The CCR6-CCL20 axis promotes regulatory T cell glycolysis and immunosuppression in tumors.

Regulatory T cells (Tregs) are important players in the tumor microenvironment. However, the mechanisms behind their immunosuppressive effects are poorly understood. We found that CCR6-CCL20 activity in tumor-infiltrating Tregs is associated with greater glycolytic activity and ablation of Ccr6 reduced glycolysis and lactic acid production while increasing compensatory glutamine metabolism. Immunosuppressive activity towards CD8+ T cells was abrogated in Ccr6-/- Tregs due to reduction in activation-induced glycolysis. Furthermore, Ccr6-/- mice exhibited improved survival across multiple tumor models compared to wildtype mice, and Treg and CD8+ T-cell depletion abrogated the improvement. In addition, Ccr6 ablation further promoted the efficacy of anti-PD-1 therapy in a preclinical glioma model. Follow-up knockdown of Ccl20 with siRNA also demonstrated improvement in antitumor efficacy. Our results unveil CCR6 as a marker and regulator of Treg-induced immunosuppression and identify approaches to target the metabolic determinants of Treg immunosuppressive activity.

MedPodGPT: A multilingual audio-augmented large language model for medical research and education.

The proliferation of medical podcasts has generated an extensive repository of audio content, rich in specialized terminology, diverse medical topics, and expert dialogues. Here we introduce a computational framework designed to enhance large language models (LLMs) by leveraging the informational content of publicly accessible medical podcast data. This dataset, comprising over 4, 300 hours of audio content, was transcribed to generate over 39 million text tokens. Our model, MedPodGPT, integrates the varied di-alogue found in medical podcasts to improve understanding of natural language nuances, cultural contexts, and medical knowledge. Evaluated across multiple benchmarks, MedPodGPT demonstrated an average improvement of 2.31% over standard open-source benchmarks and showcased an improvement of 2.58% in its zero-shot multilingual transfer ability, effectively generalizing to different linguistic contexts. By harnessing the untapped potential of podcast content, MedPodGPT advances natural language processing, offering enhanced capabilities for various applications in medical research and education.

Association of Semaglutide With Tobacco Use Disorder in Patients With Type 2 Diabetes : Target Trial Emulation Using Real-World Data.

BACKGROUND: Reports of reduced desire to smoke in patients treated with semaglutide, a glucagon-like peptide receptor agonist (GLP-1RA) medication for type 2 diabetes mellitus (T2DM) and obesity, have raised interest about its potential benefit for tobacco use disorders (TUDs). OBJECTIVE: To examine the association of semaglutide with TUD-related health care measures in patients with comorbid T2DM and TUD. DESIGN: Emulation target trial based on a nationwide population-based database of patient electronic health records. SETTING: United States, 1 December 2017 to 31 March 2023. PARTICIPANTS: Seven target trials were emulated among eligible patients with comorbid T2DM and TUD by comparing the new use of semaglutide versus 7 other antidiabetes medications (insulins, metformin, dipeptidyl-peptidase-4 inhibitors, sodium-glucose cotransporter-2 inhibitors, sulfonylureas, thiazolidinediones, and other GLP-1RAs). MEASUREMENTS: The TUD-related health care measures (medical encounter for diagnosis of TUD, smoking cessation medication prescriptions, and smoking cessation counseling) that occurred within a 12-month follow-up were examined using Cox proportional hazards and Kaplan-Meier survival analyses. RESULTS: The study compared 222 942 new users of antidiabetes medications including 5967 of semaglutide. Semaglutide was associated with a significantly lower risk for medical encounters for TUD diagnosis compared with other antidiabetes medications, and was strongest compared with insulins (hazard ratio [HR], 0.68 [95% CI, 0.63 to 0.74]) and weakest but statistically significant compared with other GLP-1RAs (HR, 0.88 [CI, 0.81 to 0.96]). Semaglutide was associated with reduced smoking cessation medication prescriptions and counseling. Similar findings were observed in patients with and without a diagnosis of obesity. For most of the group comparisons, the differences occurred within 30 days of prescription initiation. LIMITATION: Documentation bias, residual confounding, missing data on current smoking behavior, body mass index, and medication adherence. CONCLUSION: Semaglutide was associated with lower risks for TUD-related health care measures in patients with comorbid T2DM and TUD compared with other antidiabetes medications including other GLP-1Ras, primarily within 30 days of prescription. These findings suggest the need for clinical trials to evaluate semaglutide's potential for TUD treatment. PRIMARY FUNDING SOURCE: National Institutes of Health.

Extraction of Unstructured Electronic Health Records to Evaluate Glioblastoma Treatment Patterns.

PURPOSE: Data on lines of therapy (LOTs) for cancer treatment are important for clinical oncology research, but LOTs are not explicitly recorded in electronic health records (EHRs). We present an efficient approach for clinical data abstraction and a flexible algorithm to derive LOTs from EHR-based medication data on patients with glioblastoma multiforme (GBM). METHODS: Nonclinicians were trained to abstract the diagnosis of GBM from EHRs, and their accuracy was compared with abstraction performed by clinicians. The resulting data were used to build a cohort of patients with confirmed GBM diagnosis. An algorithm was developed to derive LOTs using structured medication data, accounting for the addition and discontinuation of therapies and drug class. Descriptive statistics were calculated and time-to-next-treatment (TTNT) analysis was performed using the Kaplan-Meier method. RESULTS: Treating clinicians as the gold standard, nonclinicians abstracted GBM diagnosis with a sensitivity of 0.98, specificity 1.00, positive predictive value 1.00, and negative predictive value 0.90, suggesting that nonclinician abstraction of GBM diagnosis was comparable with clinician abstraction. Of 693 patients with a confirmed diagnosis of GBM, 246 patients contained structured information about the types of medications received. Of them, 165 (67.1%) received a first-line therapy (1L) of temozolomide, and the median TTNT from the start of 1L was 179 days. CONCLUSION: We described a workflow for extracting diagnosis of GBM and LOT from EHR data that combines nonclinician abstraction with algorithmic processing, demonstrating comparable accuracy with clinician abstraction and highlighting the potential for scalable and efficient EHR-based oncology research.

Key Opinion Leaders' Interviews to Inform the Future of Benefit-Risk Planning in the Medical Total Product Life Cycle of Global Pharmaceutical and Medical Device Organizations.

BACKGROUND AND OBJECTIVES: Key opinion leader (KOL) interviews were conducted by the Benefit-Risk Assessment Planning (BRAP) Taskforce to seek expert opinion mainly from industry and regulatory bodies, about the current status and future direction of benefit-risk assessment (BRA) planning in the lifecycle of medical product development. The findings from these interviews are intended to help communication concerning planning for BRA between industry and regulators and shape future guidance. METHODS: Key opinion leader interviews consisted of 5 questions related to BRA planning, which were administered to volunteers (mainly clinicians and statisticians) within a pool of experienced pharmaceutical and medical device professionals representing academia, industry, regulatory agencies and a patient group. The interviewees' responses to the 5 questions were summarized. To analyze the qualitative data, a Coding System was developed to label themes arising from the interviews. The key findings from the interviews were summarized into a Master Template. A quantitative analysis based on descriptive statistics was also conducted. RESULTS: Of the 27 interviewees, there were 11 professionals from regulatory agencies, 11 from industry, 4 from academia and 1 from a patient advocacy group. Key findings based on the comments provided by 48% of the interviewees indicated the need of incorporating BRA into other (e.g., existing) processes with the importance of alignment between processes being stressed in the comments provided by 59% of the interviewees. Commencing BRA early in the product lifecycle was emphasized in comments provided by 44% of the interviewees. Among other needs identified were an appropriate contextualization of benefits and risks (based on comments provided by 41% of interviewees) through adoption of an integrated approach with structured support by regulatory agencies and a need for understanding the audience with better communication of benefit-risk (BR) among all stakeholders (based on comments provided by 44% of the interviewees). Almost all comments provided by interviewees (96%) highlighted the importance of utilizing patient experience/preference to guide new product development and BRA. Comments provided by 74% of the interviewees expressed the need to understand patient tolerance for risk and trade-offs, with a majority (78%) of interviewees highlighting how to gather information, and 59% stressing the need for the selection and development of appropriate methodologies as important considerations for enhancing the quality and relevance of the data collected from patients. CONCLUSIONS: Interviewees indicated that BRA should commence early in the medical product development and inform decision-making throughout the product lifecycle. Better planning and integration of BRA into existing processes within industry would be valuable. The importance of incorporating the patient voice into BRA and medical product development was emphasized. Other key findings from the KOL interviews included a need for improved communication of BR information, and establishment of methodologies for performing BRA and soliciting patient input.

Application of estimand framework to the design and analysis of multi-regional clinical trials.

With the increasing globalization of drug development and the publication of the International Council for Harmonisation (ICH) E17 guideline (ICH International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use 2017), multi-regional clinical trials (MRCTs) have become a preferred option to accelerate the availability of new medical products by design, execution and simultaneous submission under one protocol. MRCTs, with the participation of all major regions including countries from both developed and emerging markets, surely make new drug development more efficient. Even though the proposed estimand framework (ICH E9 (R1) (2019), came later in 2019 and was not mentioned in ICH E17, the application of the estimand framework has the potential to enhance the design, execution, and analysis in MRCTs. Defining an estimand within the regional context in MRCTs is an important issue that requires careful consideration. Given that consistency evaluation of treatment effects across regions is critical in MRCTs, the utilization of the estimand framework for regional consistency evaluation is also worth discussion. This paper aims to address these two questions. The five attributes of the estimand definition are discussed within a multi-regional context. It is imperative to thoroughly consider regional intrinsic/extrinsic factors when planning the estimand and estimation of MRCTs. A holistic approach is summarized to conduct consistency evaluation. When a regional inconsistency is observed, the possible reasons need to be further explored under five attributes of the estimand framework. Two real case studies are discussed to illustrate the application of the estimand framework in the consistency evaluation.

Associations of semaglutide with incidence and recurrence of alcohol use disorder in real-world population.

Alcohol use disorders are among the top causes of the global burden of disease, yet therapeutic interventions are limited. Reduced desire to drink in patients treated with semaglutide has raised interest regarding its potential therapeutic benefits for alcohol use disorders. In this retrospective cohort study of electronic health records of 83,825 patients with obesity, we show that semaglutide compared with other anti-obesity medications is associated with a 50%-56% lower risk for both the incidence and recurrence of alcohol use disorder for a 12-month follow-up period. Consistent reductions were seen for patients stratified by gender, age group, race and in patients with and without type 2 diabetes. Similar findings are replicated in the study population with 598,803 patients with type 2 diabetes. These findings provide evidence of the potential benefit of semaglutide in AUD in real-world populations and call for further randomized clinicl trials.

Single-cell and spatial alterations of neural cells and circuits in clinical and translational medicine.

The spatiotemporal heterogeneity of neurons, circuits and regulators is being uncovered at a single-cell level, from single-cell gene expression to functional regulations. The classifications, architectonics and functional communications amongst neural cells and circuits within the brain can be clearly delineated using single-cell multiomics and transomics. This Editorial highlights the spatiotemporal heterogeneity of neurons and circuits as well as regulators, initiates the translation of neuronal diversity and spatial organisation at single-cell levels into clinical considerations, and enables the discovery and development of new therapies for neurological diseases. It is predicted that single-cell and spatial multiomics will be integrated with metabolomic profiles and corresponding gene epigenetic modifications. The interactions amongst DNAs, RNAs and proteins in a cell provide details of intracellular functional regulations and new opportunities for the translation of temporospatial diversity of neural cell subtypes/states into clinical practice. The application of single-cell multiomics with four-dimensional genome to the human pathological brain will lead us to a new milestone of the diagnosis and treatment.

Macrophage PET imaging in mouse models of cardiovascular disease and cancer with an apolipoprotein-inspired radiotracer.

Macrophages are key inflammatory mediators in many pathological conditions, including cardiovascular disease (CVD) and cancer, the leading causes of morbidity and mortality worldwide. This makes macrophage burden a valuable diagnostic marker and several strategies to monitor these cells have been reported. However, such strategies are often high-priced, non-specific, invasive, and/or not quantitative. Here, we developed a positron emission tomography (PET) radiotracer based on apolipoprotein A1 (ApoA1), the main protein component of high-density lipoprotein (HDL), which has an inherent affinity for macrophages. We radiolabeled an ApoA1-mimetic peptide (mA1) with zirconium-89 (89Zr) to generate a lipoprotein-avid PET probe (89Zr-mA1). We first characterized 89Zr-mA1's affinity for lipoproteins in vitro by size exclusion chromatography. To study 89Zr-mA1's in vivo behavior and interaction with endogenous lipoproteins, we performed extensive studies in wildtype C57BL/6 and Apoe-/- hypercholesterolemic mice. Subsequently, we used in vivo PET imaging to study macrophages in melanoma and myocardial infarction using mouse models. The tracer's cell specificity was assessed by histology and mass cytometry (CyTOF). Our data show that 89Zr-mA1 associates with lipoproteins in vitro. This is in line with our in vivo experiments, in which we observed longer 89Zr-mA1 circulation times in hypercholesterolemic mice compared to C57BL/6 controls. 89Zr-mA1 displayed a tissue distribution profile similar to ApoA1 and HDL, with high kidney and liver uptake as well as substantial signal in the bone marrow and spleen. The tracer also accumulated in tumors of melanoma-bearing mice and in the ischemic myocardium of infarcted animals. In these sites, CyTOF analyses revealed that natZr-mA1 was predominantly taken up by macrophages. Our results demonstrate that 89Zr-mA1 associates with lipoproteins and hence accumulates in macrophages in vivo. 89Zr-mA1's high uptake in these cells makes it a promising radiotracer for non-invasively and quantitatively studying conditions characterized by marked changes in macrophage burden.

Staged Versus Concomitant TAVI and PCI for the Treatment of Coexisting Aortic Stenosis and Coronary Artery Disease.

Aortic stenosis (AS) is one of the most common valvular pathologies. Severe coronary artery disease (CAD) often coexists with AS. Transcatheter aortic valve implantation (TAVI) and percutaneous coronary intervention (PCI) have been established as alternatives to open surgical interventions. The data on the timing for the treatment of the 2 conditions are scarce and depend on multiple factors. This review compares the clinical outcomes of the concomitant versus staged PCI and TAVI for the treatment of AS and CAD. A systematic, electronic search was performed according to Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines to identify relevant articles that compared outcomes of the staged versus concomitant approaches for the TAVI and PCI. Seven studies were included involving 3745 patients. We found no statistically significant difference in primary outcomes such as 30-day mortality [odds ratio (OR) = 0.78; 95% confidence interval (CI): 0.39-1.57] and secondary outcomes including length of hospital stay (mean difference = -4.74, 95% CI: -10.96 to 1.48), new-onset renal failure (OR = 0.83, 95% CI: 0.22-3.13), cerebrovascular accidents (OR = 1.28, 95% CI: 0.64-2.57), and intraoperative blood loss (OR = 0.83, 95% CI: 0.32-2.12). New pacemaker insertion was statistically significant in favor of the concomitant approach (OR = 0.78, 95% CI: 0.63-0.96). This analysis suggests that while the 2 approaches are largely comparable in terms of most outcomes, patients at risk of requiring a pacemaker postprocedure may benefit from a concomitant approach. In conclusion, concomitant TAVI + PCI approach is nonsuperior to the staged approach for the treatment of CAD and AS. This review calls for robust trials in the field to further strengthen the evidence.

Health systems challenges, mitigation strategies and adaptations to maintain essential health services during the COVID-19 pandemic: learnings from the six geopolitical regions in Nigeria.

BACKGROUND: The COVID-19 pandemic control strategies disrupted the smooth delivery of essential health services (EHS) globally. Limited evidence exists on the health systems lens approach to analyzing the challenges encountered in maintaining EHS during the COVID-19 pandemic. This study aimed to identify the health system challenges encountered and document the mitigation strategies and adaptations made across geopolitical zones (GPZs) in Nigeria. METHODS: The national qualitative survey of key actors across the six GPZs in Nigeria involved ten states and the Federal Capital Territory (FCT) which were selected based on resilience, COVID-19 burden and security considerations. A pre-tested key informant guide was used to collect data on service utilization, changes in service utilization, reasons for changes in primary health centres' (PHCs) service volumes, challenges experienced by health facilities in maintaining EHS, mitigation strategies implemented and adaptations to service delivery. Emerging sub-themes were categorized under the appropriate pillars of the health system. RESULTS: A total of 22 respondents were interviewed. The challenges experienced in maintaining EHS cut across the pillars of the health systems including: Human resources shortage, shortages in the supply of personal protective equipments, fear of contracting COVID-19 among health workers misconception, ignorance, socio-cultural issues, lockdown/transportation and lack of equipment/waiting area (. The mitigation strategies included improved political will to fund health service projects, leading to improved accessibility, affordability, and supply of consumables. The health workforce was motivated by employing, redeploying, training, and incentivizing. Service delivery was reorganized by rescheduling appointments and prioritizing some EHS such as maternal and childcare. Sustainable systems adaptations included IPC and telehealth infrastructure, training and capacity building, virtual meetings and community groups set up for sensitization and engagement. CONCLUSION: The mitigation strategies and adaptations implemented were important contributors to EHS recovery especially in the high resilience LGAs and have implications for future epidemic preparedness plans.

Simultaneous Global Drug Development and Multiregional Clinical Trials (MRCT): 5 Years After Implementation of ICH E17 Guidelines.

The ICH E17 guidelines (2014-2017) on Multiregional Clinical Trials (MRCT) was a joint effort by the regulators and industry to facilitate simultaneous global drug development and registration through taking a strategic approach for clinical trials. In other words, the objective was to reduce the time it takes to bringing medications to patients around the world through minimizing unnecessary duplication of local or regional studies, which may add the regulatory burden to cost and time of bringing new therapies to patients. Under the auspices of ICH, training materials were created and provided to various stakeholders. Despite the successful promotion of the benefits of ICH E17 MRCT guidelines across the different regions, the uptake of some concepts (e.g., pooling strategy) in the ICH E17 guidelines has been slow. This paper describes various factors which could affect the conduct of MRCT at a global level, including ambiguity in definition of "region" (in MRCT), new regulatory requirements to enroll a diverse patient population, the use of decentralized clinical trials, use of data sources other than randomized clinical trials (e.g., use of Real Word Data), and the impact of the COVID-19 pandemic on the conduct of MRCT.

Integrating predictive coding and a user-centric interface for enhanced auditing and quality in cancer registry data.

Data curation for a hospital-based cancer registry heavily relies on the labor-intensive manual abstraction process by cancer registrars to identify cancer-related information from free-text electronic health records. To streamline this process, a natural language processing system incorporating a hybrid of deep learning-based and rule-based approaches for identifying lung cancer registry-related concepts, along with a symbolic expert system that generates registry coding based on weighted rules, was developed. The system is integrated with the hospital information system at a medical center to provide cancer registrars with a patient journey visualization platform. The embedded system offers a comprehensive view of patient reports annotated with significant registry concepts to facilitate the manual coding process and elevate overall quality. Extensive evaluations, including comparisons with state-of-the-art methods, were conducted using a lung cancer dataset comprising 1428 patients from the medical center. The experimental results illustrate the effectiveness of the developed system, consistently achieving F1-scores of 0.85 and 1.00 across 30 coding items. Registrar feedback highlights the system's reliability as a tool for assisting and auditing the abstraction. By presenting key registry items along the timeline of a patient's reports with accurate code predictions, the system improves the quality of registrar outcomes and reduces the labor resources and time required for data abstraction. Our study highlights advancements in cancer registry coding practices, demonstrating that the proposed hybrid weighted neural-symbolic cancer registry system is reliable and efficient for assisting cancer registrars in the coding workflow and contributing to clinical outcomes.

Unplanned Rehospitalisation due to Medication Harm following an Acute Myocardial Infarction.

INTRODUCTION: The contribution of medication harm to rehospitalisation and adverse patient outcomes after an acute myocardial infarction (AMI) needs exploration. Rehospitalisation is costly to both patients and the healthcare facility. Following an AMI, patients are at risk of medication harm as they are often older and have multiple comorbidities and polypharmacy. This study aimed to quantify and evaluate medication harm causing unplanned rehospitalisation after an AMI. METHODS: This was a retrospective cohort study of patients discharged from a quaternary hospital post-AMI. All rehospitalisations within 18 months were identified using medical record review and coding data. The primary outcome measure was medication harm rehospitalisation. Preventability, causality, and severity assessments of medication harm were conducted. RESULTS: A total of 1,564 patients experienced an AMI, and 415 (26.5%) were rehospitalised. Eighty-nine patients (5.7% of total population; 6.0% of those discharged) experienced a total of 101 medication harm events. Those with medication harm were older (p = 0.007) and had higher rates of heart failure (p = 0.005), chronic kidney disease (p = 0.046), chronic obstructive pulmonary disease (p = 0.037), and a prior history of ischaemic heart disease (p = 0.005). Gastrointestinal bleeding, acute kidney injury, and hypotension were the most common medication harm events. Forty percent of events were avoidable, and 84% were classed as "serious." Furosemide, antiplatelets, and angiotensin-converting enzyme inhibitors were the most commonly implicated medications. The median time to medication harm rehospitalisation was 79 days (interquartile range: 16-200 days). CONCLUSION: Medication harm causes unplanned rehospitalisation in 5.7% of all AMI patients (1 in 17 patients; 6.0% of those discharged). The majority of harm was serious and occurred within the first 200 days of discharge. This study highlights that measures to attenuate the risk of medication harm rehospitalisation are essential, including post-discharge medication management.

Association of semaglutide with reduced incidence and relapse of cannabis use disorder in real-world populations: a retrospective cohort study.

Cannabis is the most frequently used illicit drug in the United States with more than 45 million users of whom one-third suffer from a cannabis use disorder (CUD). Despite its high prevalence, there are currently no FDA-approved medications for CUD. Patients treated with semaglutide, a glucagon-like peptide-1 receptor agonist (GLP-1RA) approved for treating type 2 diabetes (T2D) and for weight management have reported reduced desire to drink and smoke. Preclinical studies have shown that semaglutide decreased nicotine and alcohol consumption. Preclinical and preliminary clinical evidence of semaglutide's potential beneficial effects on various substance use disorders led us to evaluate if it pertained to CUD. In this retrospective cohort study of electronic health records (EHRs) from the TriNetX Analytics Network, a global federated health research network of approximately 105.3 million patients from 61 large healthcare organizations in the US, we aimed to assess the associations of semaglutide with both incident and recurrent CUD diagnosis compared to non-GLP-1RA anti-obesity or anti-diabetes medications. Hazard ratio (HR) and 95% confidence intervals (CI) of incident and recurrent CUD were calculated for 12-month follow-up by comparing propensity-score matched patient cohorts. The study population included 85,223 patients with obesity who were prescribed semaglutide or non-GLP-1RA anti-obesity medications, with the findings replicated in 596,045 patients with T2D. In patients with obesity (mean age 51.3 years, 65.6% women), semaglutide compared with non-GLP-1RA anti-obesity medications was associated with lower risk for incident CUD in patients with no prior history CUD (HR: 0.56, 95% CI: 0.42-0.75), and recurrent CUD diagnosis in patients with a prior history CUD (HR: 0.62, 95% CI: 0.46-0.84). Consistent reductions were seen for patients stratified by gender, age group, race and in patients with and without T2D. Similar findings were replicated in the study population with T2D when comparing semaglutide with non-GLP-1RA anti-diabetes medications for incident CUD (HR: 0.40, 95% CI: 0.29-0.56) and recurrent CUD (HR: 0.66, 95% CI: 0.42-1.03). While these findings provide preliminary evidence of the potential benefit of semaglutide in CUD in real-world populations, further preclinical studies are warranted to understand the underlying mechanism and randomized clinical trials are needed to support its use clinically for CUD.

Effects of a culturally informed model of care for Aboriginal and Torres Strait Islander patients with acute coronary syndrome in a tertiary hospital in Australia: a pre-post, quasi-experimental, interventional study.

BACKGROUND: Aboriginal and Torres Strait Islander (Indigenous) peoples with cardiac disease in Australia have worse outcomes than non-Indigenous people with cardiac disease. We hypothesised that the implementation of a culturally informed model of care for Indigenous patients hospitalised with acute coronary syndrome (ACS) would improve their clinical outcomes. METHODS: For this pre-post, quasi-experimental, interventional study, cohorts of Indigenous patients before and after the implementation of a model of care were compared. The novel, culturally informed, multidisciplinary-team model of care was a local programme of care developed to reduce morbidity and mortality from cardiac conditions among Indigenous Australians. All index admissions in the 24-month pre-implementation period (Jan 1 2013, to Dec 31, 2014) were analysed, as were all index admissions in the 12-month post-implementation period (Oct 1, 2015, to Sept 30, 2016). Comparisons were also made with non-Indigenous cohorts in the same timeframes. Admissions were excluded if the patient did not survive to hospital discharge. The study was conducted at Princess Alexandra Hospital, a tertiary hospital in metropolitan Brisbane (QLD, Australia). Data on presentation, comorbidities, investigations, treatment, and for outcomes were manually collected from a consolidated clinical information application. Mortality data were obtained from the Queensland Registry of Births, Deaths, and Marriages. The primary outcome was a composite of death, acute myocardial infarction, unplanned revascularisation, and cardiac readmission at 90 days after index admission, assessed in all patients. FINDINGS: The Indigenous cohorts included 199 patients admitted with ACS before the model of care was implemented (85 [43%] were female and 114 [57%] were male) and 119 admitted post-implementation (62 [52%] were female and 57 [48%] were male). The non-Indigenous cohorts included 440 patients with ACS before the model of care was implemented (140 [32%] were female and 300 [68%] were male) and 467 admitted post-implementation (143 [31%] were female and 324 [69%] were male). Compared with the pre-implementation group, Indigenous patients admitted post-implementation had a significant reduction in the primary outcome (67 [34%] of 199 vs 24 [20%] of 119; hazard ratio 0·60, 95% CI 0·40-0·90; p=0·012), which was driven by a reduction in unplanned cardiac readmissions (64 [32%] of 199 vs 21 [18%] of 119; 0·55, 0·35-0·85; p=0·0060). There was no significant change in non-Indigenous patients between the pre-implementation and post-implementation timeframes in the composite endpoint at 90 days (81 [18%] of 440 vs 93 [20%] of 467; 1·08, 0·83-1·41; p=0·54). Pre-implementation, there was significantly more incidence of the primary outcome in Indigenous patients than non-Indigenous patients (p<0·0001), with no significant difference in the post-implementation period (p=0·92). INTERPRETATION: Clinical outcomes for Indigenous patients admitted to a tertiary hospital in Australia improved after implementation of a culturally informed model of care, with a reduction in the disparity in incidence of primary endpoints that existed between Indigenous and non-Indigenous patients before implementation. FUNDING: Queensland Department of Health Aboriginal and Torres Strait Islander Health Division (now First Nations Health Office).

Lisocabtagene maraleucel for treatment of relapsed and refractory primary mediastinal large B-cell lymphoma in an adolescent patient.

The safety and efficacy of CAR T-cell therapy are unknown in pediatric and adolescent patients with relapsed or refractory primary mediastinal large B-cell lymphoma (R/R PMBCL) which is associated with dismal prognosis. Here, we present a case report of a 16-year-old patient with R/R PMBCL treated with lisocabtagene maraleucel including correlative studies. Patient achieved complete response at 6 months without cytokine release syndrome and immune effector cell-associated neurotoxicity syndrome. She only experienced mild cytopenias, requiring filgrastim once. This report highlights the safety and efficacy of lisocabtagene maraleucel in this population, warranting prospective studies to improve clinical outcomes.

A web-based tool for real-time adequacy assessment of kidney biopsies.

The escalating incidence of kidney biopsies providing insufficient tissue for diagnosis poses a dual challenge, straining the healthcare system and jeopardizing patients who may require rebiopsy or face the prospect of an inaccurate diagnosis due to an unsampled disease. Here, we introduce a web-based tool that can provide real-time, quantitative assessment of kidney biopsy adequacy directly from photographs taken with a smartphone camera. The software tool was developed using a deep learning-driven automated segmentation technique, trained on a dataset comprising nephropathologist-confirmed annotations of the kidney cortex on digital biopsy images. Our framework demonstrated favorable performance in segmenting the cortex via 5-fold cross-validation (Dice coefficient: 0.788±0.130) (n=100). Offering a bedside tool for kidney biopsy adequacy assessment has the potential to provide real-time guidance to the physicians performing medical kidney biopsies, reducing the necessity for re-biopsies. Our tool can be accessed through our web-based platform: http://www.biopsyadequacy.org.

Safety signal detection with control of latent factors.

Postmarket drug safety database like vaccine adverse event reporting system (VAERS) collect thousands of spontaneous reports annually, with each report recording occurrences of any adverse events (AEs) and use of vaccines. We hope to identify signal vaccine-AE pairs, for which certain vaccines are statistically associated with certain adverse events (AE), using such data. Thus, the outcomes of interest are multiple AEs, which are binary outcomes and could be correlated because they might share certain latent factors; and the primary covariates are vaccines. Appropriately accounting for the complex correlation among AEs could improve the sensitivity and specificity of identifying signal vaccine-AE pairs. We propose a two-step approach in which we first estimate the shared latent factors among AEs using a working multivariate logistic regression model, and then use univariate logistic regression model to examine the vaccine-AE associations after controlling for the latent factors. Our simulation studies show that this approach outperforms current approaches in terms of sensitivity and specificity. We apply our approach in analyzing VAERS data and report our findings.