Fokken, Shawn C.

Objectives Long-term symptoms following infection with acute respiratory syndrome coronavirus-2 (SARS-CoV-2), termed post-acute sequelae of SARS-CoV-2 infection (PASC) or Long COVID (LC), persist beyond 90 days and may impact at least 10% of patients with acute infection. The exact cause of LC remains unknown, but several theories include persistent viral particles, immune dysfunction, and autonomic nervous system (ANS) imbalance, particularly involving the vagus nerve. Given the role of the vagus nerve in inflammation regulation, vagal nerve stimulation (VNS) is being explored as a treatment option. The present study aimed to evaluate the feasibility, safety, and exploratory effects of a handheld external transcutaneous cervical non-invasive VNS (tcVNS) on the primary endpoint of Post-COVID Functional Status (PCFS) grade, alongside secondary outcomes such as LC-related fatigue and other symptoms. Methods Participants from our Post COVID Care Clinic were randomized into treatment (tcVNS treatments two minutes, three times a day) and control (no VNS) groups for a study period of 12 weeks. Participants completed validated questionnaires, PET-CT scans, and inflammatory cytokines at baseline and 12 weeks. Results All randomized patients (8 tcVNS, 10 control) completed the 12-week study. Participants randomized to tcVNS were observed to have improvements in PHQ-9, PROMIS-F, and COMPASS-31 when compared to controls, but these differences were not statistically significant. Cortisol and DHEA were also observed to increase less in the tcVNS group when compared to the control group, but these changes were also not statistically significant. Conclusions tcVNS was well tolerated and may be a promising therapeutic approach for LC, a chronic disease with no approved treatments and very low rates of complete recovery.

Conventional cigarette smoking remains a leading preventable cause of morbidity and mortality despite declining prevalence, yet evidence-based treatments remain underused. This narrative review examines guideline-supported therapies and emerging approaches, including digital tools, neuromodulation, and harm-reduction strategies. Standard care typically combines FDA-approved pharmacotherapy with behavioral counseling. Digital interventions can extend access and support adherence, particularly when integrated with pharmacotherapy and follow-up. Repetitive transcranial magnetic stimulation (rTMS) can be considered as an adjunctive option for patients who do not respond to pharmacotherapy and is FDA-approved. For patients unable to quit, structured harm-reduction strategies may help reduce risk while supporting progression toward eventual abstinence. These approaches should be used alongside, not in place of, guideline-recommended pharmacotherapy and behavioral counseling, which remain the gold standard for care. This review outlines a pragmatic, primary care–oriented model that integrates stepped-care with harm-reduction strategies.

Purpose While the clinical utility for Point-of-Care Ultrasound (POCUS) is well-established through its use in clinical practice to enhance diagnostic accuracy, expedite care, and improve patient interactions/communication, its impact on patient experience in outpatient consultative settings remains largely underexplored. We sought to evaluate patients’ experience and satisfaction by incorporating POCUS use during outpatient consultations. Methods In this prospective, cross-sectional survey study conducted in a consultative outpatient internal medicine practice, a continuous sample of 100 patients undergoing POCUS during routine medical evaluations participated. We assessed patient perspectives using a survey that was adapted from validated instruments. The following items were evaluated using the anonymized survey: the extent of patient understanding, the integration of POCUS into the consultation, its impact on patient-doctor communication, perceived quality of care, and overall patient experience. Results Most respondents felt better informed about their health (88%), more thoroughly examined (94%), and reported improved confidence in their physician’s assessment (92%) after the POCUS exam. In addition, POCUS was perceived as a natural part of the consultation (95%) and minimally burdensome (93%). Overall, 96% of study respondents agreed that POCUS improved their quality of care, and 98% described their experience as positive or very positive. Open-ended comments emphasized the immediacy of results, enhanced communication, and cost-effectiveness of the POCUS experience. Conclusion Incorporating POCUS in this environment improved patients’ perceptions of their physician, clinic, and overall care. These findings support the broader adoption of POCUS in similar clinical settings and its potential impact on healthcare delivery and patient satisfaction.

Background: Artificial intelligence (AI) is increasingly being integrated into healthcare, with applications ranging from predictive analytics to clinical decision support. In clinical nutrition, AI tools offer opportunities to improve workflow efficiency, enhance dietary assessment, and personalize nutrition care. Despite growing interest, little is known about registered dietitian nutritionists’ (RDNs) perceptions of AI in clinical practice. The aim of the present study was to assess RDNs’ attitudes toward AI use within a large healthcare system, along with their perceived barriers in this regard. Methods: A cross-sectional survey was developed through expert review and distributed electronically via REDCap to RDNs across Mayo Clinic’s academic campuses and affiliated health system sites. The 23-item survey included Likert-scale items addressing AI’s potential utilization within clinical care, perceived benefits and risks, and readiness for adoption. Responses were summarized using descriptive statistics. Factor analysis identified underlying constructs related to AI attitudes. Differences stratified by age and years of experience were evaluated using ANOVA. Results: Of the 185 RDNs invited, 64 (35%) responded. Two factors emerged: optimism regarding AI usage (Cronbach’s α = 0.94) and skepticism about implementation (α = 0.76). The overall mean ± SD score for optimism was 0.1 ± 0.6 (neutral), while skepticism averaged 1.0 ± 0.6 (moderate). Skepticism differed by years of experience (p = 0.012), with the lowest levels observed among RDNs with ≥21 years of practice. No significant differences were observed across age groups. Discussion: RDNs demonstrated neutral attitudes toward AI use but expressed concerns about accuracy, training, and implementation challenges. Addressing these concerns through education and structured implementation strategies may facilitate successful adoption of AI in dietetic practice.

Abstract Background Clinical nutrition (CN) is becoming increasingly complex because of the rising prevalence of chronic illness, cancer, and malnutrition‐related conditions such as short bowel syndrome and refeeding syndrome. Despite its clinical significance, nutrition education among US physicians remains limited. Simultaneously, large language model (LLM)–based artificial intelligence assistants (AIAs) have emerged as tools to support complex clinical decision‐making but remain largely untested in CN. Methods This retrospective study evaluated four LLM‐based AIAs—ChatGPT (OpenAI), OpenEvidence (OpenEvidence Inc), Gemini (Google, Google DeepMind), and Copilot (Microsoft Corporation)—using five complex CN cases from our nutrition support service. Each AIA was queried with patient‐specific CN questions. Responses were blinded and reviewed by five physician CN experts using an eight‐item assessment tool evaluating clarity, relevance, evidence, and clinical utility. Results All AIAs produced clinically appropriate responses, with Gemini scoring highest in relevance (4.04) and clarity (4.16). Overall satisfaction scores ranged from 3.08 (Copilot) to 3.84 (Gemini). Citation quality and originality of insights varied and were generally limited, and no consistent differences in performance were observed across the five cases among the four AIAs. Conclusion LLM‐based AIAs can reliably replicate expert reasoning in CN. Although not yet a source of novel clinical insights, the true potential of this approach may lie in its application among physicians without specialized expertise in CN, helping to bridge existing knowledge gaps in nutrition care. Presenting full clinical cases, as shown in this study, could support AIA‐enabled e‐consultation in the future, thereby addressing gaps in CN education.

Objective: This study evaluated the feasibility and satisfaction of using a wearable brain activity sensing device for stress reduction among patients experiencing Long COVID (LC). Patients and Methods: Patients with LC (N = 45) were invited to participate in an open-label pilot study. Participants were asked to use a brain-sensing electroencephalogram (S-EEG) wearable device (Muse-S™) daily for 90 days and followed for an additional 90 days (180 days total participation). Study enrollment began June 28, 2022, and ended July 28, 2023. Results: Patients were predominantly female (82%), white (96%), and with an average age of 47.6 (±12.5) years. At the end of treatment (90 days), cognition, sleep, self-efficacy, and quality-of-life quality of life improved ( P < .001 to P = .04). In addition, stress and anxiety were significantly reduced ( P < .001). These significant changes persisted by end-of-study (180 days). For stress ( P = .023) and anxiety ( P = .033), a change from the baseline during follow-up was significantly associated with the amount of S-EEG usage. The end-of-study satisfaction survey indicated that patients were very satisfied with the S-EEG device, and 97% planned to continue using it. Conclusion: Results suggest that the S-EEG device improved cognition in LC, which is one of the main severe symptoms we see in our LC clinic. In addition, it helped reduce stress and anxiety. These findings have important clinical implications for LC patients using S-EEG as an adjunct to concurrent LC clinical care which includes pharmacotherapies.

Objectives: To identify patient characteristics, health concerns, and barriers to care based on overweight or obesity. Methods: A 50-question anonymous survey was administered to patients. Data were compared by body mass index (BMI). Results: Among 3976 distributed surveys, 899 were returned and 682 were analyzed. Most respondents were women (60%), White (94%), and married/partnered (65%) and had some college education (80%). Younger and unmarried persons had higher BMI ( P < .001). Concern for quality of life ( P < .001) and importance of lifestyle changes ( P = .006) increased with BMI, but confidence in making changes decreased as BMI increased ( P < .001). Perceived good health decreased with increasing BMI ( P < .001), whereas depression and other comorbid conditions increased. Self-esteem decreased and stigma increased with higher BMI (both P < .001). Weight discussions with clinicians ( P < .001) and belief that clinicians should be involved in weight management ( P = .002) increased with BMI, yet self-perception of being judged by clinicians also increased ( P < .001). As BMI increased, delays in seeking health care increased ( P < .001). Conclusions: This survey study highlights perceived health concerns and barriers to care among persons with overweight and obesity. With higher BMI, self-esteem decreased, and stigma, self-perception of poor health, perception of being judged by clinicians, and delay in seeking medical care increased.

Background Over the past few years, a growing number of studies have explored massage robots. However, to date, a dedicated systematic review focused solely on robot-assisted massage has not been conducted. Objective To systematically identify and summarize evidence from studies concerning robot-assisted massage in healthcare settings. Methods An extensive literature search, involving electronic databases Ovid and Scopus, was conducted from the inception of the databases up to March 2023. This systematic review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement, and relevant papers were chosen based on the predefined inclusion criteria. Given the substantial methodological diversity among the included studies, a qualitative analysis was conducted. Results Seventeen studies met the inclusion criteria, comprising 15 preliminary trials, one quasi-experimental study, and one randomized controlled trial. Approximately 29% of the studies focused on the application of robotic massage for patients, 24% targeted both healthy volunteers and patients, and the remaining 47% were preclinical trials assessing the effectiveness of robotic massage solely on healthy volunteers. Primary interventions included robotic massage for oral rehabilitation, scalp massage, low back massage, shoulder massage, and full-body massage. All studies provided evidence that robotic massage interventions can enhance health and well-being, indicating a promising future for the integration of robotics in the field of massage therapy. Conclusions In general, robotic massage interventions offer physical and mental health benefits. Robot-assisted massage may be integrated into care provision as an adjunct to enhance human well-being. Nonetheless, further research is needed to confirm these findings.

Background: Electronic massagers have gained popularity for their non-invasive and cost-effective approach to healthcare. However, existing electronic massagers require manual manipulation, leading to inconsistency. Objective: To investigate the feasibility and acceptability of the Electronic Massager—Expert Manipulative Massage Automation (EMMA) among the American population. Methods: A single-arm pilot study was conducted at Mayo Clinic Rochester campus. Participants received massage therapy with the EMMA treatment model and completed a demographics and Satisfaction Survey Questionnaire. Data were collected using REDCap, and statistical analysis was performed. Results: Twenty healthy volunteers (13 women, 7 men; median age, 47 years) participated and completed the intervention within 2 weeks. No adverse events were reported. Overall, the acceptability and satisfaction of massage utilizing EMMA were high, with all participants finding the study worthwhile, willing to participate again, and willing to recommend the study to others. Regarding the overall experience, 65.0% reported a better-than-expected experience. Responses to open-ended post-treatment questions showed that most participants enjoyed the warmth (35%), pressure (25%), and relaxation (20%) provided by EMMA, with the majority suggesting no changes or improvements were needed. However, some participants expressed a desire for an expanded massage area (20%). Conclusions: This study suggests that the EMMA massager has high acceptability and satisfaction among healthy volunteers, thus demonstrating its feasibility. However, further research is needed to optimize EMMA and assess its clinical effectiveness.