Sara, Jaskanwal D S

Background Studies have demonstrated an association between endothelial dysfunction and major depressive disorder (MDD). However, the link between coronary endothelial dysfunction (CED) and an incident diagnosis of MDD across sexes is unclear. Methods Patients with nonobstructive coronary artery disease (stenosis <40%) underwent an invasive assessment of CED. Macrovascular CED was defined as a percentage change in coronary diameter in response to acetylcholine of ≤−10% compared with baseline. Microvascular CED was defined as a percentage change in coronary blood flow in response to acetylcholine of ≤−50% compared with baseline. In the period after the index procedure, patients were followed up for developing a diagnosis of MDD, and logistic regression was performed to assess the association between baseline CED and incident MDD. Results In total, 2280 patients underwent invasive testing for CED. A total of 516 patients (23%) underwent an evaluation for MDD at a date after the index procedure (mean±SD age, 53±12 years; 72% women). A total of 160 (31%) were diagnosed with MDD. The percentage change in coronary diameter in response to acetylcholine was lower in those diagnosed with MDD in all patients (−10.8% versus −5.3%; P =0.008), and in men (−19.0% versus −4.8%; P =0.001). In men, a higher proportion of those with macrovascular CED were diagnosed with MDD compared with those not diagnosed with MDD (59% versus 38%; P =0.035). In multivariable analyses, macrovascular CED was associated with MDD in men (odds ratio: 2.99 [95% CI, 1.26–7.45]; P =0.015). Conclusions Macrovascular CED is significantly associated with incident MDD in men with nonobstructive coronary artery disease. Endothelial dysfunction in the coronary arteries could thus be a helpful biomarker to identify patients at risk of MDD.

Abstract Importance Voice-based health technologies are growing rapidly, but they lack standardized terminology, which hinders interdisciplinary collaboration, research quality, and clinical translation. Objective The objective of this work is to develop universally accepted definitions in the rapidly evolving field of vocal biomarkers, as part of the VOCAL ( V ocal Biomarker Guidelines for O ntology, C lassification, A pplication, and L ogistics) initiative, a structured, international consensus-based framework that aims to provide standards, and guidelines. Design VOCAL is a rigorous, international, multi-stage consensus-building study conducted in 2024-2025. Setting Multi-institutional collaboration between representatives from the Bridge2AI-Voice Consortium (North America) and the eVoiceNet Network (European Union), culminating in an in-person workshop at the 2025 Bridge2AI Voice Symposium. Participants A group of 24 international experts in medicine, clinical research, speech and language, audio signal processing, statistics, methodology, regulation, ethics. Methods VOCAL’s iterative process involved five rounds of review, feedback, and an in-person workshop at the international 2025 Bridge2AI Voice Symposium, ensuring the incorporation of diverse perspectives and achieving a robust agreement on the proposed definitions. Main outcomes and measures Consensus-based definitions for vocal biomarkers, spanning from broad concepts (biomarker, digital biomarker, vocal biomarker) to domain-specific measures (cardio-respiratory acoustic, voice, speech/articulatory, cognitive/language). Results A hierarchical continuum model of vocal biomarkers was established. We first distinguished between the concepts of vocal measures and vocal biomarkers. We then defined terms from broad, overarching concepts (Level 0: Biomarker, Digital Biomarker, Vocal Biomarker) to more specific physiological and cognitive domains (Level 1: Cardio-Respiratory Acoustic; Level 2: Voice; Level 3: Speech/Articulatory; Level 4: Cognitive/Language, including linguistic and paralinguistic subtypes). Conclusions and Relevance This work provides a shared vocabulary that is essential for fostering communication through interdisciplinary collaboration, improving the quality and efficiency of research and development, and ensuring the ethical, reliable, and scalable deployment of future voice-based health technologies. It lays foundational groundwork for upcoming guidelines and standards, which are crucial for advancing the field of vocal biomarkers into widespread clinical utility. Key points Question Can we establish an international consensus on the definitions related to vocal biomarkers? Findings Through a multi-stage international consensus process involving expert representatives from the Bridge2AI-Voice Consortium and eVoiceNet Network, a hierarchical model of vocal biomarkers was developed, defining terms from broad concepts (biomarker, digital biomarker, vocal biomarker) to specific physiological and cognitive domains (cardio-respiratory acoustic, voice, speech/articulatory, cognitive/language). Meaning Standardized definitions for vocal biomarkers provide an essential shared vocabulary for interdisciplinary collaboration and lay the foundational groundwork for future guidelines needed to advance the implementation of voice-based health technologies into clinical practice and clinical research.

Background A subset of individuals with major depressive disorder (MDD) have a high burden of cardiovascular risk factors and cerebral small‐vessel disease, implicating vascular disease in the development of depression. Cross‐sectional studies demonstrate a link between endothelial dysfunction and MDD, but the prospective association between peripheral endothelial dysfunction (PED) and an incident diagnosis of MDD is unknown. Methods and Results Patients undergoing a baseline assessment of cardiovascular risk were evaluated for PED using reactive hyperemia–peripheral arterial tonometry (≤1.8 consistent with PED). Patient medical records were reviewed to identify those who underwent a formal clinical evaluation of MDD after the index PED evaluation. The frequency of PED was compared in those with and without MDD. Logistic regression analyses were performed to assess the association between baseline PED and incident MDD. Between January 2006 and December 2020, 1614 patients underwent testing for PED. Four hundred eighty‐four (30.1%) patients underwent a formal evaluation for MDD after (0–15 years) the index procedure (mean±SD age, 52.8±13.8 years; 65.2% women). Of these, 157 (32.4%) had PED and 108 (31.0%) were diagnosed with MDD. Individuals with MDD had a higher frequency of PED (40.2% versus 30.2%; P =0.034) compared with those without MDD. In multivariable analyses, PED was significantly associated with MDD (odds ratio, 2.3 [95% CI, 1.4–3.8]; P <0.001). Conclusions PED is significantly associated with incident MDD. Thus, PED may be a useful marker to identify individuals at increased risk of depression who may benefit from more frequent and earlier management strategies.

Background Myocardial bridging (MB) is accompanied by the dynamic extravascular compression of epicardial coronary arteries, leading to intracoronary hemodynamic disturbance with abnormal coronary flow profiles. We aimed to evaluate the prognostic implications of resistive reserve ratio (RRR), a composite measure of flow and pressure parameters that represents the vasodilatory capacity of the coronary arteries, in patients with angina with nonobstructive coronary artery disease (ANOCA) and MB, in comparison with coronary flow reserve (CFR). Methods and Results In this retrospective cohort study, we included patients with ANOCA who underwent coronary reactivity testing, where MB was identified by transient constriction in coronary artery segments between systole and diastole. Abnormal CFR and RRR were defined as <2.5 and <2.62, respectively. Major adverse cardiac events, including cardiovascular death, stroke, myocardial infarction, heart failure, and late revascularization, served as outcomes. Among 1251 patients with ANOCA, 191 (15.3%) had MB. The prevalence of abnormal CFR or RRR was not significantly different between patients with and without MB ( P =0.144 and P =0.398, respectively). Over a median follow‐up time of 6.9 years, abnormal RRR predicted major adverse cardiac events in patients with MB (hazard ratio [HR], 4.38 [95% CI, 1.71–11.21]; P =0.002) and without MB (HR, 1.91 [95% CI, 1.38–2.64]; P <0.001). Abnormal CFR predicted major adverse cardiac events in patients without MB (HR, 2.15 [95% CI, 1.54–3.00]; P <0.001), whereas it was not predictive of major adverse cardiac events in patients with MB (HR, 2.29 [95% CI, 0.93–5.65]; P =0.073). Conclusions In patients with ANOCA and MB, impaired RRR was superior to impaired CFR in distinguishing patients at a higher risk of future adverse events, suggesting that RRR may serve as a risk stratification tool in patients with MB and ANOCA.

Background Recent studies have indicated high rates of future major adverse cardiovascular events in patients with Takotsubo cardiomyopathy (TC), but there is no well‐established tool for risk stratification. This study sought to evaluate the prognostic value of several artificial intelligence‐augmented ECG (AI‐ECG) algorithms in patients with TC. Methods and Results This study examined consecutive patients in the prospective and observational Mayo Clinic Takotsubo syndrome registry. Several previously validated AI‐ECG algorithms were used for the estimation of ECG‐ age, probability of low ejection fraction, and probability of atrial fibrillation. Multivariable models were constructed to evaluate the association of AI‐ECG and other clinical characteristics with major adverse cardiac events, defined as cardiovascular death, recurrence of TC, nonfatal myocardial infarction, hospitalization for congestive heart failure, and stroke. In the final analysis, 305 patients with TC were studied over a median follow‐up of 4.8 years. Patients with future major adverse cardiac events were more likely to be older, have a history of hypertension, congestive heart failure, worse renal function, as well as high‐risk AI‐ECG findings compared with those without. Multivariable Cox proportional hazards analysis indicated that the presence of 2 or 3 high‐risk findings detected by AI‐ECG remained a significant predictor of major adverse cardiac events in patients with TC after adjustment by conventional risk factors (hazard ratio, 4.419 [95% CI, 1.833–10.66], P =0.001). Conclusions The combined use of AI‐ECG algorithms derived from a single 12‐lead ECG might detect subtle underlying patterns associated with worse outcomes in patients with TC. This approach might be beneficial for stratifying high‐risk patients with TC.

Cardiovascular disease is often a disease of aging. Considerable advances in our understanding of the biological mechanisms of aging have been made; yet, cardiovascular disease remains the leading cause of death in the United States urging a continued search for novel risk factors to target for preventing and treating disease. Mental stress (MS) is emerging as an important risk factor, and while progress has been made in understanding the link between MS and cardiovascular disease, the precise mechanisms of a putative causal relationship require greater clarification. In the current review, we (1) summarize our current understanding of the pathological effects of MS on vascular health; (2) describe important aspects of the pathobiology of vascular aging including inflammation, oxidative stress, mitochondrial dysfunction as well as novel processes such as genomic instability, epigenetic alterations, and nutrient signal pathways; (3) highlight similarities in the downstream biologic effects of aging and MS on vascular health with an emphasis on cellular and molecular processes that could be used to develop novel prognostic markers and treatment strategies for cardiovascular disease; (4) discuss lifestyle and pharmacological methods that target indicators of aging whose role could be translated into approaches managing the effects of MS; and (5) outline important future steps that should be considered in this area of research including the need for prospective clinical trials and for creating greater collaboration between preclinical aging researchers and clinical investigators managing MS.