Citations

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 Ileostomy creation is common among patients with colorectal cancer, diverticulitis, and inflammatory bowel disease. Surgical removal or diversion of the colon can result in nutrition complications, most notably dehydration—a leading cause of hospital readmission—and increased risk of kidney injury. Existing studies on fluid and electrolyte management after ileostomy largely focus on short bowel syndrome or high‐output stomas, overlooking the physiological implications of ileostomy creation, even in patients with normal output. Given the absence of standardized oral rehydration protocols and limited interventional data, a scoping review was conducted to map the current evidence on oral rehydration solutions for postoperative fluid and electrolyte management in adults without short bowel syndrome or high‐output stoma. Comprehensive searches across five databases identified 5738 articles, of which 6 met inclusion criteria. Eligible studies examined adults with ileostomy for any standard indication in which oral rehydration solution use was a study objective. The included studies were methodologically heterogeneous, encompassing randomized controlled, crossover, double‐blinded comparator, retrospective cohort, and qualitative designs. Collectively, available evidence supports a pivotal role for oral rehydration solutions in both short‐term and long‐term management after ileostomy, improving hydration and reducing complications. This review highlights the need for standardized, evidence‐based oral rehydration regimens and underscores opportunities to reduce postoperative morbidity, kidney injury, and hospital readmissions while optimizing long‐term outcomes in this growing patient population.

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.

Background/Objectives: Multi-cancer detection (MCD) tests have emerged as a promising tool to redefine the landscape of early cancer detection. Implementation of this novel technology will likely fall to primary care clinicians (PCC). The purpose of this study is to characterize and explore differences in PCCs perceptions and preferences towards MCD testing. Methods: Between March and May of 2023, this cross-sectional survey was administered to 281 PCCs, including physicians and advanced care providers practicing within an integrated healthcare system spanning five states. The survey collected data on self-reported characteristics, perceptions of MCD testing, and preferences for learning about MCD testing. Analysis was limited to those with no prior experience with MCD testing (N = 181, response rate 22.8%). Descriptive statistics summarized key variables and chi-square tests assessed differences in perceptions and preferences by key characteristics. Results: Most PCCs were interested in MCD testing (66.3%), but limited knowledge/awareness of MCD testing and confidence to manage patients with a positive test were observed, along with concerns around cost (76.7%) and misuse/poor implementation. The primary preferences for learning about MCD testing were online courses or classroom instruction (64.5%). Significant differences in perceptions and preferences for learning were observed by location, degree, and years in practice. Conclusions: PCCs in our study held positive views towards MCD testing, but gaps and variation in knowledge and confidence towards MCD testing and concerns around the cost and misuse/poor implementation were observed. While efforts to train and educate all PCCs on MCD testing is a critical first step, more research is needed to understand how best to support implementation tailored to individual and system-level needs and characteristics.

Background Coronavirus Disease 2019 (COVID-19) has led to dramatic changes including social distancing, closure of schools, travel bans, and issues of stay-at-home orders. The health-care field has been transformed with elective procedures and on-site visits being deferred. Telemedicine has emerged as a novel mechanism to continue to provide care. However, there remains a paucity of data regarding its efficacy in nutrition support, especially in patients with chronic intestinal failure (CIF). Objective Describe the utilization of telehealth in the routine management of CIF, particularly in the initiation and training of home parenteral nutrition (HPN). Methods A case series presenting our experience with the use of telemedicine to provide training for HPN for three patients. The manuscript describes the utility of telehealth in providing remote and adequate training for patients commenced on HPN during COVID-19 pandemic. Results Since the onset of the COVID-19 pandemic, we have successfully provided virtual training to three patients, including two who were noted to be severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive and one patient who could not be transferred to our facility for training. For SARS-CoV-2 positive patients, the risk of transmission to nursing staff with 8–10 h of face-to-face training in two cases was felt to be too significant for in-person training. We determined that the best option would be to stabilize parenteral nutrition in the hospital and perform virtual training. Although virtual training was successfully performed, it was felt that training in this manner took much longer, required frequent adjustment of the tablet device to ensure patient remained in field of view, and made it difficult to connect with the patient emotionally. Conclusions Telemedicine has significantly improved care provided during COVID-19 as a modality for effective training on HPN, while in-person communication was significantly limited due to the pandemic. However, when possible, it should be used in a manner that complements but does not supplant standard care.

Background: Artificial intelligence (AI) platforms can potentially enhance clinical decision-making (CDM) in primary care settings. OpenEvidence (OE), an AI tool, draws from trusted sources to generate evidence-based medicine (EBM) recommendations to address clinical questions. However, its effectiveness in real-world primary care cases remains unknown. Objective: To evaluate the performance of OE in providing EBM recommendations for five common chronic conditions in primary care: hypertension, hyperlipidemia, diabetes mellitus type 2, depression, and obesity. Methods: Five patient cases were retrospectively analyzed. Physicians posed specific clinical questions, and OE responses were evaluated on clarity, relevance, evidence support, impact on CDM, and overall satisfaction. Four independent physicians provided ratings using a 0 to 4 scale. Results: OE provided accurate, evidence-based recommendations in all cases, aligning with physician plans. OE was scored on a scale of zero to four, where zero was very unclear, and four was very clear. Mean scores across cases were clarity (3.55 ± 0.60), relevance (3.75 ± 0.44), support (3.35 ± 0.49), and satisfaction (3.60 ± 0.60). However, the impact on CDM was limited (1.95 ± 1.05), as OE primarily reinforced rather than modified plans. Conclusion: OE was rated high in clarity, relevance, and evidence-based support, reinforcing physician decisions in common chronic conditions. While the impact on CDM was minimal due to the study’s retrospective nature, OE shows promise in augmenting the primary care physician. Prospective trials are needed to evaluate its utility in complex cases and multidisciplinary settings.

Objective: Multicancer Detection (MCD) tests, such as the GRAIL Galleri, offer a novel approach to cancer screening by detecting cancer-specific methylation patterns in cell-free DNA through a single blood sample. This study evaluated an 18-month implementation of MCD testing in a tertiary ambulatory internal medicine clinic. Patients and Methods: Between June 2022 and November 2023, 2244 asymptomatic (without symptoms attributed to cancer) patients underwent MCD testing. The study focused on operational workflows, patient and physician education, and diagnostic follow-up of positive results. Standardized materials, including electronic health record (EHR) workflows, FAQs, and diagnostic pathways, were developed to facilitate implementation. Challenges included managing false positives, patient anxiety, costs, and ethical considerations. Results: Of the 2244 patients tested, 17 (0.76%) had positive results, and 15 underwent further diagnostic evaluation. Cancer was confirmed in 11 (73.3%) patients, including cases of breast, colon, esophageal, lymphoma, ovarian, and pancreatic cancers. Four patients had no identifiable malignancy despite comprehensive work-up. Conclusions: MCD testing is feasible in routine clinical workflows, with 73% of positive cases yielding cancer diagnoses. While promising, further research is required to assess long-term outcomes, cost-effectiveness, and optimal implementation strategies of cancer interception in broader healthcare settings.

Introduction: The Undiagnosed Mass Clinic (UMC) at our institution is a clinical and research program created to address gaps in the early diagnostic phase of the cancer care continuum for patients with potential malignant neoplasms. All patients referred to the UMC are invited to participate in the UMC registry, which tracks operational and clinical metrics while maintaining a repository of blood and tissue specimens for future research. Methods: We conducted a retrospective cohort study of the first 100 patients enrolled in the UMC registry. We analyzed patient demographics, final diagnoses, and the time from initial consultation to final diagnosis. Results: Most participants were White (86%), non-Hispanic (93%), and married (72%). The mean (SD) age was 64 (13.9) years. The final diagnoses of the masses were categorized as malignant/neoplastic with malignant potential (n = 53), benign (n = 36), or requiring diagnostic surveillance (n = 10). The mean (SD) time from initial consultation to final diagnosis of malignant/neoplastic with malignant potential masses significantly improved from 37.4 (36.6) days for the first 50 participants to 17.3 (19.7) days for the next 50 participants ( P = .006). Conclusions: These initial insights from the UMC registry will help direct future efforts to improve the care of patients with potential malignant neoplasms.

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.