Faculty Bibliography

OBJECTIVES/OBJECTIVE:The gut microbiome plays a crucial role in regulating systemic immunity and has been implicated in several chronic inflammatory diseases. Intestinal expansions of Ruminococcus gnavus (RG), a dominant gut commensal, correlate with disease flares in lupus nephritis (LN), but the underlying mechanism remains unknown. METHODS:In a Pilot cohort of patients with biopsy-proven LN, subsetted by gut microbiota community, immune status was characterised using bulk-blood RNA sequencing libraries, serum levels of representative host proteins, and levels of immunoglobulin (Ig)G antibodies to the novel lipoglycan (LG) produced by pathogenic RG strains. A Validation LN cohort was evaluated for blood transcriptomic profiles and levels of anti-LG antibodies. In murine models, mechanistic hypotheses were tested after RG gut colonisation or after intraperitoneal injection with an LG preparation, with outcomes determined by transcriptomic analyses, platelet functional readouts, and tissue histology. RESULTS:In a Pilot cohort of patients with LN, RG gut expansions were associated with high-level platelet, neutrophil, and monocyte activation. Serum levels of platelet factor 4 and release of neutrophil extracellular traps (NETs) were significantly higher in patients with high serum IgG antibody against the novel RG-specific LG, a marker of in vivo immune exposure. An LN Validation cohort confirmed these correlates and showed that anti-LG antibodies serve as a surrogate for thromboinflammatory profile in this LN-associated endotype. In mice, gut colonisation with LG-producing RG strains or a single LG injection caused megakaryocytosis and platelet activation; RG colonisation with LG-producing strains induced tubulointerstitial injury with NETosis. In vivo responses to LG toxin were Toll-like receptor 2-dependent. CONCLUSIONS:Gut expansions of the RG pathobiont may contribute to autoimmune pathogenesis through the LG toxin and cause LN flares through thromboinflammatory mechanisms in this previously unrecognised LN endotype.

INTRODUCTION/UNASSIGNED:Variceal hemorrhage is a severe and often fatal consequence of portal hypertension from liver cirrhosis. Although endoscopic and radiographic interventions have largely replaced balloon tamponade, the Sengstaken-Blakemore tube (SBT) remains a critical salvage therapy. However, declining use has led to limited provider experience and familiarity with SBT placement and management. METHODS/UNASSIGNED:We implemented a hands-on, manikin-based simulation program for fellows and attendings from gastroenterology and critical care to improve provider familiarity with SBT placement and management. Standardized SBT kits were developed and distributed across all sites. Annual simulation sessions included presession didactics, live demonstrations, and small-group hands-on practice. Pre- and postsession surveys assessed self-reported confidence in SBT placement, management, and removal using a 5-point Likert scale. A Wilcoxon signed-rank test analyzed changes in confidence. RESULTS/UNASSIGNED:Fifty-four participants participated in 2023. Prior to training, only 20% of participants reported having received any formal instruction on SBT placement or management and 39% had never placed an SBT in a real-life scenario. Confidence in SBT placement (mean 3.00-4.30), management (1.78-4.31), and removal (2.17-4.43) significantly increased after the simulation. DISCUSSION/UNASSIGNED:This simulation-based intervention was associated with improved self-reported confidence in SBT placement, management, and removal for a high-acuity, low-frequency procedure. Given interest, emergency medicine, surgery, and internal medicine were included in subsequent years. Our results underscore the importance of structured training in bridging knowledge and skill gaps across gastroenterology and critical care disciplines. Future work should assess long-term retention and explore curriculum integration.

Although previously B cells had been underestimated in comparison to T cells in their role in autoimmunity, now, their impact is well established. Via secretion of autoantibodies, presentation of autoantigens, regulation of antigen processing and presentation, and release of inflammatory cytokines, B cells can mediate cytotoxicity and lead to organ damage. B cell depletion via CD20 targeting effectively eliminates B cells in the blood and primary lymph organs and has found an effective role in the treatment of both rheumatological and neurological diseases. The neonatal Fc receptor (FcRn) is a key component of immune regulation that prevents IgG (produced by B cells) from degradation by lysosomes, sending it back into the extracellular compartment, thereby extending its half-life. This abundance of pathogenic IgG can lead to the development of autoimmune disease. The interplay between these two mechanisms of autoimmunity provides the great potential for combination therapy to reduce existent pathogenic IgG as well as prevent the production of new autoantibodies, though further investigation is needed to determine the risks, particularly of infection. This paper will explore existing B cell depleting treatments and FcRn inhibitors, and consider the potential impact for autoimmune disease as well as for the treatment of atherosclerosis.

Salvage chemotherapy and autologous stem cell transplantation (ASCT) offer the opportunity to cure eligible patients with relapsed diffuse large B-cell lymphoma (DLBCL). Epigenetic alterations such as aberrant DNA methylation patterns have been linked to chemotherapy resistance in DLBCL. Oral Azacitadine (AZA) is a hypomethylating agent that inhibits DNA methyltransferase and has provided evidence of chemotherapy sensitization in DLBCL. In this phase I trial the safety and feasibility of two dose levels of AZA were investigated in combination with standard cytotoxic chemotherapy rituximab, ifosfamide, carboplatin, and etoposide (R-ICE) in relapsed DLBCL patients who were candidates for ASCT.

IMPORTANCE/OBJECTIVE:Since the cardiac intensive care unit (CICU) was first introduced into to the medical landscape, patient complexity, comorbidity, and illness severity have increased substantially over time. This evolution has required and informed the cultivation of new tools and an expanding skill set for those who deliver care in these units, and has paved the way for the emergence and growth of a distinct discipline-Critical Care Cardiology. With the genesis of this field and the need to care for comorbid and critically ill patients, numerous questions have been posed, including those related to optimal staffing models, appropriate training pathways, and the development of best practice principles to guide patient management. To address these and other challenges, to foster necessary collaborations, and to galvanize a maturing field, the Society of Critical Care Cardiology (SoCCC) was born. OBSERVATIONS/METHODS:SoCCC was created to provide an independent, yet complementary home for stakeholders within this rapidly growing discipline. Its mission is to address the unique needs and concerns of Critical Care Cardiology through an inclusive approach that prioritizes the development of early career faculty, actively engaging them to help to shape the field and to strengthen its unique practice environment - the CICU. While collaborations with larger professional societies remain essential, an independent subspecialty society like SoCCC intends to capitalize on the historical precedent and experiences shared by other successful organizations, while leveraging its nimble structure to advocate for and advance the needs of its constituency. CONCLUSIONS/RELEVANCE/CONCLUSIONS:While this document primarily details the history and rationale that led to the establishment of SoCCC, it also endeavors to be a practical blueprint to support future leaders who might be considering a new society for their own subspecialty.

Accurate mortality prediction in older adults is a critical component of precision public health and risk stratification in healthcare systems worldwide. In middle-income countries, however, real-world applications remain scarce due to limitations in data quality and methodological scalability. This study aims to develop and benchmark state-of-the-art predictive models for all-cause mortality among adults aged 80 years and older in Colombia's five major cities, leveraging a uniquely rich and comprehensive administrative health dataset. We constructed two predictive cohorts from high-dimensional, real-world data covering over 300,000 and 50,000 individuals for one- and two-year models, respectively. The dataset includes detailed records on thousands of prescribed medications, medical procedures, ICD-10 diagnoses, service provider and insurer identifiers, care modalities (outpatient, inpatient, emergency, home-based), and financial payment mechanisms, reflecting routine clinical practice across hundreds of healthcare providers and insurers. We implemented and compared five advanced modeling strategies: artificial neural networks, autoencoders, extreme gradient boosting (XGBoost), Bayesian regression, and TabTransformer (a self-attention architecture tailored for structured data). Model performance was assessed using area under the curve (AUC), F1-score, accuracy, and Brier score. Our research demonstrates that diagnostic codes, pharmacological profiles, and hospitalization patterns are the most predictive domains of late-life mortality, whereas operational variables (e.g., provider or insurer) add little incremental value. The highest discriminative performance was achieved with XGBoost (AUC = 0.92 for two-year, 0.89 for one-year predictions), followed by autoencoders (AUC = 0.85 and 0.87) and TabTransformer (AUC = 0.82 and 0.84). Neural networks showed moderate performance, and Bayesian regression faced convergence issues due to computational demands. Notably, some models achieved AUC values above 0.88, indicating strong discriminatory performance for mortality classification in older adults using real-world data, although F1 scores reflected moderate classification balance. This study demonstrates the feasibility and potential of deploying advanced machine learning techniques on richly granular administrative health data in a middle-income country. Our findings offer a robust methodological foundation for the early identification of high-risk older adults and provide actionable insights for health insurers, care providers, and policymakers within Colombia's General System of Social Security in Health. The integration of such models could inform targeted preventive strategies and resource allocation to improve outcomes in aging populations.

Patients with classic Hodgkin lymphoma (cHL) with primary refractory disease, early relapse, or extranodal disease have a higher risk of relapse after salvage therapy and autologous stem cell transplant (ASCT). Post-ASCT brentuximab vedotin (BV) maintenance improved progression-free survival (PFS) in high-risk relapsed/refractory (R/R) cHL in the AETHERA trial, but subgroup analysis suggested that the benefit in patients transplanted in complete metabolic response (CMR) is unclear. In a large international real-world cohort, we assessed the efficacy of BV maintenance stratified by pre-ASCT metabolic response and by the number of clinical risk factors as defined in the AETHERA trial. Adult patients with R/R cHL who met AETHERA risk criteria were included. Utilizing propensity score analyses, PFS and OS were assessed overall and in subgroups of CMR (442 pts) and partial metabolic response (PMR, 249 pts). We observed that post-ASCT BV maintenance was associated with significantly higher PFS in the subgroup with PMR (5-year PFS: 59.6% vs 43.3% HR = 0.52, CI₉₅: 0.33-0.82; p = 0.007). In the subgroup of patients with CMR, BV maintenance did not significantly improve PFS (5-year PFS: 75.8% vs 62.3% HR = 0.88, CI₉₅: 0.59-1.32; p = 0.29). However, when focusing on patients with CMR treated post-FDA approval of BV, there was a significant PFS benefit observed in those treated with BV maintenance vs. not (5-year PFS: 81.2% vs 55.2% HR = 0.40, CI₉₅: 0.22-0.72; p = 0.003). Overall, BV maintenance after ASCT remains an important therapy for high-risk R/R cHL patients, especially for those in PMR or those in CMR.

OBJECTIVE:Using AI algorithms can exacerbate health disparities if care or resources are allocated away from underserved populations. We evaluated an algorithm for its potential to worsen health disparities across different clinical use cases. MATERIALS AND METHODS/METHODS:This was a retrospective study of patients with heart failure (HF) at an academic health system using an algorithm that predicts pharmacy fill nonadherence to evidence-based HF medications. We compared prediction performance metrics (accuracy, false positive rate, false negative rate), using rate-ratios (RRs), between subgroups with and without known HF care disparities: below vs above median neighborhood-level socioeconomic status (nSES) and Black vs White race. Results were then applied to 3 hypothetical clinical use cases. RESULTS:Among 34 697 patients (13% Black, 10% Hispanic, 65% White), algorithm accuracy was similar across nSES and racial subgroups. The algorithm assigned more false positives for medication nonadherence among low vs high nSES (RR [95%CI] 1.50 [1.44-1.56]) and Black vs White (2.05 [1.92-2.19]) subgroups. The algorithm also assigned fewer false negatives (0.63 [0.59-0.67]) to Black vs White subgroups. When applied to 3 hypothetical use cases, worsening of existing disparities was pertinent for clinical applications where false positives could be particularly harmful (e.g, if predictions of nonadherence prompted lower treatment priority). DISCUSSION/CONCLUSIONS:Although accuracy was similar across demographic groups, differences in false positive and false negative rates revealed that the same prediction may worsen disparities in some use cases, but not others. CONCLUSION/CONCLUSIONS:Evaluation of predictions in the context of clinical use is essential to avoid unintentionally worsening inequities.

BACKGROUND:In many health disparities studies, persons aged 75 and older are underrepresented. Burden of cardiovascular disease (CVD) mortality and morbidity remains high in this age group, with a higher risk to Black individuals. Interestingly, at age 85 and older, CVD mortality is higher in White than Black patients. OBJECTIVE:Compared serum lipid patterns in non-Hispanic Black (NHB) and White (NHW) individuals in a national survey of persons aged 75+. METHODS:Data on demographics and serum lipids of NHB and NHW aged 75 and older were examined in the 2007 to March 2020 National Health and Nutrition Examination Survey for 2350 NHW and 496 NHB individuals. Serum triglycerides were measured, and low-density lipoprotein (LDL) was calculated for those examined in the morning (1124 NHW, 223 NHB). Statistical analysis accounted for the complex survey design and sampling weights. RESULTS:Median high-density lipoprotein (HDL) cholesterol levels were higher in Black individuals compared to White individuals and also higher in women than in men. Race remained significantly associated with HDL after multivariable adjustment (P < .01). Median LDL-cholesterol was similar between Black and White individuals and higher in women. Race was not significantly associated with LDL after adjustment. The LDL/HDL ratio was similar in Black and White individuals among women, lower in Black individuals among men, and higher in men than in women. Race was not associated with LDL/HDL in women, but LDL/HDL was higher in NHW than NHB men after adjustment (P = .005). CONCLUSION/CONCLUSIONS:This analysis demonstrates that HDL differences persist in older adults, whereas LDL patterns are consistent across races, underscoring the need for age-specific prevention strategies.