Publications by Year: 2026

IMPORTANCE: Home blood pressure monitoring (HBPM) is essential and universally recommended for hypertension management, but patterns of real-world patient engagement with HBPM have not been studied and remain largely unknown.

OBJECTIVE: To evaluate patient engagement with HBPM in a remote hypertension management program.

DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study analyzing prospectively collected program data was conducted within a remote hypertension management program at a large academic health care system, Mass General Brigham, in Boston, Massachusetts. Data were collected from from September 2018 to June 2022. Adults with uncontrolled hypertension enrolled in the program were eligible for inclusion. Data analyses were conducted from February to April 2025.

INTERVENTIONS: Patients received free automated HBPM devices, education, and ongoing personalized support from health care navigators via telephone and messaging, with algorithm-guided medication titration.

MAIN OUTCOMES AND MEASURES: The primary outcome was engagement at baseline. Weekly HBPM frequency was categorized as no engagement (0 measurements), low engagement (1-11 measurements/week), intermediate engagement (12-23 measurements/week), and high engagement (24-28 measurements/week).

RESULTS: A total of 3390 patients were enrolled in the remote hypertension program; median (IQR) patient age was 61 (52-69) years, with 1958 (57.8%) female patients. Mean (SD) systolic BP at baseline was 143 (13) mm Hg, and most patients had comorbidities, including 1369 patients (40.4%) with atherosclerotic cardiovascular disease and 996 (29.4%) with diabetes. At baseline, 1107 patients (32.7%) had no engagement, 484 (14.3%) had low engagement, 618 (18.2%) had intermediate engagement, and 1181 (34.8%) had high engagement.

CONCLUSIONS AND RELEVANCE: In this cohort study of a remote hypertension management program, patient engagement with HBPM was suboptimal despite free devices, education, and personalized support with a navigator. To support optimal HBPM, innovative methods of BP monitoring that are more convenient and less burdensome for patients may enhance engagement and improve hypertension management outcomes.

IMPORTANCE: Despite increasingly widespread use of artificial intelligence (AI)-driven ambient scribes in medicine, the extent to which they are associated with clinician practice is not well studied.

OBJECTIVE: To characterize differences in documentation and treatment of psychiatric symptoms in primary care outpatient notes generated using ambient scribes compared with human or no scribes.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study used a matched retrospective case-control design to evaluate primary care annual visit notes from the Massachusetts General and Brigham and Women's Hospital systems between February 2023 and February 2025. A random sample of notes from 4 types of visits, matched 1:1 using sociodemographic and clinical features, was used: those using an ambient scribe, those using a human scribe, those occurring during the same period without a scribe (contemporaneous), and those occurring prior to scribe deployment. Data analysis was performed from April 25 to May 1, 2025.

EXPOSURE: Use of an AI ambient scribe.

MAIN OUTCOMES AND MEASURES: Neuropsychiatric symptom documentation, in terms of estimated Research Domain Criteria (RDoC), using a Health Insurance Portability and Accountability Act-compliant large language model (GPT-4o version gpt-4o-11-20; OpenAI); antidepressant prescriptions and diagnostic codes; and referral for mental health follow-up.

RESULTS: Among 20 302 notes, the mean (SD) age of the patients was 48 (14) years and 11 960 (59%) were for visits by female patients; 1026 (5%) met criteria for moderate or greater depressive symptoms by Patient Health Questionnaire-9 score. Estimated levels of RDoC symptoms in all 6 domains were significantly greater in the AI-scribed notes compared with other groups. In a multiple logistic regression model, likelihood of a psychiatric intervention (referral, new diagnosis, or antidepressant prescription) was significantly lower among AI-scribed visits compared with contemporaneous unscribed visits (adjusted odds ratio, 0.83; 95% CI, 0.72-0.95), but not for human-scribed visits compared with contemporaneous unscribed visits (adjusted odds ratio, 0.97; 95% CI, 0.85-1.11).

CONCLUSIONS AND RELEVANCE: In this retrospective cohort study using a matched case-control design examining outpatient primary care notes, incorporation of AI ambient scribes in primary care was associated with greater levels of neuropsychiatric symptom documentation but lesser likelihood of documented management of psychiatric symptoms. Further study will be required to determine whether these changes are associated with differential outcomes.

IMPORTANCE: Restless legs syndrome (RLS) is a sleep-related movement disorder that affects approximately 3% of US adults to a clinically significant extent and can cause substantial sleep disturbance.

OBSERVATIONS: Restless legs syndrome is characterized by an overwhelming urge to move the limbs, typically the legs, often accompanied by unpleasant limb sensations (eg, achiness, tingling). Symptoms, provoked by immobility, are relieved while moving and are typically present or most severe in the evening or at night. Restless legs syndrome symptoms may lead to difficulty falling asleep, staying asleep, or returning to sleep. According to population-based studies, approximately 8% of US adults experience RLS symptoms of any frequency annually and 3% experience moderately or severely distressing symptoms at least twice weekly. Patients with RLS have impaired quality of life and elevated rates of cardiovascular disease (29.6% with coronary artery disease, stroke, or heart failure), depression (30.4%), and suicidal ideation or self-harm (0.35 cases/1000 person-years). Restless legs syndrome is common among patients with multiple sclerosis (27.5%), end-stage kidney disease (24%), and iron deficiency anemia (23.9%); during pregnancy and especially in the third trimester (22%); with peripheral neuropathy (eg, diabetic, idiopathic; 21.5%); and with Parkinson disease (20%). Other risk factors include family history of RLS, northern European descent, female sex (2:1 vs male sex), and older age (RLS prevalence of 10% in adults ≥65 years). Restless legs syndrome is diagnosed based on clinical history; polysomnography is not recommended for diagnosis. Iron supplementation with ferrous sulfate (325-650 mg daily or every other day) or intravenous iron (1000 mg) should be initiated for serum ferritin level less than or equal to 100 ng/mL or transferrin saturation less than 20%. If possible, medications associated with RLS, including serotonergic antidepressants, dopamine antagonists, and centrally acting H1 antihistamines (eg, diphenhydramine), should be discontinued. Gabapentinoids (eg, gabapentin, gabapentin enacarbil, pregabalin) are first-line pharmacologic therapy. In randomized clinical trials, approximately 70% of patients treated with gabapentinoids had much or very much improved RLS symptoms vs approximately 40% with placebo (P < .001). Dopamine agonists (eg, ropinirole, pramipexole, rotigotine) are no longer recommended as first-line medications due to the risk of augmentation, an iatrogenic worsening of RLS symptoms, which has an annual incidence of 7% to 10% with these medications. Patients who do not improve with first-line treatment or have augmented RLS often benefit from low-dose opioids (eg, methadone 5-10 mg daily).

CONCLUSIONS AND RELEVANCE: Restless legs syndrome affects approximately 3% of adults and can have negative effects on sleep and quality of life. Initial management includes cessation of exacerbating medications, as well as iron supplementation for patients with low-normal iron indices. If medication therapy is indicated, gabapentinoids are first-line treatment.

Cardiac magnetic resonance imaging (CMR) provides decisive advantages, particularly in coronary heart disease, myocarditis and cardiomyopathy. It accurately detects ischemia, scarring, edema and microvascular disorders, enables reliable risk stratification and supports treatment decisions such as revascularization or medication adjustments. Modern quantitative perfusion methods and artificial intelligence (AI)-based analyses further increase the diagnostic accuracy. In inflammatory myocardial and pericardial diseases, CMR using mapping techniques and late gadolinium enhancement (LGE) forms the basis for differentiated diagnostics and estimation of the prognosis. It also enables a precise etiological classification and provides prognostically relevant parameters in cases of hypertrophic, dilated, arrhythmogenic and restrictive cardiomyopathies. In the diagnostics of valvular diseases and the planning of interventional procedures and cardiac tumors, CMR provides essential additional information and demonstrates a high sensitivity and specificity. New techniques such as quantitative 4‑dimensional (4D) flow measurements, high-resolution 3D imaging and electrocardiograph (ECG)-independent scans will further increase its value. Due to the increasing number of CMR examinations, standardized procedures, qualified personnel and structured training programs are essential to ensure a high quality of care in the long term.