Context.—: Hemophagocytic lymphohistiocytosis (HLH) is a rare, life-threatening disorder of immune regulation that can eventually result in end-organ damage and death. HLH is characterized by uncontrolled activation of cytotoxic T lymphocytes, natural killer cells, and macrophages that can lead to a cytokine storm. The diagnosis of HLH is often challenging due to the diverse clinical manifestations and the presence of several diagnostic mimics. The prognosis is generally poor, warranting rapid diagnosis and aggressive management. Objective.—: To provide a comprehensive review of the pathogenesis, clinical features, diagnosis, and management of HLH. Data Sources.—: Peer-reviewed literature. Conclusions.—: HLH is a condition where a complete understanding of the pathogenesis, early diagnosis, and proper management has an important role in determining patient outcome. Genetic mutations causing impairment in the function of cytotoxic T lymphocytes and natural killer cells have been identified as the root cause of familial HLH; however, the specific pathogenesis of acquired HLH is unclear. The HLH-2004 protocol used in the diagnosis of HLH was originally developed for the pediatric population. The HLH-2004 protocol still forms the basis of the diagnosis of HLH in adults, although its use in adults has not been formally validated yet. Treatment of HLH is primarily based on the HLH-94 protocol, which involves suppressing the inflammatory response, but the treatment needs to be modified in adults depending on the underlying cause and comorbidities.

Primary Sjögren’s syndrome (pSS) is a chronic autoimmune rheumatic disease with symptoms including dryness, fatigue, and pain. The previous work by our group has suggested that certain proinflammatory cytokines are inversely related to patient-reported levels of fatigue. To date, these findings have not been validated. This study aims to validate this observation. Blood levels of seven cytokines were measured in 120 patients with pSS from the United Kingdom Primary Sjögren’s Syndrome Registry and 30 age-matched healthy non-fatigued controls. Patient-reported scores for fatigue were classified according to severity and compared to cytokine levels using analysis of variance. The differences between cytokines in cases and controls were evaluated using Wilcoxon test. A logistic regression model was used to determine the most important identifiers of fatigue. Five cytokines, interferon-γ-induced protein-10 (IP-10), tumour necrosis factor-α (TNFα), interferon-α (IFNα), interferon-γ (IFN-γ), and lymphotoxin-α (LT-α) were significantly higher in patients with pSS (n = 120) compared to non-fatigued controls (n = 30). Levels of two proinflammatory cytokines, TNF-α (p = 0.021) and LT-α (p = 0.043), were inversely related to patient-reported levels of fatigue. Cytokine levels, disease-specific and clinical parameters as well as pain, anxiety, and depression were used as predictors in our validation model. The model correctly identifies fatigue levels with 85% accuracy. Consistent with the original study, pain, depression, and proinflammatory cytokines appear to be the most powerful predictors of fatigue in pSS. TNF-α and LT-α have an inverse relationship with fatigue severity in pSS challenging the notion that proinflammatory cytokines directly mediate fatigue in chronic immunological conditions.

The integration of artificial intelligence in pathology has ignited discussions about the role of technology in diagnostics-whether artificial intelligence serves as a tool for augmentation or risks replacing human expertise. This manuscript explores artificial intelligence's evolving contributions to pathology, emphasizing its potential capacity to enhance, rather than eclipse, the pathologist's role. Through historical comparisons, such as the transition from analog to digital in radiology, this paper highlights how technological advancements have historically expanded professional capabilities without diminishing the essential human element. Current applications of artificial intelligence in pathology-from diagnostic standardization to workflow efficiency-demonstrate its potential to augment diagnostic accuracy, expedite processes, and improve consistency across institutions. However, challenges remain in algorithmic bias, regulatory oversight, and maintaining interpretive skills among pathologists. The discussion underscores the importance of comprehensive governance frameworks, evolving educational curricula, and public engagement initiatives to ensure artificial intelligence in pathology remains a collaborative endeavor that empowers professionals, upholds ethical standards, and enhances patient outcomes. This manuscript ultimately advocates for a balanced approach where artificial intelligence and human expertise work in concert to advance the future of diagnostic medicine.

The COVID-19 pandemic put most in-person pathology electives on-hold as departments adapted to changes in education and patient care. To address the subsequent void in pathology education, we created a free, virtual, modular, and high-quality pathology elective website. Website traffic from June 1, 2020, to October 1, 2020, was monitored using the built-in analyses on Squarespace. Twitter engagement was analyzed using Twitter analytics and the Symplur Social Graph Score. A voluntary satisfaction survey was sent to all PathElective users and results were analyzed. During this time, the site saw 25 467 unique visitors, over 34 988 visits, 181 302 page views, and 4449 subscriptions from 99 countries. Countries with the highest traffic are the United States (14 682), India (5210), and the Philippines (2195). PathElective’s Twitter social graph score increased from 63.59 to 89.3 with the addition of 1637 followers. Data from surveyed users (n = 177) show most to be pathology residents (41%). Most subscribers (89%) are committed to a career in pathology. The majority heard of the website via Twitter (55%). Almost half of those surveyed engaged with the PathTwitter community on Twitter and of those who participated, 99% found that interaction useful. In all survey questions surrounding satisfaction and usefulness, a large majority of the users were either satisfied or very satisfied. PathElective is a novel pathology elective that offers a unique opportunity to educate medical students and residents from around the globe and demonstrates high effectiveness and satisfaction among users.

Context: PathElective.com was created in response to the pandemic's restrictions on interactions with trainees, and since has been incorporated into many training programs worldwide, serving as a unique means of delivering high-quality pathology and laboratory medical education at multiple levels of training. Objective: To analyze student usage, performance, and satisfaction to provide insight into the effectiveness of virtual education to guide curricular evolution. Design: Squarespace (Squarespace, Inc) was used for website development and to collect website analytics. Students were assessed before and after course participation using a dual-form crossover quiz design. Quiz data were anonymous and analyzed with a paired t test to account for varying student backgrounds. A novel analysis was performed aimed at examining the attrition rate of students across multiple modules. Results: During the study period (May 1, 2020 to October 31, 2021), PathElective.com received 577 483 page views, 126 180 visits, 59 928 unique visitors, and 10 278 registered users who earned 15 305 certificates. A total of 7338 premodule and postmodule quiz pairs were analyzed. The overall average increase in score was 13.83% (P = .02). All but 5 of the 56 courses experienced a statistically significant increase in score. All courses received median scores of Very Satisfied/Satisfied in all 6 assessment domains. Aggregate attrition data revealed a unique, negative polynomial relationship (R2 = 0.656). Conclusions: PathElective.com is a free, effective means of enhancing anatomic/clinical pathology training in medical education. These analyses offer a unique perspective on the online user experience and could guide the development of future online medical education resources.