Citations

Hypertension is the main risk factor for cardiovascular disease (CVD), affecting 20–40% of Latin American (LATAM) adults, and responsible for more than two million deaths annually due to CVD. The different ethnic, economic, geographic, and cultural characteristics of the LATAM population influence the high prevalence of all cardiovascular risk factors (CVRF), particularly metabolic disturbances such as type 2 diabetes (DM2), obesity and the metabolic syndrome. Their main determinants in LATAM includes environment, food quality, social inequity, low education, political aspects, contextual behaviour, and genetics. The prevalence of overweight and obesity in LATAM increased during the last four decades reaching figures of 10–20% in childhood, 30–40% in adolescence, and 60–70% in adults. Many studies in the region have reported the extremely low rates of awareness, treatment, and control of CVRF in the general population of LATAM, particularly in patients with metabolic disorders, and the consequent high cardiovascular morbidity and mortality. This 2026 LATAM consensus is developed by a large group of experts from different LATAM countries, the USA and Europe, representing areas of internal medicine, cardiology, nephrology, endocrinology, geriatrics, paediatrics, pharmacology, and epidemiology. A careful search for novel studies in LATAM, together with new evidence that has emerged since the 2019 LATAM consensus, support the statements and recommendations in the current report. This update aims to provide clear and useful recommendations for health professionals to improve awareness, treatment, and control of hypertension and associated CVRF in the region.

Abstract Despite effective control of inflammation in rheumatoid arthritis (RA), persistent and severe pain remains a challenge. Dysregulated pain processing in the central nervous system may underlie this disconnect. The PainDETECT questionnaire, originally developed to identify neuropathic pain, may capture features of central sensitization. We hypothesized that neuropathic-like pain at diagnosis predicts worse pain prognosis in early RA, independent of baseline pain severity and inflammation. We also explored brain activation patterns using neuroimaging. In this prospective cohort study, adults with newly diagnosed RA completed the PainDETECT questionnaire at baseline. Bodily pain was measured using the SF-36 Bodily Pain Subscale at baseline, 3, 6, and 12 months. C-reactive protein (CRP) was monitored. Linear mixed-effects models examined associations between PainDETECT, as a continuous measure, and bodily pain and CRP over time, adjusting for baseline outcome values. A neuroimaging substudy (n = 27) used task-based functional MRI to assess brain responses to evoked pressure pain. Among 158 participants (mean age 58.4 years; 35% male), 24.7% had likely neuropathic-like pain (PainDETECT ≥19) at baseline. Higher baseline PainDETECT scores were associated with worse bodily pain throughout follow-up in fully adjusted models (β = −0.43; 95% CI: −0.84 to −0.02; P = 0.043), independent of socio-demographics and comorbidities. No association was found between PainDETECT and CRP. On neuroimaging, higher PainDETECT scores correlated with increased activation in the left insula, dorsal anterior cingulate cortex, and left amygdala during evoked wrist pain. Neuropathic-like pain at diagnosis predicts a worse pain prognosis in early RA, independently of inflammation. Early identification may support more targeted and effective pain management.

Background: We aimed to develop automated data extraction pipelines with large language models (LLMs) to extract registry data from total hip arthroplasty (THA) operative notes and compare the performance with that of existing natural language processing (NLP) algorithms. Methods: We randomly sampled 1,000 primary THA cases from our institutional registry. Two human annotators manually reviewed each operative note for 3 data points: surgical approach, bearing surface, and fixation technique. All labeled THA notes were split into the development set (n = 239) and the testing set (n = 719). We developed a custom data extraction pipeline for each data point by combining an iteratively customized prompt with an LLM. The performance was compared with that of existing rules-based NLP algorithms. Results: The accuracy of LLMs was superior to that of NLP algorithms for all data points: surgical approach (96% compared with 94%), bearing surface (89% compared with 74%), and fixation technique (96% compared with 95%). Furthermore, the LLM accurately inferred the bearing surface for 80% of the notes that were ambiguous about the bearing surface. Conclusions: We developed LLM pipelines for extracting 3 registry-relevant data points from THA operative notes, demonstrating superior performance to existing NLP algorithms. Clinical Relevance: LLMs have the potential to impact clinical care, including the evaluation of electronic medical record free-text data. As registries serve as a cornerstone of orthopaedic evidence, this work demonstrates promise for LLMs to simplify, improve, and democratize the construction of registry databases from operative notes.

Background: Successful applications of artificial intelligence (AI) in healthcare have increased interest in how it could be integrated into orthopaedic surgery. However, orthopaedics surgeons’ current use of AI and attitudes toward its incorporation remain largely unexplored. The 2025 American British Canadian Travelling Fellowship Survey on AI in Orthopaedic Surgery aimed to assess AI use, knowledge, training, and attitudes among orthopaedic surgeons. Methods: The survey was administered from May 7 to September 4, 2025 to orthopaedic surgeons across Australia, New Zealand, the United Kingdom, and North America. Questions addressed demographics, AI training and use, and attitudes toward AI. Descriptive statistics summarized responses, chi-square tests compared AI use by geography and attitudes by career stage, and linear regression explored associations between demographics, AI behaviors, and outlook on AI. Results: Among 350 participants, most were trainees (45.1%) and from North America (42.9%). AI use exceeded training, and 79.9% rated their AI knowledge as average or poor. Trainees reported significantly more favorable attitudes toward AI than late-career respondents. Higher self-rated AI knowledge and AI use in clinical and research settings were associated with a more positive outlook on the future of AI in orthopaedics. Conclusions: These findings highlight the need for formal AI education, as use is widespread despite limited training, particularly among later-career surgeons. Future studies should reduce self-selection and career-stage imbalance and include additional demographic variables to improve generalizability. Level of Evidence: III . See Instructions for Authors for a complete description of levels of evidence.

Parkinson’s disease (PD) significantly affects patients’ quality of life through debilitating motor symptoms, such as Freezing of Gait (FoG). Continuous, in-home monitoring of FoG is essential for timely clinical intervention but remains challenging due to high power consumption, annotation cost, and the controlled environments required by current wearables. We introduce LIFT-PD (the source code is available at: https://github.com/shovito66/LIFT-PD ), a novel self-supervised learning (SSL) framework for real-time, patient-independent FoG detection that uniquely utilizes a single waist-worn accelerometer—an approach traditionally considered less optimal due to weaker gait signatures. LIFT-PD leverages SSL on unlabeled data collected from uncontrolled, real-world settings and employs a novel Differential Hopping Windowing Technique (DHWT) to address gait variability and dataset imbalance. Additionally, an opportunistic inference module selectively activates the deep learning model only during patient movement, significantly reducing power consumption and enabling continuous monitoring ( \(>\) 48 hours). Experimental results show that LIFT-PD achieves a 7.25% increase in precision and 4.4% improvement in accuracy compared to supervised and semi-supervised baseline models while requiring approximately 40% fewer labeled training samples. Evaluations across diverse patient characteristics-including severity, medication state, age, and gender-confirm the model’s robustness and clinical applicability, positioning LIFT-PD as a practical, energy-efficient, and scalable solution for continuous real-world FoG monitoring in PD.

Importance Exploring the relationship between moral distress and occupational burnout is necessary to understand the association between these constructs. Objective To evaluate moral distress among physicians and US workers, and to explore the association of moral distress with burnout, intent to leave (ITL) current position, and intent to reduce clinical work hours (ITR). Design, Setting, and Participants This cross-sectional national survey study included physicians from all specialties and a probability-based sample of employed nonphysicians. Participants were aged 29 to 65 years. Data were collected between October 19, 2023, and March 5, 2024. Data were analyzed from June 30 to October 20, 2025. Main Outcomes and Measures Moral distress was measured using the Moral Distress Thermometer (MDT, range 0-10), with a high level of moral distress defined by a score of 4 or higher. Burnout was measured using the complete Maslach Burnout Inventory (MBI). Professional fulfillment was measured using the Stanford Professional Fulfillment Index. ITL and ITR were measured using a standardized item with response options of none, slight, moderate, likely, and definitely. Results This survey study included 5741 physicians and 3501 nonphysician US workers. The median (IQR) age of physicians was 53 (44-62), and included 3262 men (58.0%), 2255 women (40.1%), and 107 individuals who responded other (1.9%). The mean (SD) moral distress score for physicians was 3.29 (2.81), with 2243 (39.1%) reporting a high level of moral distress (4 or more considered high). On multivariable analysis, women physicians had higher odds of moral distress (OR, 1.29; 95% CI, 1.12-1.48). Compared with internal medicine subspecialists, emergency medicine physicians (OR, 3.16; 95% CI, 2.27-4.4) and general internal medicine physicians (OR, 1.92; 95% CI, 1.42-2.59) were more likely to report high levels of moral distress. Mean emotional exhaustion and depersonalization scores, as well as the proportion of physicians with burnout, were higher with each 1-point increase in moral distress score. The overall correlation between the emotional exhaustion score and moral distress score was R = 0.55 ( P < .001) while the correlation between the depersonalization score and moral distress score was R = 0.50 ( P < .001). Additionally, 1068 of 3477 physicians (30.7%) with a moral distress score less than 4 had burnout symptoms compared with 1675 of 2231 physicians (75.1%) with scores of 4 or more ( P < .001). The prevalence of ITL and ITR was higher for each 1-point increase in moral distress score. For example, 619 of 3404 physicians (18.2%) with low moral distress reported ITL within 24 months compared with 748 of 2171 (34.5%) among those with high moral distress ( P < .001). Compared with other US workers, physicians had markedly higher odds of experiencing moral distress (OR, 4.40; 95% CI, 3.84-5.06). Conclusion and Relevance In this survey study, moral distress was common among physicians and experienced at higher rates than the general US working population. Understanding the differences between moral distress and burnout may allow organizations to more effectively implement interventions to address both concerns among clinicians.

Nodular fasciitis is a rapidly growing soft tissue tumor that typically arises in children and young adults. Histologically, it consists of short, sweeping, and intersecting fascicles of bland-appearing myofibroblasts. The majority of nodular fasciitis lesions harbor rearrangements involving the ubiquitin-specific protease 6 ( USP6 ) gene. Most lesions are benign, with a tendency to regress spontaneously or remain stable following conservative excision. However, rare cases have shown clinically aggressive behavior, including distant metastasis. More recently, morphologic variants with malignant features have also been reported. We present a 20-month-old boy who developed a rapidly enlarging facial mass following blunt trauma. The excised mass revealed a variant of nodular fasciitis displaying marked cellular pleomorphism and frequent atypical mitotic figures. Molecular analysis identified a COL3A1::USP6 fusion and a TP53 Y234C mutation. While the majority of facial lesions referred to plastic surgeons for excision are benign, this case highlights the need for a broad differential diagnosis that includes both benign and potentially malignant entities. It also emphasizes the importance of multidisciplinary evaluation and management in patients with complex and unusual pathologic diagnoses.

Abstract Background Progressive supranuclear palsy (PSP) is a tauopathy for which there is limited understanding of epidemiological risk factors. Objective The objective of this study was to identify premorbid nonmedical and medical risk factors for PSP diagnosis in a large prospective population‐based cohort. Methods We performed a matched nested case–control study using the UK Biobank (UKB) cohort consisting of >500,000 adults aged 37 to 73 years. PSP diagnoses were identified from 2007 to censor date (August 2025) and matched 1:10 by age and sex to control subjects without parkinsonism or dementia diagnoses. We derived risk factors using an iterative logistic regression approach. Results There were 240 incident PSP diagnoses in the UKB. In the fully adjusted model, premorbid depression (odds ratio [OR], 3.22; 95% confidence interval [CI], 2.30–4.50; P < 0.001), delirium (OR, 6.76; 95% CI, 4.08–11.19; P < 0.001), and functional gastrointestinal disorders (OR, 1.91; 95% CI, 1.39–2.63; P < 0.001) were associated with increased risk. Heavy alcohol consumption was associated with higher risk compared with moderate consumption (OR, 1.65; 95% CI: 1.21–2.26; P = 0.0017). Body mass index (BMI) and alcohol consumption had nonlinear risk profiles. Cancer diagnosis was inversely associated with PSP (OR, 0.56; 95% CI, 0.40–0.79; P < 0.001). Depression and delirium diagnoses remained significant 5 to 10 years before diagnosis. Conclusions In this large prospective cohort, PSP was associated with premorbid lifestyle practices and neuropsychiatric diagnoses years before diagnosis. This suggests a long premotor phase and highlights opportunities for earlier diagnosis and further mechanistic investigation. The inverse association with cancer mirrors the relationship seen in other neurodegenerative conditions and may point toward shared mechanisms. © 2026 International Parkinson and Movement Disorder Society.