Citations

Objective To provide evidence‐based and expert guidance for the treatment and management of non‐renal systemic lupus erythematosus (SLE); treatment and management of lupus nephritis are addressed in a separate guideline. Methods Clinical questions for treatment and management of SLE were developed in the PICO format (population, intervention, comparator, and outcome). Systematic literature reviews were developed for each PICO question, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology was used to assess evidence quality and formulate recommendations. The Voting Panel achieved a consensus of ≥70% agreement on the direction (for or against) and strength (strong or conditional) of each recommendation. Results We present recommendations and ungraded, consensus‐based good practice statements for the treatment and management of SLE that are applicable to pediatric and adult patients. Recommendations emphasize uniform treatment with hydroxychloroquine, limiting duration of glucocorticoid use, and early introduction of conventional and/or biologic immunosuppressive therapies to achieve and maintain control of SLE inflammation (remission or a low level of disease activity), reduce SLE‐related morbidity and mortality, and minimize medication‐related toxicities. Conclusion This guideline presents direction regarding treatment and management of SLE and provides a foundation for well‐informed, shared clinician–patient decision‐making. These recommendations should not be used to limit or deny access to therapies, as treatment decisions may vary due to the unique clinical situation and personal preferences of each person with SLE.

Background and Aims: With rapid changes in the management landscape of chronic hepatitis B (CHB), this technical systematic review addresses 4 critical Population, Intervention, Comparator, Outcome (PICO) questions to provide guidance to the formulation of recommendations to the 2025 AASLD practice guideline for management of CHB. Approach: The review was reported in accordance with PRISMA guidelines. Outcomes were evaluated across 4 key PICOs: (1) antiviral therapy for prevention of horizontal HBV transmission in high-risk groups, (2) antiviral therapy versus observation for persons in the immune-tolerant phase, (3) discontinuation versus continuation of nucleos(t)ide analogue therapy in HBeAg-negative individuals with undetectable HBV DNA, and (4) hepatocellular carcinoma (HCC) surveillance in non-cirrhotic individuals with HBsAg clearance or co-infections with HCV, HDV, or HIV. Results: For PICO 1, limited evidence suggests antiviral therapy may reduce horizontal transmission risk, though with low certainty. PICO 2 analyses reveal uncertain benefits of treating persons in the immune-tolerant phase, with very low certainty due to heterogeneity and bias. PICO 3 analyses demonstrate that discontinuing antiviral therapy in persons who are HBeAg negative with undetectable HBV DNA increases HBsAg loss rates (OR: 12.65, 95% CI: 1.58–101.51) but carries moderate risks of virologic relapse (OR: 47.17, 95% CI: 2.79–797.35) and clinical flares. PICO 4 analyses on several cohort studies showed that in patients co-infected with HCV, HBV, or HIV, the annual incidence of HCC was higher than the level where screening becomes cost-effective, suggesting that regular liver cancer screening could be beneficial for these patients. Conclusions: Despite low certainty, the findings support shared decision-making in high-risk horizontal transmission scenarios or in treating individuals in the immune tolerance phase, caution in discontinuing antiviral therapy in virologically suppressed individuals without HBsAg loss, and tailored HCC surveillance for those with co-infection or cirrhosis.

Background and Aims: Accumulating data related to prevention, surveillance and treatment of chronic hepatitis B (CHB) provided the impetus for this updated guideline, using the Grading of Recommendation Assessment, Development and Evaluation (GRADE) approach. Methods: The guideline was developed in compliance with the National Academy of Medicine standards. The guideline panel developed structured questions following the Population, Intervention Comparison, Outcomes (PICO) framework. The panel addressed 6 PICO questions covering prevention (maternal to infant transmission and horizontal transmission), surveillance for liver cancer (among hepatitis B surface antigen positive (HBsAg) persons co-infected with hepatitis C virus, hepatitis D virus and/or human immunodeficiency viruses and after HBsAg loss) and treatment (HBsAg positive persons in immune-tolerant or indeterminate phases as well as withdrawal of antiviral therapy), providing evidence-based recommendations on these topics. Four systematic reviews of the literature were conducted, and two existing systematic reviews were utilized to support the recommendations in this practice guideline. Conclusions: This evidence-based guideline provides updated recommendations to optimize the care of persons with CHB.

Objective To provide evidence‐based and expert guidance for the treatment and management of non‐renal systemic lupus erythematosus (SLE); treatment and management of lupus nephritis are addressed in a separate guideline. Methods Clinical questions for treatment and management of SLE were developed in the PICO format (population, intervention, comparator, and outcome). Systematic literature reviews were developed for each PICO question, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology was used to assess evidence quality and formulate recommendations. The Voting Panel achieved a consensus of ≥70% agreement on the direction (for or against) and strength (strong or conditional) of each recommendation. Results We present recommendations and ungraded, consensus‐based good practice statements for the treatment and management of SLE that are applicable to pediatric and adult patients. Recommendations emphasize uniform treatment with hydroxychloroquine, limiting duration of glucocorticoid use, and early introduction of conventional and/or biologic immunosuppressive therapies to achieve and maintain control of SLE inflammation (remission or a low level of disease activity), reduce SLE‐related morbidity and mortality, and minimize medication‐related toxicities. Conclusion This guideline presents direction regarding treatment and management of SLE and provides a foundation for well‐informed, shared clinician–patient decision‐making. These recommendations should not be used to limit or deny access to therapies, as treatment decisions may vary due to the unique clinical situation and personal preferences of each person with SLE.

Background The Woven EndoBridge (WEB) device represents an innovative solution for cerebral aneurysm occlusion, particularly for challenging wide-neck bifurcation aneurysms. However, factors affecting sustained occlusion remain poorly understood. We utilized machine learning to attempt to identify predictors of favorable long-term outcomes following WEB treatment. Methods In this multicenter retrospective study, we collected patient demographics, aneurysm characteristics, procedural details, and clinical outcomes. The primary endpoint was improvement in occlusion status, defined as maintained Raymond-Roy Occlusion Classification (RROC) grade 1, or improvement from grade 2 to 1, or from grade 3 to either 2 or 1 on final angiographic follow up. The dataset was split into training (75%) and validation (25%) sets. The CatBoost algorithm was selected based on performance metrics, with Shapley Additive exPlanations (SHAP) values calculated to determine feature importance. Furthermore, a multivariable binomial logistic regression model was performed to validate machine learning findings. Results Among 720 aneurysms from 36 hospitals, 84% showed improvement in occlusion at follow up. Both machine learning and multivariable logistic regression identified aneurysm height as the most consistent correlate of nonimprovement (odds ratio (OR) 0.90 per mm, p = 0.022). In the CatBoost model, the highest-ranking features by SHAP included aneurysm height, patient age, treatment acuity, ACom location, WEB-SLS device, bifurcation anatomy, aneurysm multiplicity, baseline modified Rankin Scale, access route, and partial thrombosis. Conclusions Machine-learning and regression analyses identified consistent predictors of occlusion improvement after WEB treatment, with aneurysm height most strongly linked to nonimprovement. These insights may guide patient selection and follow up. Findings require cautious interpretation and external validation in larger cohorts.

Background: Breast cancer polygenic risk scores (PRS) and traditional risk models (e.g., the Gail model [Gail]) are known to contribute largely independent information, but it is unclear how the overlap varies by ancestry, age, disease type (invasive breast cancer, DCIS), and risk threshold. Methods: In a retrospective case–control study, we evaluated risk prediction performance in 180,398 women (161,849 of European ancestry; 18,549 of Asian ancestry). Odds ratios (ORs) from logistic regression models and the area under the receiver operating characteristic curve (AUC) were estimated. Results: PRS for invasive disease showed a stronger association in younger (<50 years) women (OR = 2.51, AUC = 0.622) than in women ≥ 50 years (OR = 2.06, AUC = 0.653) of European ancestry. PRS performance in Asians was lower (OR range = 1.62–1.64, AUC = 0.551–0.600). Gail performance was modest across groups and poor in younger Asian women (OR = 0.94–0.99, AUC = 0.523–0.533). Age interactions were observed for both PRS (p < 0.001) and Gail (p < 0.001) in Europeans, whereas in Asians, age interaction was observed only for Gail (invasive: p < 0.001; DCIS: p = 0.002). PRS identified more high-risk individuals than Gail in Asian populations, especially ≥50 years, while Gail identified more in Europeans. Overlap between PRS, Gail, and family history was limited at higher thresholds. Calibration analysis, comparing empirical and model-based ROC curves, showed divergence for both PRS and Gail (p < 0.001), which indicates miscalibration. In Europeans, family history and prior biopsies drove Gail discrimination. In younger Asians, age at first live birth was influential. Conclusions: PRS adds value to risk stratification beyond traditional tools, especially in younger women and Asian ancestry populations.

Background: Cardiac disease is the leading cause of premature mortality in Friedreich Ataxia (FA). However, validated prognostic indicators or early imaging biomarkers that can reliably predict cardiac events are lacking. To address this gap, we created a multicenter FA cardiac registry to characterize disease progression and identify early echocardiographic (echo) predictors of major adverse cardiac events (MACE). Methods: FA subjects from 6 North American centers with at least two echos performed ≥5 years apart were included. Demographics, FA-specific disease characteristics, and MACE (a composite of death, heart failure hospitalization, aborted sudden cardiac death, and/or life-threatening arrhythmia) were abstracted. Digital echo images were re-read at a centralized core lab. Paired T tests were utilized for comparison of the normally distributed first and second echo parameters, and logistic regression models were utilized to evaluate for predictors of MACE. Results: Of 115 subjects, 52 (45%) were female. Mean age at diagnosis was 10 ± 3 years, median GAA1 repeat length (a marker of genetic severity) was 700 (range 66–1200), and median age at first analyzed echo was 12 years (range 4-36). MACE occurred in 35 (30%) of the cohort. Serial echocardiograms demonstrated progressive worsening of multiple cardiac parameters over time, including markers of ventricular thickness and hypertrophy, chamber size, systolic function, and novel markers of atrial and ventricular strain (Table 1). On univariate analysis, several markers of hypertrophy and systolic function from the earliest analyzed echo predicted MACE. However, after adjusting for age of diagnosis, GAA1 repeat length, and collinearity among variables, only posterior wall thickness in diastole (PWTd) remained an independent predictor of MACE (odds ratio 1.8 per mm increase, 95% CI 1.1–3.3, p = 0.028). Conclusions: This multicenter FA registry identifies early posterior wall thickness as a significant and independent predictor of major adverse cardiac events in FA. Each millimeter increase in PWTd on early echo is associated with nearly double the odds of MACE. This commonly acquired parameter is often overlooked and may serve as a powerful early marker of cardiac risk. Further investigation of PWTd as a potential surrogate endpoint for therapeutic trials in FA is warranted.

Background: Heart transplantation is the definitive treatment of end-stage heart failure and is a complex process involving coordination in procurement, preservation, and transport of a donor organ to a recipient. There are different heart transport methods, including the traditional static methods of Cooler and Ryobi and advanced dynamic methods, including SherpaPak and the Organ Care System (OCS). The aim of the study is to compare the post-transplant outcome of these in patients bridged with Impella 5.5. Method: A retrospective study was conducted between 2020 and 2025 after IRB approval. Patient demographics and clinical data was extracted from the medical record. Cox proportional hazards regression model was applied to identify independent predictors of mortality across 30-day, 90-day, and 1-year intervals. Results: 123 patients were included in the analysis. Age, EF and Race were similar between all groups. The transport method was a significant predictor of 1-year mortality. Use of OCS (HR=0.022, p value <0.05) and SherpaPak (HR=0.066, p value <0.05) was associated with a significant decrease in mortality compared to traditional cooler use. Across 30-day, 90-day, and 1-year intervals, OCS showed the strongest survival benefit, while SherpaPak also demonstrated reduced mortality, but less significant compared to OCS. Conclusion: Transport method is a strong predictor of 1-year post-transplant mortality, with OCS showing the most pronounced effect in reducing the risk of 1-year mortality as well as mortality across 30-day and 90-day intervals. These findings support broader adoption of advanced transport systems in clinical practice to improve post-transplant outcomes.

Background: Pulmonary hypertension (PH) is a life-threatening disease affecting up to 1% of the global population. Diagnosis can be challenging and is often delayed due to the need for advanced imaging and invasive procedures. The use of artificial intelligence applied to ECGs (ECG-AI) has been shown to detect subtle patterns in voltage-time data and may be a valuable tool for the early detection of PH. Hypothesis and Purpose: To evaluate the performance of a previously trained, ECG-AI algorithm to detect PH (ECG-AI PH) using real-world data (RWD) collected in a multicenter, validation study. A joint primary hypothesis required sensitivity (Sn), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV) to exceed the null values of 76%, 70%, 10% and 90%. Study Design and Methods: This retrospective validation study was conducted at 5 geographically diverse U.S. health systems. Adult subjects were eligible for inclusion if they had a 12-lead ECG paired with an echocardiogram (Echo) in which tricuspid regurgitation velocity (TRV) was recorded, following presentation with dyspnea. Patients were classified according to echocardiographic criteria as either PH (PH+, TRV >3.4 m/s) or controls (PH-, TRV ≤2.8 m/s) to simulate the real-world use of ECG-AI, where a positive result could lead to a follow-up Echo. The study database was locked before processing the digital ECGs with ECG-AI PH. Performance was also estimated in a subset of subjects that later had a right heart catheterization using mPAP ≥ 20mmHg as the definition of PH. Results: A total of 14281 subjects (53% female, 63% aged 50+ years) met the inclusion criteria, including 3019 PH+ cases and 11262 PH- controls (Figure). Sn and Sp were 84.0% (95% CI: 82.6%, 85.3%) and 71.7% (95% CI: 70.9%, 72.6%), respectively. The positive and negative predictive values were 18.9% (95% CI: 18.4%, 19.4%) and 98.3% (95% CI: 98.1%, 98.4%), respectively, at 7.3% prevalence. Each endpoint met pre-defined performance criteria. In the subset of 1683 subjects with a follow up RHC, performance remained robust (Sn 85% (1155/1358); Sp 46% (151/325)). Conclusion: While ECG-AI PH was first developed as an investigational tool to detect PH, continued development as software as a medical device for clinical use demonstrated that the algorithm retained strong performance to detect PH in diverse, non-overlapping clinical settings and patient populations.