UC Irvine Department of Medicine

Aberration of the "gut-liver axis" contributes to the development and progression of metabolic dysfunction-associated steatotic liver disease (MASLD). Here, we use multi-omics to analyze the gut microbiota composition and metabolic profile of patients with type-2 diabetes mellitus (T2DM). T2DM patients were screened for liver disease by blood tests, ultrasound, and liver stiffness measurements. Stool microbiota was analyzed by 16S rRNA gene sequencing; metabolomic profiling by Nuclear Magnetic Resonance spectroscopy and Ultra-High Performance-Mass Spectrometry. Microbiome and metabolic signatures were analyzed in the whole cohort and in matched subsets to identify signatures specific for steatosis (MASLD±) or fibrosis (Fibrosis±). Gut permeability was assessed in-vitro using monolayers of MDCK cells and trans-epithelial electric resistance (TEER). Cytokine profile was assessed in serum and stools.Overall, 285 patients were enrolled: 255 serum, 252 urine and 97 stool samples were analyzed. Anaeroplasma and Escherichia/Shigella ASVs were higher, while Butyricicoccus ASVs were lower in those with normal liver. In MASLD±, Butyricicoccus ASV was significantly higher in those with steatosis. In the Fibrosis±, Butyricicoccus ASV was significantly lower in those with fibrosis. Glycochenodeoxycholic acid-3-sulfate (G-UDCA-3S) appeared to be higher in MASLD with fibrosis. Fecal water from patients with MASLD and fibrosis caused the greatest drop in the TEER vs those with normal liver; this was reversed with protease inhibitors. Finally, fecal IL-13 was lower in MASLD with fibrosis. We identified microbiome signatures which were specific for steatosis and fibrosis and independent of other metabolic risk factors. Moreover, we conclude that protease-related gut permeability plays a role in those MASLD patients with fibrosis, and that disease progression is linked to a gut-liver axis which is at least partially independent of T2DM.

OBJECTIVE: Many studies support the notion that polygenic risk scores (PRS) improve risk prediction for coronary heart disease (CHD) beyond conventional risk factors. However, PRS are not yet considered risk-enhancing factor in guidelines. Our objective was to determine the predictive performance of a commercially available PRS (CARDIO inCode-Score®) compared with the Pooled Cohorts Equations (PCE) in a contemporary, multi-ethnic cohort. METHODS: Participants (n = 63,070; 67 % female; 18 % non-European) without prior CHD were followed from 2007 through 12/31/2022. The association between the PRS and incident CHD was assessed using Cox regression adjusting for genetic ancestry and risk factors. Event rates were estimated by categories of PCE and by low/intermediate/high genetic risk within PCE categories; risk discrimination and net reclassification improvement (NRI) were also assessed. RESULTS: There were 3,289 incident CHD events during 14 years of follow-up. Adjusted hazard ratio (aHR) for incident CHD per 1 SD increase in PRS was 1.18 (95 % CI:1.14-1.22), and the aHR for the upper vs lower quintile of the PRS was 1.66 (95 % CI:1.49-1.86). The association was consistent in both sexes, in European participants compared with all minority groups combined and was strongest in the first 5 years of follow-up. The increase in the C-statistic was 0.004 (0.747 vs. 0.751; p < 0.0001); the NRI was 2.4 (0.9-3.8) for the entire cohort and 9.7 (7.5-12.0) for intermediate PCE risk individuals. After incorporating high genetic risk, a further 10 percent of participants at borderline/intermediate PCE risk would be candidates for statin therapy. CONCLUSION: Inclusion of polygenic risk improved identification of primary prevention individuals who may benefit from more intensive risk factor modification.

Introduction: Financial toxicity has negative implications for patient well-being and health outcomes. There is a gap in understanding financial toxicity for patients undergoing palliative radiotherapy (RT). Methods: A review of patients treated with palliative RT was conducted from January 2021 to December 2022. The FACIT-COST (COST) was measured (higher scores implying better financial well-being). Financial toxicity was graded according to previously suggested cutoffs: Grade 0 (score ≥26), Grade 1 (14-25), Grade 2 (1-13), and Grade 3 (0). FACIT-TS-G was used for treatment satisfaction, and EORTC QLQ-C30 was assessed for global health status and functional scales. Results: 53 patients were identified. Median COST was 25 (range 0-44), 49% had Grade 0 financial toxicity, 32% Grade 1, 15% Grade 2, and 4% Grade 3. Overall, cancer caused financial hardship among 45%. Higher COST was weakly associated with higher global health status/Quality of Life (QoL), physical functioning, role functioning, and cognitive functioning; moderately associated with higher social functioning; and strongly associated with improved emotional functioning. Higher income or Medicare or private coverage (rather than Medicaid) was associated with less financial toxicity, whereas an underrepresented minority background or a non-English language preference was associated with greater financial toxicity. A multivariate model found that higher area income (HR .80, P = .007) and higher cognitive functioning (HR .96, P = .01) were significantly associated with financial toxicity. Conclusions: Financial toxicity was seen in approximately half of patients receiving palliative RT. The highest risk groups were those with lower income and lower cognitive functioning. This study supports the measurement of financial toxicity by clinicians.

UNLABELLED: High cardiorespiratory fitness (CRF) is associated with decreased mortality in people with pre-diabetes (pre-DM) and diabetes mellitus (DM); however, the degree to which CRF attenuates the risk of cardiovascular disease (CVD)-related and all-cause mortality is unclear. STUDY OBJECTIVE: We examined the impact of CRF status on CVD-related morbidity and all-cause mortality in non-DM, Pre-DM, and DM populations. DESIGN AND SETTING: 13,968 adults from the Third US National Health and Nutrition Examination Survey (NHANES III) were stratified into non-DM, pre-DM, or DM groups based on HbA1c levels. VO2Max was calculated using the Fitness Registry and Importance of Exercise: A National Database (FRIEND) equation. PARTICIPANTS: Participants were categorized into tertiles of VO2Max; first VO2Max tertile was the lowest VO2Max and third VO2Max tertile was the highest. MAIN OUTCOME MEASURES: Cox regression was used to analyze the relationship between glycemic levels, VO2Max, and CVD-related and all-cause mortality. RESULTS: Those with DM in the highest fitness tertile had CVD (HR 0.13; 95 % CI 0.06, 0.27; p < 0.0001) and all cause (HR 0.28; 95 % CI 0.21, 0.38; p < 0.0001) mortality rates as low or lower than those with pre-DM (CVD HR 1.02; 95 % CI 0.78, 1.33 p < 0.892; all cause HR 0.96; 95 % CI 0.83, 1.12; p < 0.5496) or non-DM (CVD HR 0.65; 95 % CI 0.52, 0.80; p < 0.0001; all cause HR 0.61; 95 % CI 0.55, 0.68; p < 0.0001) at lower fitness levels. Regardless of DM status, there was lower all-cause mortality with higher CRF levels. CONCLUSIONS: Higher fitness levels in DM individuals are associated with total and CVD mortality rates as low or lower than those without DM with lower fitness.

OBJECTIVE: Nursing home residents may be particularly vulnerable to coronavirus disease 2019 (COVID-19). Therefore, a question is when and how often nursing homes should test staff for COVID-19 and how this may change as severe acute respiratory coronavirus virus 2 (SARS-CoV-2) evolves. DESIGN: We developed an agent-based model representing a typical nursing home, COVID-19 spread, and its health and economic outcomes to determine the clinical and economic value of various screening and isolation strategies and how it may change under various circumstances. RESULTS: Under winter 2023-2024 SARS-CoV-2 omicron variant conditions, symptom-based antigen testing averted 4.5 COVID-19 cases compared to no testing, saving $191 in direct medical costs. Testing implementation costs far outweighed these savings, resulting in net costs of $990 from the Centers for Medicare & Medicaid Services perspective, $1,545 from the third-party payer perspective, and $57,155 from the societal perspective. Testing did not return sufficient positive health effects to make it cost-effective [$50,000 per quality-adjusted life-year (QALY) threshold], but it exceeded this threshold in ≥59% of simulation trials. Testing remained cost-ineffective when routinely testing staff and varying face mask compliance, vaccine efficacy, and booster coverage. However, all antigen testing strategies became cost-effective (≤$31,906 per QALY) or cost saving (saving ≤$18,372) when the severe outcome risk was ≥3 times higher than that of current omicron variants. CONCLUSIONS: SARS-CoV-2 testing costs outweighed benefits under winter 2023-2024 conditions; however, testing became cost-effective with increasingly severe clinical outcomes. Cost-effectiveness can change as the epidemic evolves because it depends on clinical severity and other intervention use. Thus, nursing home administrators and policy makers should monitor and evaluate viral virulence and other interventions over time.

OBJECTIVE: Lipoprotein(a) [Lp(a)] is an atherogenic and prothrombotic lipoprotein associated with atherosclerotic cardiovascular disease (ASCVD). We assessed the association between regular aspirin use and ASCVD mortality among individuals with versus without elevated Lp(a) in a nationally representative US cohort. METHODS: Eligible participants were aged 40-70 years without clinical ASCVD, reported on aspirin use, and had Lp(a) measurements from the Third National Health and Nutrition Examination Survey (NHANES III, 1988-1994), the only cycle of this nationally representative US cohort to measure Lp(a). Regular aspirin use was defined as taking aspirin ≥30 times in the previous month. Using NHANES III linked mortality records and weighted Cox proportional hazards regression, the association between regular aspirin use and ASCVD mortality was observed in those with and without elevated Lp(a) (≥50 versus <50 mg/dL) over a median 26-year follow-up. RESULTS: Among 2,990 persons meeting inclusion criteria (∼73 million US adults), the mean age was 50 years, 86% were non-Hispanic White, 9% were non-Hispanic Black, 53% were female, and 7% reported regular aspirin use. The median Lp(a) was 14 mg/dL and the proportion with elevated Lp(a) was similar among those with versus without regular aspirin use (15.1% versus 21.9%, p = 0.16). Among individuals with elevated Lp(a), the incidence of ASCVD mortality per 1,000 person-years was lower for those with versus without regular aspirin use (1.2, 95% CI: 0.1-2.3 versus 3.9, 95% CI: 2.8-4.9). In multivariable modeling, regular aspirin use was associated with a 52% lower risk of ASCVD mortality among individuals with elevated Lp(a) (HR=0.48, 95% CI: 0.28-0.83), but not for those without elevated Lp(a) (HR=1.01, 95% CI: 0.81-1.25; p-interaction=0.001). CONCLUSION: Regular aspirin use was associated with significantly lower ASCVD mortality in adults without clinical ASCVD who had elevated Lp(a). These findings may have clinical and public health implications for aspirin utilization in primary prevention.

Internal medicine physicians are increasingly interacting with systems that implement artificial intelligence (AI) and machine learning (ML) technologies. Some physicians and health care systems are even developing their own AI models, both within and outside of electronic health record (EHR) systems. These technologies have various applications throughout the provision of health care, such as clinical documentation, diagnostic image processing, and clinical decision support. With the growing availability of vast amounts of patient data and unprecedented levels of clinician burnout, the proliferation of these technologies is cautiously welcomed by some physicians. Others think it presents challenges to the patient-physician relationship and the professional integrity of physicians. These dispositions are understandable, given the "black box" nature of some AI models, for which specifications and development methods can be closely guarded or proprietary, along with the relative lagging or absence of appropriate regulatory scrutiny and validation. This American College of Physicians (ACP) position paper describes the College's foundational positions and recommendations regarding the use of AI- and ML-enabled tools and systems in the provision of health care. Many of the College's positions and recommendations, such as those related to patient-centeredness, privacy, and transparency, are founded on principles in the ACP Ethics Manual. They are also derived from considerations for the clinical safety and effectiveness of the tools as well as their potential consequences regarding health disparities. The College calls for more research on the clinical and ethical implications of these technologies and their effects on patient health and well-being.

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Purines are the building blocks of DNA/RNA, energy substrates, and cofactors. Purine metabolites, including ATP, GTP, NADH, and coenzyme A, are essential molecules in diverse biological processes such as energy metabolism, signal transduction, and enzyme activity. When purine levels increase, excess purines are either recycled to synthesize purine metabolites or catabolized to the end product uric acid. Purine catabolism increases during states of low oxygen tension (hypoxia and ischemia), but this metabolic pathway is incompletely understood in the context of histotoxic hypoxia (i.e., inhibition of oxygen utilization despite normal oxygen tension). In rabbits exposed to cyanide-a classical histotoxic hypoxia agent-we demonstrated significant increases in several concordant metabolites in the purine catabolic pathway (including plasma levels of uric acid, xanthosine, xanthine, hypoxanthine, and inosine) via mass spectrometry-based metabolite profiling. Pharmacological inhibition of the purine catabolic pathway with oxypurinol mitigated the deleterious effects of cyanide on skeletal muscle cytochrome c oxidase redox state, measured by non-invasive diffuse optical spectroscopy. Finally, plasma uric acid levels correlated strongly with those of lactic acid, an established clinical biomarker of cyanide exposure, in addition to a tissue biomarker of cyanide exposure (skeletal muscle cytochrome c oxidase redox state). Cumulatively, these findings not only shed light on the in vivo role(s) of cyanide but also have implications in the field of medical countermeasure (MCM) development.

BACKGROUND: Inadequate and inequitable access to quality behavioral health services and high costs within the mental health systems are long-standing problems. System-level (e.g., fee-for-service payment model, lack of a universal payor) and individual factors (e.g., lack of knowledge of existing resources) contribute to difficulties in accessing resources and services. Patients are underserved in County behavioral health systems in the United States. Orange Countys (California) Behavioral Health System Transformation project sought to improve access by addressing two parts of their system: developing a template for value-based contracts that promote payor-agnostic care (Part 1); developing a digital platform to support resource navigation (Part 2). Our aim was to evaluate facilitators of and barriers to each of these system changes. METHODS: We collected interview data from County or health care agency leaders, contracted partners, and community stakeholders. Themes were informed by the Consolidated Framework for Implementation Research. RESULTS: Five themes were identified related to behavioral health system transformation, including 1) aligning goals and values, 2) addressing fit, 3) fostering engagement and partnership, 4) being aware of implementation contexts, and 5) promoting communication. A lack of fit into incentive structures and changing state guidelines and priorities were barriers to contract development. Involving diverse communities to inform design and content facilitated the process of developing digital tools. CONCLUSIONS: The study highlights the multifaceted factors that help facilitate or hinder behavioral health system transformation, such as the need for addressing systematic and process behaviors, leveraging the knowledge of leadership and community stakeholders, fostering collaboration, and adapting to implementation contexts.