dermatological diseases, TRMs share three core features: persistence in previously affected skin after clinical resolution, rapid reactivation by diverse triggers (stress, autoantigens, allergens, or cytokines) leading to site‐specific recurrence, and relative resistance to conventional therapies. Together, these properties provide a unifying framework linking tissue immune memory to the chronic, relapsing nature of inflammatory skin diseases. However, the dominant TRM pathways vary by disease, reflecting differences in immune polarization and antigen specificity. Targeting TRMs represents a promising strategy for disease control and serves as a biomarker of residual disease or flare. image

Importance In vivo biomarkers for detecting neuropathologies from repetitive head impacts (RHI), including chronic traumatic encephalopathy (CTE), are needed. Objective To evaluate the utility of plasma phosphorylated tau 217 (p-tau217), assess its performance as a beta-amyloid (Aβ) biomarker in participants with RHI exposure at risk for CTE, and explore concordance with CTE neuropathology in a postmortem subsample. Design, Setting, and Participants This longitudinal, multicenter, case-control study used data from the Diagnostics, Imaging, and Genetics Network for the Objective Study and Evaluation of CTE (DIAGNOSE CTE) Research Project, collected from September 2016 to October 2023. Participants were former American football players (case participants) and asymptomatic men unexposed to RHI (control participants). A subsample had available neuropathologic data. Exposures RHI, traumatic encephalopathy syndrome (TES) diagnoses, and levels of CTE certainty. Main Outcomes and Measures Plasma p-tau217 (classified as positive [≥0.63 pg/mL], intermediate [0.40-0.62 pg/mL], and negative [&amp;lt;0.40 pg/mL]), Aβ–positron emission tomography (PET; 18 F-florbetapir; with Aβ-positive defined as a standardized uptake value ratio [SUVR] ≥1.10), and tau-PET ( 18 F-flortaucipir). TES diagnoses were assigned by multidisciplinary consensus conference. Analyses of postmortem brains controlled for age, race, and APOE ε4 status. Results Among 231 participants (mean [SD] age, 57.75 [8.25] years), 177 were former football players (117 professional and 60 college) and 54 were unexposed participants. Former football players had higher baseline mean (SD) p-tau217 concentrations than unexposed participants (0.35 [0.26] pg/mL vs 0.27 [0.14] pg/mL; P = .008), although this was driven by a higher proportion of Aβ-PET–positive participants among former players. Plasma p-tau217 increased over time across the sample (B = 0.207 [95% CI, 0.117-0.298]; P &amp;lt; .001), with no significant time × exposure group interactions. Among football players, p-tau217 showed no time × group interactions with TES diagnosis, TES-CTE certainty, or RHI metrics. Higher p-tau217 concentration correlated with higher global Aβ-PET SUVR (B = 0.058 [95% CI, 0.053-3.501; P = .01), with a few discordant cases (5 participants were p-tau217–negative and Aβ-PET–positive; 7 participants were p-tau217–positive and Aβ-PET–negative). P-tau217 had similar areas under the curve for projecting Aβ-PET positivity as cerebrospinal fluid (CSF) p-tau181/Aβ42 and CSF Aβ40/42 measures (p-tau217: AUC, 0.88 [95% CI, 0.80-0.96]; CSF p-tau181/Aβ42: AUC, 0.89 [95% CI, 0.79-1.00]; CSF Aβ40/42: AUC, 0.85 [95% CI, 0.72-0.98]). Among 9 brain donors, 6 had CTE (stages II-IV; none with Alzheimer disease). Seven had negative or intermediate p-tau217, concordant with Aβ-PET. Two p-tau217 outliers with stage III CTE had normal concentrations upon additional testing. Conclusions and Relevance The findings of this study suggest that plasma p-tau217 concentration is unlikely to be useful for the detection of CTE, but it does show utility for ruling out Aβ pathology in participants at risk for CTE.

Introduction Cognitive symptoms such as ‘brain fog’ are frequent and disabling in patients with SLE. We aimed to develop and validate the Lupus Brain Fog Severity Scale (LBFSS), the first patient-reported outcome measure (PROM) for cognitive symptoms in SLE. Methods The LBFSS was developed using a multi-step international approach involving healthcare professionals and patients with SLE. Patients provided free-text descriptions of brain fog, generating candidate domains through thematic analysis (step 1). Domains were rated for relevance (step 2) and those retained converted into self-assessable items (step 3). The pilot LBFSS was iteratively refined (step 4). The finalised LBFSS was validated (step 5) in a large international SLE cohort. Psychometric evaluation included internal consistency, exploratory factor analysis and assessment of construct, convergent, known-groups and criterion-related validity. Results In step 1, 147 SLE participants across 39 countries generated 21 domains for cognitive symptoms, of which 13 were retained in consensus (step 2), converted into self-assessable items (step 3) and iteratively refined using patient and physician feedback. In step 5, validation of the LBFSS instrument in 378 patients from 36 countries demonstrated high internal consistency (Cronbach’s α=0.95) and a unidimensional structure explaining 62.2% of variance. LBFSS scores were significantly higher in participants reporting brain fog (p<0.0001), confirming known-group validity. Construct validity was supported by significant correlations with functional impact and symptom severity (ρ=0.46–0.65, p<0.0001), strong convergent validity with the Perceived Deficits Questionnaire-20 (ρ=0.84, p<0.0001) while the discriminative performance for presence versus absence of self-reported brain fog was high (area under the curve=0.85). Conclusion The LBFSS is a new, valid and feasible PROM to assess brain fog and cognitive symptoms in SLE.