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Importance Tumor-infiltrating lymphocytes (TILs) are a provocative biomarker in melanoma, influencing diagnosis, prognosis, and immunotherapy outcomes; however, traditional pathologist-read TIL assessment on hematoxylin and eosin–stained slides is prone to interobserver variability, leading to inconsistent clinical decisions. Therefore, development of newer TIL scoring approaches that produce more reliable and consistent readouts is important. Objective To evaluate the analytical and clinical validity of a machine learning algorithm for TIL quantification in melanoma compared with traditional pathologist-read methods. Design, Setting, and Participants This multioperator, global, multi-institutional prognostic study compared TIL scoring reproducibility between traditional pathologist-read methods and an artificial intelligence (AI)-driven approach. The study was conducted using retrospective cohorts of patients with melanoma between January 2022 and June 2023 across 45 institutions, with tissue evaluated by participants from academic, clinical, and research institutions. Participants were selected to ensure diverse expertise and professional backgrounds. Main Outcomes and Measures Intraclass correlation coefficient (ICC) values were calculated for the manual and AI-assisted arms using log-transformed data. Kendall W values were calculated for Clark scores (brisk = 3, nonbrisk = 2, and sparse = 1). Reliabilities of ICC and W values were classified as moderate (0.40-0.60), good (0.61-0.80), or excellent (>0.80). AI TIL measurements were dichotomized using the 16.6 and median cutoffs. Univariable and multivariable Cox regression analyses assessed the prognostic value of TIL scores adjusted for clinicopathologic variables. Results There were 111 patients with melanoma in the independent testing cohort (median [range] age at diagnosis, 61.0 [25.0-87.0] years; 56 [50.5%] male) who contributed melanoma whole tissue sections. A total of 98 participants evaluated TILs on 60 hematoxylin and eosin–stained melanoma tissue sections. All 40 participants in the manual arm were pathologists, while the AI-assisted arm included 11 pathologists and 47 nonpathologists (scientists). The AI algorithm demonstrated superior reproducibility, with ICCs higher than 0.90 for all machine learning TIL variables, significantly outperforming manual assessments (ICC, 0.61 for AI-derived stromal TILs vs Kendall W , 0.44 for manual Clark TIL scoring). AI-based TIL scores showed prognostic associations with patient outcomes (n = 111) using the median cutoff approach with a hazard ratio (HR) of 0.45 (95% CI, 0.26-0.80; P = .005), and using the cutoff of 16.6, with an HR of 0.56 (95% CI, 0.32-0.98; P = .04). Conclusions and Relevance In this prognostic study of TIL quantification in melanoma, the AI algorithm demonstrated superior reproducibility and prognostic associations compared with traditional methods. Although the retrospective nature of the cohorts limits demonstration of clinical utility, the publicly available dataset and open-source AI tool offer a foundation for future validation and integration into melanoma management.

Study Design: A national prospective cervical spine surgery registry was developed to archive radiographic studies, patient-reported outcome measures (PROMs), and surgical implant data to assess long-term safety. Objective: To describe the design, development, funding, and implementation of a cervical spine data registry for 1000 patients with myelopathy and radiculopathy. Summary of Background Data: While surgery for cervical radiculopathy and myelopathy is safe and effective, there is significant practice variation among spine surgeons. While randomized clinical trials (RCTs) can provide high-quality comparative effectiveness data, RCTs lack the ability to evaluate the safety and effectiveness of various surgical procedures and implants among heterogenous real-world patient populations. The CSRS Registry was designed to collect patient demographics, outcomes, radiographic imaging, surgical approach, and implant data for the purpose of conducting high-quality research. Methods: Patients with cervical myelopathy or radiculopathy were enrolled in the CSRS National Registry. De-identified patient data, validated PROMs, radiographic data, and implant data were collected from multiple clinical sites across the United States. Results: One thousand patients [mean age, 58 y; 456 (46%) women] were enrolled, with 31% follow-up at 1 year. Five hundred ninety-two patients were diagnosed with radiculopathy, 252 with myelopathy, and 156 with radiculopathy and myelopathy. Patients had significant improvements in their PROMs after surgery. At 1 year, the mean NDI score improved from 37.2 to 20.9 ( P <0.001). The mean self-reported P-mJOA score at baseline was 14.2 and improved to 15.2 by 1 year ( P <0.001). Baseline CSDI score was 23.6 and improved with a 1-year decrease to an average score of 13.6 ( P <0.001). There was significant improvement in PROMIS-10 Physical Health score from 41.0 to 45.9 (n=311; P <0.001) at 1-year follow-up. Conclusions: The CSRS Registry has successfully collected clinical outcomes data that is being leveraged for comparative effectiveness research and evaluations of the long-term safety and effectiveness of spinal implants.

Abstract Objective There is a need to develop a comprehensive, formalized, and globally applicable epilepsy surgery curriculum in order to help standardize the quality of epilepsy surgery practice in the world. Methods The Epilepsy Surgery Educational Task Force of the ILAE developed a competency‐based epilepsy surgery educational curriculum comprised of four domains: Diagnosis, Counseling, Pre‐surgical Work‐up, and Surgical Techniques. To evaluate this educational curriculum, a survey questionnaire consisting of 11 items was sent out for feedback to ILAE and IESS members. The survey questionnaire asked respondents to rate the degree of importance of each competency on a five‐point scale that ranged from “extremely important” to “not at all important” and provided space for free text comments. All competencies that were rated as “slightly important” or “somewhat important” by more than 10% of responders, as well as all free text feedback comments, were fully reviewed, and the final curriculum was adjusted accordingly. Results One hundred and twenty‐two responses ( n = 122) were submitted by the ILAE and IESS communities. Seventy‐one percent (71.9%) of the responses came from neurosurgeons of varied experience and training levels. Ninety‐four percent (94.4%) of responders stated that they “support a curriculum to determine the competency of neurosurgeons participating in the care of people with epilepsy in my country,” and 94.3% confirmed that they “would be interested in taking or would recommend an ILAE course based on these competencies, that would provide an ILAE certificate of completion.” Relevant changes within the curriculum were made based on feedback. Significance The newly developed ILAE comprehensive epilepsy surgery educational curriculum has a high level of support from neurosurgeons and neurologists around the world and shows potential for broad acceptance and implementation.

AbstractBackgroundGastric cancer with synchronous peritoneal metastases is a debilitating disease with limited treatment options. This article describes an update of the 2018 Chicago Consensus guidelines addressing the management of gastric cancer with synchronous peritoneal metastases in line with the most recent evidence.MethodsA clinical management pathway was updated through two rounds of a Delphi consensus to assess agreement levels with pathway blocks. Supporting evidence underwent evaluation using a rapid literature review. Meta‐analyses were performed as appropriate.ResultsOverall, the level of evidence in this disease subset was low to moderate. Of 124 participants in the first round, 109 (88%) responded in the second round. Strong consensus (>90%) was achieved in six of eight blocks (75%) in rounds 1 and 2. A multidisciplinary preoperative assessment and diagnostic laparoscopy should be offered to all patients, whereas patients with a high burden of disease or progression should undergo nonsurgical management. Patients with stable/responsive disease and a low peritoneal carcinomatosis index should subsequently be offered treatment with regional therapeutic interventions and cytoreductive surgery. In patients who are cytology‐positive, systemic therapy can be used to convert them to cytology‐negative, with subsequent surgery offered according to the patient's goals of care. Meta‐analysis of observational and randomized control trials revealed a survival benefit with the addition of intraperitoneal chemotherapy to cytoreductive surgery (hazard ratio, 0.52).ConclusionsThe consensus‐driven clinical pathway for gastric cancer with synchronous peritoneal metastases offers vital clinical guidance for practitioners. There is a growing body of high‐quality evidence to support management strategies, and future clinical trials are eagerly awaited.

Abstract Aims Syncope remains a diagnostic challenge despite advancements in testing and treatment. Cardiac syncope is an independent predictor of mortality and can be difficult to distinguish from other causes of transient loss of consciousness (TLOC). This paper explores whether artificial intelligence (AI) can improve the evaluation and management of patients with syncope. Methods and results We conducted a literature review and incorporated the opinions of experts in the fields of syncope and AI. The cause of TLOC is often unclear, hospitalization criteria are ambiguous, diagnostic tests are frequently non-informative, and assessments are costly. Patients are left with unanswered questions and limited guidance. Artificial intelligence (AI) has the potential to optimize syncope evaluation by processing large data sets, detecting imperceptible patterns, and assisting clinicians. However, AI has limitations, including errors, lack of human empathy, and uncertain clinical utility. Liability issues further complicate its integration. We present three viewpoints: (i) AI is crucial for advancing syncope management; (ii) AI can enhance the patient experience; and (iii) AI in syncope care is inevitable. Conclusion Artificial intelligence may improve syncope diagnosis and management, particularly through machine learning–based test interpretation and wearable device data. However, it has yet to surpass human clinical judgment in complex decision-making. Current challenges include gaps in understanding syncope mechanisms, AI interpretability, generalizability, and clinical integration. Standardized diagnostic approaches, real-world validation, and curated data sets are essential for progress. Artificial intelligence may enhance efficiency and communication but raises concerns regarding confidentiality, bias, inequities, and legal implications.

AbstractPurposeThe Collaborative care model (CoCM) is the leading model for integrating behavioral health into primary care for patients with major depressive disorder (MDD). However, CoCM requires engagement and ongoing participation. We aimed to assess whether two area‐based measures, the area‐deprivation index (ADI) and rurality, were associated with enrollment, participation, and outcomes with CoCM.MethodsThis was an observational analysis of Mayo Clinic patients eligible for CoCM: adults aged ≥18 years, empaneled in primary care, and with a PHQ‐9 of ≥10. We operationalized ADI as quintiles with Q1 being least deprived and Q5 being most deprived and rurality using RUCA codes with two categories: urban and rural. We evaluated enrollment in CoCM, drop out defined by leaving the program early, the count and type of contacts with the care coordinator, and clinical improvement measured using the PHQ‐9.FindingsWe identified 54,030 individuals with 16,532 (30.6%) residing in rural areas and 11,122 (20.6%) residing in the most deprived ADI quintile (Q5). Living in a rural area was associated with lower enrollment in CoCM (–2.3 percentage points [95% confidence interval (CI): –2.5, 2.2]), longer length in CoCM (18.6 days [95% CI: 5.7, 31.5]), more contacts with the care coordinator (1.1 contacts [95% CI: 0.2, 2.0]), and worse response and remission. In contrast, ADI Q5 was only associated with worse response and remission.ConclusionsRurality was associated with lower enrollment, greater engagement, and worse clinical outcomes. More work may be needed to address enrollment barriers for individuals living in rural areas to improve clinical outcomes.

ABSTRACT The characteristics at diagnosis and clinical course of primary extranodal follicular lymphoma (EFL) have not been extensively described. The International Extranodal Lymphoma Study Group (IELSG) conducted an international retrospective survey aimed to describe the clinical features at diagnosis and the outcomes of FL cases with a clinically dominant extranodal component. The dataset included 605 pathologically reviewed cases from 19 different countries, and their outcomes were compared to those of nodal follicular lymphomas. The two most common presentation sites for EFL were the skin ( n = 334) and the gastrointestinal tract ( n = 72), with 22 cases having primary duodenal localization. These subsets exhibited unique features at diagnosis and significantly different overall survival (OS) patterns. After a median follow‐up of 5.5 years, primary cutaneous lymphomas showed a superior outcome [10‐year OS: 89% (95% CI, 83%–93%)], while primary gastrointestinal lymphomas had an intermediate outcome [10‐year OS: 79% (95% CI, 59%–90%)]. Among the gastrointestinal lymphomas, primary duodenal lymphomas tended toward the best outcome [10‐year OS: 95% (95% CI, 69%–99%)]. Other primary extranodal sites had inferior outcomes [10‐year OS: 59% (95% CI, 48%–68%)], similar to primary nodal lymphomas [10‐year OS: 57% (95% CI, 49%–64%)]. These findings support the identification of specific primary FL localizations as distinct entities with particular clinical and biological characteristics.

ABSTRACT Background Transvenous lead removal (TLR) is a Class I indication for patients with cardiac implantable electronic device (CIED) infections. However, disparities in the utilization of TLR have not been fully explored, particularly concerning demographic and socioeconomic factors. Objectives This study aims to examine whether disparities exist among patients hospitalized for CIED infections with respect to the utilization of TLR, focusing on sex, race, and income characteristics. Methods We utilized the 2019 National Inpatient Sample (NIS) to assess patients hospitalized with CIED infections and identify those who underwent TLR. Multiple logistic regression was used to examine risk factors for TLR utilization, including age, sex, race/ethnicity, and socioeconomic characteristics. Results A total of 56 709 patients were hospitalized for CIED infection in the United States in 2019, of which 9867 (17.4%) underwent TLR. On an adjusted analysis, females and Black patients were found to have lower odds of undergoing TLR compared to males and White patients (OR: 0.62; 95% CI: 0.59–0.78; p < 0.01; and OR: 0.47; 95% CI: 0.39–0.57; p < 0.01, respectively). Hispanic patients also had reduced odds of TLR (OR: 0.73; 95% CI: 0.58–0.93; p = 0.01). No significant associations were observed between income or insurance status and the likelihood of receiving TLR after adjustment. Conclusions This study identified significant disparities in the utilization of TLR among patients hospitalized for CIED infections. Female, Black, and Hispanic patients were significantly less likely to receive TLR.

ABSTRACTObjectiveTo build consensus from different stakeholders on the content and digital interactivity of a shared decision making (SDM) tool to guide patient‐clinician collaborative conversations about treatment for bipolar depression.Patients and MethodsThis study was conducted between September 2022 and September 2023. In the first phase, we conducted a narrative review on pharmacological, neuromodulatory, and psychotherapeutic treatments available for bipolar depression. For each option, we assessed treatment effectiveness, side effects, need for clinical monitoring, clinical considerations, and cost. In the second phase, committees comprised of mental health clinicians and people with lived experience with bipolar disorder from a national mood disorders advocacy group identified key features and content to be included in the SDM tool. A thematic analysis of these data then contributed to populate the SDM tool.ResultsTwenty‐one evidence‐based treatment options identified from the narrative review were presented to the four convened committees (clinical, lived experience, peer council, and integrated steering committees) in five meetings. After discussions and thematic analysis, 12 outcomes of interest for each of the therapeutic interventions were delineated for inclusion in a web‐based SDM tool. A detailed description of the development process and SDM tool is provided.ConclusionThis is the first partnership between clinicians and persons with bipolar disorder lived experience charged with the development of a patient‐centered SDM tool to integrate clinical evidence with real‐world clinical practice and patient preferences for use during clinical encounters. Human‐centered design and testing in real clinical encounters will now contribute to refining the instrument and readying it for rigorous evaluation and implementation in practice.