Citations

Background: Varicose veins (VVs) of the lower limbs, characterized by palpable, dilated, and tortuous veins, affect 2–73% of the global population. Artificial intelligence (AI) offers significant potential to enhance healthcare efficiency and decision-making, particularly in managing VVs through improved risk factor identification, diagnosis, and treatment planning. Objective: This abstract explores the role of AI in VV management, focusing on its applications in risk detection, image analysis, treatment planning, and surgical interventions, while addressing challenges to its widespread adoption. Methods: AI leverages advanced techniques such as computer vision and deep learning to analyze patient data, including medical history, symptoms, physical examinations, and imaging (e.g., ultrasounds, venography). It identifies patterns in large datasets to support personalized treatment plans, early risk detection, and disease severity assessment. Results: AI demonstrates promise in automating VV detection and classification, assessing disease severity, and aiding treatment planning. It enhances surgical interventions through preoperative planning, intraoperative navigation, and recurrence risk prediction. However, its adoption is limited by a lack of large-scale studies, concerns over accuracy, and the need for regulatory and ethical oversight. Conclusion: AI has the potential to revolutionize VV management by improving diagnosis, treatment precision, and patient outcomes. Further research, validation, and integration are critical to overcoming current limitations and fully realizing AI’s capabilities in clinical practice.

OBJECTIVES: To develop the first core Critical Care Data Dictionary (C2D2) with common data elements (CDEs) to characterize critical illness and injuries. DESIGN: Group consensus process using modified Delphi approach. SETTING: Electronic surveys and in-person meetings. SUBJECTS: A multidisciplinary workgroup of clinicians and researchers with expertise in the care of the critically ill and injured. INTERVENTIONS: The Delphi process was divided into domain and CDE portions with each composed of two item generation rounds and one item reduction/refinement rounds. Two in-person meetings augmented this process to facilitate review and consideration of the domains and by panel members. The final set of domains and CDEs was then reviewed by the group to meet the competing criteria of utility and feasibility, resulting in the core dataset. MEASUREMENTS AND MAIN RESULTS: The 23-member Delphi panel was provided 1833 candidate variables for potential dataset inclusion. The final dataset includes 226 patient-level CDCs in nine domains, which include anthropometrics and demographics (8), chronic comorbid illnesses (18), advanced directives (1), ICU diagnoses (61), diagnostic tests (42), interventions (27), medications (38), objective assessments (26), and hospital course and outcomes (5). Upon final review, 91% of the panel endorsed the CDCs as meeting criteria for a minimum viable data dictionary. Data elements cross the lifespan of neonate through adult patients. CONCLUSIONS: The resulting C2D2 provides a foundation to facilitate rapid collection, analyses, and dissemination of information necessary for research, quality improvement, and clinical practice to optimize critical care outcomes. Further work is needed to validate the effectiveness of the dataset in a variety of critical care settings.

The NCCN Guidelines for Head and Neck Cancers address tumors arising in the oral cavity (including mucosal lip), pharynx, larynx, and paranasal sinuses, as well as occult primary cancer, salivary gland cancer, and mucosal melanoma (MM). The specific site of disease, stage, and pathologic findings guide treatment (eg, the appropriate surgical procedure, radiation targets, dose and fractionation of radiation, indications for systemic therapy). The NCCN Head and Neck Cancers Panel meets at least annually to review comments from reviewers within their institutions, examine relevant new data from publications and abstracts, and reevaluate and update their recommendations. These NCCN Guidelines Insights summarize the panel’s most recent recommendations regarding management of nasopharynx cancer and ongoing research in this area.

SummaryGlobal obesity rates have risen dramatically, now exceeding deaths from starvation. Metabolic and bariatric surgery (MBS), initially for severe obesity (BMI ≥35 kg/m2), is performed globally over 500 000 times annually, offering significant metabolic benefits beyond weight loss. However, varying eligibility criteria globally impact patient care and healthcare resources. Updated in 2022, ASMBS and IFSO guidelines aim to standardise MBS indications, reflecting current understanding and emphasising comprehensive preoperative assessments. Yet, clinical variability persists, necessitating consensus‐based recommendations. This modified Delphi study engaged 45 global experts to establish consensus on perioperative management in MBS. Experts selected from bariatric societies possessed expertise in MBS and participated in a two‐round Delphi protocol. Consensus was achieved on 90 of 169 statements (53.3%), encompassing multidisciplinary team composition, patient selection criteria, preoperative testing, and referral pathways. The agreement highlighted the critical role of comprehensive preoperative assessments and the integration of healthcare professionals in MBS. These findings offer essential insights to standardise perioperative practices and advocate for evidence‐based guidelines in MBS globally. The study underscores the need for unified protocols to optimise outcomes and guide future research in MBS.

In 2023, Mayo Clinic in Rochester, MN, cared for over 20,000 patients with hematologic malignancies, roughly 42% of whom were rural. Patients residing in rural areas can face challenges in access to care, financial and time burdens due to treatment-related travel, and limited opportunities to participate in clinical trials. In 2021, The Leukemia & Lymphoma Society launched its IMPACT (Influential Medicine Providing Access to Clinical Trials) grant with Mayo Clinic being among its first recipients. The program provides funding to major cancer centers, in partnership with local community oncology centers, to help increase participation of patients traditionally underrepresented in clinical trials, including those who are rural, minority and/or economically disadvantaged. The award allowed significant changes to be made to clinical trial selection and facilitation models increasing access to trials within the rural setting and reducing the socioeconomic barriers noted above. This program included Rochester (IMPACT Hub) and Mayo Clinic Health System (MCHS) sites in Albert Lea, MN (65 miles to Hub), Eau Claire, WI (96 miles to hub), La Crosse, WI (73 miles to Hub), and Mankato, MN (84 miles to Hub). Methods: Two models were deployed; the full activation model where clinical trials were fully opened at MCHS sites, and the hybrid model where clinical trial participants are consented at the Hub and portions of participant care are conducted at MCHS sites. Initial barriers included limitations in clinical trials support staff, insufficient specimen processing equipment, medication storage and shipping limitations, MCHS catchment population unalignment with the Hub trials portfolio, and reduced bandwidth of providers due to patient care responsibilities. To address barriers to trial conduct, community center site champions were identified to streamline trial review and increase collaboration to better define site catchment areas, trial constraints, and site needs. A feasibility specialist was hired to support the program in trial design/implementation, barrier tracking, and to serve as a liaison between community site providers, study staff, and the program. Results: Since 2021, 20 clinical studies including 14 interventional treatment trials have been activated demonstrating 108 total patients accrued with 42 interventional accruals; 5 within the full activation model (13 accruals) and 15 in the hybrid model (29 accruals). Patients showed an average of 216 miles, with an estimated mileage cost of $142/trip based on the 2023 IRS mileage rate of $0.655/mile to the hub location. Nine of those patients traveled over 260 miles, with an estimated mileage cost of $170/visit to access clinical trials. Under the hybrid model, 8 patients transitioned portions of their care to their home city resulting in reduction of an average of 155 miles/visit, and 7 patients were able to reduce their travel time an average of 216 miles/visit. By estimating at least 10 study visits, the travel burden was reduced by 2,160 miles (4320 driving hours) and $1,420 in driving costs alone for participants. Using participant averages the 108 patients would spend a total of $15,336 in travel costs for just the initial visit, but when factoring in the 10-visit estimate, travel reduction could result in a net savings of $153,360. Based on travel data, it is estimated 11 of these patients would have required overnight accommodation using an average of $149/night hotel stay, a savings of $1,490/patient is estimated for the lifecycle of trial participation or $16,390 for the 11-patient cohort requiring accommodation. These results do not include travel companion and time off work costs. Efforts have been made to further develop the full activation model and 5 clinical trials are in activation. Data gathered from the program is being used to design strategies to reduce the administrative burden of clinical trial participation for community providers and launch screening programs. Conclusion: The Mayo Clinic LLS IMPACT program has demonstrated success in addressing barriers to opening clinical trials in the community-center setting and reduced the travel burden and financial impact to clinical trial participation in a cohort of trial participants. Centralized hub support of study activation and conduct and decentralized care to support treatment of patients in proximity of their home can be extended to other hospital systems and settings.