Citations

Background and Aims: Alcohol-associated hepatitis (AH) poses significant short-term mortality. Existing prognostic models lack precision for 90-day mortality. Utilizing artificial intelligence in a global cohort, we sought to derive and validate an enhanced prognostic model. Approach and Results: The Global AlcHep initiative, a retrospective study across 23 centers in 12 countries, enrolled patients with AH per National Institute for Alcohol Abuse and Alcoholism criteria. Centers were partitioned into derivation (11 centers, 860 patients) and validation cohorts (12 centers, 859 patients). Focusing on 30 and 90-day postadmission mortality, 3 artificial intelligence algorithms (Random Forest, Gradient Boosting Machines, and eXtreme Gradient Boosting) informed an ensemble model, subsequently refined through Bayesian updating, integrating the derivation cohort’s average 90-day mortality with each center’s approximate mortality rate to produce posttest probabilities. The ALCoholic Hepatitis Artificial INtelligence Ensemble score integrated age, gender, cirrhosis, and 9 laboratory values, with center-specific mortality rates. Mortality was 18.7% (30 d) and 27.9% (90 d) in the derivation cohort versus 21.7% and 32.5% in the validation cohort. Validation cohort 30 and 90-day AUCs were 0.811 (0.779–0.844) and 0.799 (0.769–0.830), significantly surpassing legacy models like Maddrey’s Discriminant Function, Model for End-Stage Liver Disease variations, age-serum bilirubin-international normalized ratio-serum Creatinine score, Glasgow, and modified Glasgow Scores (p < 0.001). ALCoholic Hepatitis Artificial INtelligence Ensemble score also showcased superior calibration against MELD and its variants. Steroid use improved 30-day survival for those with an ALCoholic Hepatitis Artificial INtelligence Ensemble score > 0.20 in both derivation and validation cohorts. Conclusions: Harnessing artificial intelligence within a global consortium, we pioneered a scoring system excelling over traditional models for 30 and 90-day AH mortality predictions. Beneficial for clinical trials, steroid therapy, and transplant indications, it’s accessible at: https://aihepatology.shinyapps.io/ALCHAIN/.

The 2023 American Epilepsy Society Annual Course “It’s About Time” addressed timing in epilepsy evaluation and treatment with respect to health disparity and vulnerable populations and diagnostic, clinical, and epilepsy surgery evaluation. This comprehensive course included topics on gaps in epilepsy care and optimization of behavioral health for patients with epilepsy. The summary details current knowledge in areas of seizure forecasting and epileptogenesis. Intricacies and controversies over timing were discussed for treatment of nonconvulsive seizures and ictal-interictal patterns, acute symptomatic seizures, neuromodulation versus surgery, and epilepsy surgery in status epilepticus. Timing regarding clinical care in autoimmune-associated epilepsy, developmental and epileptic encephalopathy, and dietary therapy were examined. Additionally, salient topics on using novel biomarkers and collaboration with neuropsychological outcomes were also tackled in this all-encompassing lecture series.

Moderate traumatic brain injury (TBI) is a diagnosis that describes diverse patients with heterogeneity of primary injuries. Defined by a Glasgow Coma Scale between 9 and 12, this category includes patients who may neurologically worsen and require increasing intensive care resources and/or emergency neurosurgery. Despite the unique characteristics of these patients, there have not been specific guidelines published before this effort to support decision-making in these patients. A Delphi consensus group from the Latin American Brain Injury Consortium was established to generate recommendations related to the definition and categorization of moderate TBI. Before an in-person meeting, a systematic review of the literature was performed identifying evidence relevant to planned topics. Blinded voting assessed support for each recommendation. A priori the threshold for consensus was set at 80% agreement. Nine PICOT questions were generated by the panel, including definition, categorization, grouping, and diagnosis of moderate TBI. Here, we report the results of our work including relevant consensus statements and discussion for each question. Moderate TBI is an entity for which there is little published evidence available supporting definition, diagnosis, and management. Recommendations based on experts' opinion were informed by available evidence and aim to refine the definition and categorization of moderate TBI. Further studies evaluating the impact of these recommendations will be required.

Natural 4-1BBL (CD137L) is a cell membrane-bound protein critical to the expansion, effector function, and survival of CD8+ T cells. We reported the generation of an active soluble oligomeric construct, SA-4-1BBL, with demonstrated immunoprevention and immunotherapeutic efficacy in various mouse tumor models. Herein, we developed an oncolytic adenovirus (OAd) for the delivery and expression of SA-4-1BBL (OAdSA-4-1BBL) into solid tumors for immunotherapy. SA-4-1BBL protein expressed by this construct produced T-cell proliferation in vitro. OAdSA-4-1BBL decreased cell viability in two mouse lung cancer cell lines, TC-1 and CMT64, but not in the non-cancerous lung MM14.Lu cell line. OAdSA-4-1BBL induced programmed cell death types I and II (apoptosis and autophagy, respectively), and autophagy-mediated adenosine triphosphate (ATP) release was also detected. Intratumoral injection of OAdSA-4-1BBL efficiently expressed the SA-4-1BBL protein in the tumors, resulting in significant tumor suppression in a syngeneic subcutaneous TC-1 mouse lung cancer model. Tumor suppression was associated with a higher frequency of dendritic cells and an increased infiltration of cytotoxic CD8+ T and NK cells into the tumors. Our data suggest that OAdSA-4-1BBL may present an efficacious alternative therapeutic strategy against lung cancer as a standalone construct or in combination with other immunotherapeutic modalities, such as immune checkpoint inhibitors.

Primary Care Physicians (PCPs) are the first point of contact in healthcare. Because PCPs face the challenge of managing diverse patient populations while maintaining up-to-date medical knowledge and updated health records, this study explores the current outcomes and effectiveness of implementing Artificial Intelligence-based Clinical Decision Support Systems (AI-CDSSs) in Primary Healthcare (PHC). Following the PRISMA-ScR guidelines, we systematically searched five databases, PubMed, Scopus, CINAHL, IEEE, and Google Scholar, and manually searched related articles. Only CDSSs powered by AI targeted to physicians and tested in real clinical PHC settings were included. From a total of 421 articles, 6 met our criteria. We found AI-CDSSs from the US, Netherlands, Spain, and China whose primary tasks included diagnosis support, management and treatment recommendations, and complication prediction. Secondary objectives included lessening physician work burden and reducing healthcare costs. While promising, the outcomes were hindered by physicians’ perceptions and cultural settings. This study underscores the potential of AI-CDSSs in improving clinical management, patient satisfaction, and safety while reducing physician workload. However, further work is needed to explore the broad spectrum of applications that the new AI-CDSSs have in several PHC real clinical settings and measure their clinical outcomes.

PURPOSE Allogeneic hematopoietic cell transplantation (HCT) improves outcomes for patients with AML harboring an internal tandem duplication mutation of FLT3 ( FLT3-ITD) AML. These patients are routinely treated with a FLT3 inhibitor after HCT, but there is limited evidence to support this. Accordingly, we conducted a randomized trial of post-HCT maintenance with the FLT3 inhibitor gilteritinib (ClinicalTrials.gov identifier: NCT02997202 ) to determine if all such patients benefit or if detection of measurable residual disease (MRD) could identify those who might benefit. METHODS Adults with FLT3-ITD AML in first remission underwent HCT and were randomly assigned to placebo or 120 mg once daily gilteritinib for 24 months after HCT. The primary end point was relapse-free survival (RFS). Secondary end points included overall survival (OS) and the effect of MRD pre- and post-HCT on RFS and OS. RESULTS Three hundred fifty-six participants were randomly assigned post-HCT to receive gilteritinib or placebo. Although RFS was higher in the gilteritinib arm, the difference was not statistically significant (hazard ratio [HR], 0.679 [95% CI, 0.459 to 1.005]; two-sided P = .0518). However, 50.5% of participants had MRD detectable pre- or post-HCT, and, in a prespecified subgroup analysis, gilteritinib was beneficial in this population (HR, 0.515 [95% CI, 0.316 to 0.838]; P = .0065). Those without detectable MRD showed no benefit (HR, 1.213 [95% CI, 0.616 to 2.387]; P = .575). CONCLUSION Although the overall improvement in RFS was not statistically significant, RFS was higher for participants with detectable FLT3-ITD MRD pre- or post-HCT who received gilteritinib treatment. To our knowledge, these data are among the first to support the effectiveness of MRD-based post-HCT therapy.

Introduction The coronavirus disease 2019 (COVID‐19) pandemic has had a global impact on healthcare systems. There is limited data on the influence of COVID‐19 on treatment and outcomes in patients with intracranial aneurysms. We aimed to investigate the impact of COVID‐19 on the overall complications, including ischemic stroke and subarachnoid hemorrhage (SAH) rates in patients treated for intracranial aneurysms (IAs). Methods This national, multicenter, retrospective cohort study included patients diagnosed and treated for IAs from January 2016 to December 2020 in the National Inpatient Sample (NIS). A total of 57,715 admissions were identified. Of these, 45,979 occurred pre‐COVID and 11,736 during the COVID pandemic period. The outcome data points included the occurrence of postprocedural ischemic strokes or SAHs, death, non‐routine discharge, total charges (US dollars), and length of stay (days). A 1:1 propensity score matching protocol was applied using a K‐nearest neighbor approach to evaluate differences in the outcome data points between the pre‐COVID and during COVID periods. The trends during the study period were assessed using piecewise joinpoint regression with the Mann‐Kendall test. Results Overall, the mean age was 65 years, with most of the patients (69.9%) being females. Endovascular interventions were performed in 82.9% of pre‐COVID IAs admissions compared to 82.4% during the COVID period, while open surgical treatment was performed in 17.1% of pre‐COVID and 17.6% of the patients during COVID (p=0.625). After matching, there were no differences in length of stay (p=0.266), non‐home discharge (p=0.475), and in‐hospital mortality rates (p=0.305) between the two periods; however, the overall complication rate was significantly higher during the pandemic (31.1% vs. 28.3%; p<0.001). From 2016 to 2020, an upward trend in hospitalizations for ischemic stroke was seen among patients treated for IAs (6.1% to 7.9%; p=0.04). No trends were observed with respect to the occurrence of SAH or death (p=0.31). Patients hospitalized after treatment of IAs during the COVID pandemic had significantly higher odds of ischemic strokes (OR 1.13; 95% CI 1.05 to 1.22; p=0.03) but not SAH (OR 0.97; 95% CI 0.88 to 1.06; p=0.89). Conclusion The COVID‐19 pandemic has significantly impacted the healthcare system. In patients receiving treatment for IAs, this analysis noted a correlation between the COVID‐19 pandemic and postoperative complications, notably ischemic strokes. Unraveling the pandemic’s “black box” leads to awareness of plausible breaches within the system, which acts as a crucial component in improving situational readiness and preparedness in the event of similar large‐scale crises.