2,426 research outputs found
Does Group Size Matter? The Impact of Reciprocity on Giving in Local Faith Communities
We compare and contrast how group size affects the internal structure & relational dynamics of religious communities, ranging from small religious congregations to megachurches (in American society). Classic anthropological economic and evolutionary theory holds that reciprocity, particularly altruistic generalized reciprocity, is most likely to strongly influence small groups, especially kinship-based groups. In the case of non-kin groups, studies of behavior mimicking kin altruism have found that all forms of reciprocity, including extreme giving and high-cost behaviors, are most likely to be found in small social groups with tight bonds, particularly those with shared religious beliefs. In the case of larger groups and individuals who are less tightly bound, a different set of factors may be associated with giving and other forms of group interaction. Distribution and redistribution of resources through a mediator, leader or bureaucracy is often more typical of large-scale groups with less direct contact between giver and receiver. How does this dynamic apply to modern religious groups, such as megachurches? In this paper, we propose a conceptual framework for analyzing religious communities, ranging from small-scale and larger-scale churches. Based on theoretical concepts drawn from both Anthropology and Sociology, we indicate that as the social group size increases, the nature of giving, broadly defined, is altered, becoming less direct and less kin-like, and more outwardly focused. By contrast, smaller groups are more likely to focus on interior, direct, reciprocal giving and kin-like altruism on an ongoing basis. Because giving is important to individual happiness as well as to religious community identity, what lessons are there to be learned about best practices in how religious communities organize giving
Heterogeneity in the Association Between the Presence of Coronary Artery Calcium and Cardiovascular Events: A Machine Learning Approach in the MESA Study
Background: Coronary artery calcium (CAC) has been widely recognized as an important predictor of cardiovascular disease (CVD). Given the finite resources, it is important to identify individuals who would receive the most benefit from detecting positive CAC by screening. However, the evidence is limited as to whether the burden of positive CAC on CVD differs by multi-dimensional individual characteristics. We sought to investigate the heterogeneity in the association between positive coronary artery calcium (CAC) and incident cardiovascular disease (CVD). Methods: This cohort study included adults aged ≥45 years free of cardiovascular disease from the Multi-Ethnic Study of Atherosclerosis. After propensity score matching in a 1:1 ratio, we applied a machine-learning causal forest model to (i) evaluate the heterogeneity in the association between positive CAC and incident CVD and (ii) predict the increase in CVD risk at 10-year when CAC>0 (vs. CAC=0) at the individual level. We then compared the estimated increase in CVD risk when CAC>0 to the absolute 10-year atherosclerotic CVD (ASCVD) risk calculated by the 2013 ACC/AHA pooled cohort equations. Results: Across 3, 328 adults in our propensity score-matched analysis, our causal forest model showed the heterogeneity in the association between CAC>0 and incident CVD. We found a dose-response relationship of the estimated increase in CVD risk when CAC>0 with higher 10-year ASCVD risk. Almost all individuals (2293/2428 [94.4%]) with borderline or higher ASCVD risk showed ≥2.5% increase in CVD risk when CAC>0. Even among 900 adults with low ASCVD risk, 689 (69.2%) showed ≥2.5% increase in CVD risk when CAC>0; these individuals were more likely to be male, Hispanic, and have unfavorable CVD risk factors than others. Conclusions: The expected increases in CVD risk when CAC>0 were heterogeneous across individuals. Moreover, nearly 70% of people with low ASCVD risk showed a large increase in CVD risk when CAC>0, highlighting the need for CAC screening among such low-risk individuals. Future studies are needed to assess whether targeting individuals for CAC measurements based on not only the absolute ASCVD risk but also the expected increase in CVD risk when CAC>0 improves cardiovascular outcomes
Association of Intensive Blood Pressure Control and Living Arrangement on Cardiovascular Outcomes by Race
Importance: Living alone, a key proxy of social isolation, is a risk factor for cardiovascular disease. In addition, Black race is associated with less optimal blood pressure (BP) control than in other racial or ethnic groups. However, it is not clear whether living arrangement status modifies the beneficial effects of intensive BP control on reduction in cardiovascular events among Black individuals. Objective: To examine whether the association of intensive BP control with cardiovascular events differs by living arrangement among Black individuals and non-Black individuals (eg, individuals who identified as Alaskan Native, American Indian, Asian, Native Hawaiian, Pacific Islander, White, or other) in the Systolic Blood Pressure Intervention Trial (SPRINT). Design, Setting, and Participants: This secondary analysis incorporated data from SPRINT, a multicenter study of individuals with increased risk for cardiovascular disease and free of diabetes, enrolled at 102 clinical sites in the United States between November 2010 and March 2013. Race and living arrangement (ie, living alone or living with others) were self-reported. Data were collected between November 2010 and March 2013 and analyzed from January 2021 to October 2021. Exposures: The SPRINT participants were randomized to a systolic BP target of either less than 120 mm Hg (intensive treatment group) or less than 140 mm Hg (standard treatment group). Antihypertensive medications were adjusted to achieve the targets in each group. Main Outcomes and Measures: Cox proportional hazards model was used to investigate the association of intensive treatment with the incident composite cardiovascular outcome (by August 20, 2015) according to living arrangement among Black individuals and other individuals. Transportability formula was applied to generalize the SPRINT findings to hypothetical external populations by varying the proportion of Black race and living arrangement status. Results: Among the 9342 total participants, the mean (SD) age was 67.9 (9.4) years; 2793 participants [30%] were Black, 2714 [29%] lived alone, and 3320 participants (35.5%) were female. Over a median (IQR) follow-up of 3.22 (2.74-3.76) years, the primary composite cardiovascular outcome was observed in 67 of 1001 Black individuals living alone (6.7%), 76 of 1792 Black individuals living with others (4.2%), 108 of 1713 non-Black individuals living alone (6.3%), and 311 of 4836 non-Black individuals living with others (6.4%). The intensive treatment group showed a significantly lower rate of the composite cardiovascular outcome than the standard treatment group among Black individuals living with others (hazard ratio [HR], 0.53 [95% CI, 0.33-0.85]) but not among those living alone (HR, 1.07 [95% CI, 0.66-1.73]; P for interaction = .04). The association was observed among individuals who were not Black regardless of living arrangement status. Using transportability, we found a smaller or null association between intensive control and cardiovascular outcomes among hypothetical populations of 60% Black individuals or more and 60% or more of individuals living alone. Conclusions and Relevance: Intensive BP control was associated with a lower rate of cardiovascular events among Black individuals living with others and individuals who were not Black but not among Black individuals living alone. Trial Registration: ClinicalTrials.gov Identifier: NCT01206062
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Mitral Regurgitation in Female Patients: Sex Differences and Disparities
Mitral regurgitation is the most common valvular disease, particularly in older adults. Recent literature has consistently supported that there are significant differences in mitral regurgitation outcomes between male and female patients and that this is likely multifactorial. Numerous sex differences in anatomy and pathophysiology may play a role in delayed diagnoses, referrals, and treatments for female patients. Despite the recognition of these discrepancies in the literature, many guidelines that steer clinical care do not incorporate these factors into society recommendations. Identifying and validating sex-specific diagnostic parameters and increasing the representation of female patients in trials of new mitral regurgitation treatment modalities are key factors in improving outcomes for female patients
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Missing Values in Longitudinal Proteome Dynamics Studies: Making a Case for Data Multiple Imputation.
Temporal proteomics data sets are often confounded by the challenges of missing values. These missing data points, in a time-series context, can lead to fluctuations in measurements or the omission of critical events, thus hindering the ability to fully comprehend the underlying biomedical processes. We introduce a Data Multiple Imputation (DMI) pipeline designed to address this challenge in temporal data set turnover rate quantifications, enabling robust downstream analysis to gain novel discoveries. To demonstrate its utility and generalizability, we applied this pipeline to two use cases: a murine cardiac temporal proteomics data set and a human plasma temporal proteomics data set, both aimed at examining protein turnover rates. This DMI pipeline significantly enhanced the detection of protein turnover rate in both data sets, and furthermore, the imputed data sets captured new representation of proteins, leading to an augmented view of biological pathways, protein complex dynamics, as well as biomarker-disease associations. Importantly, DMI exhibited superior performance in benchmark data sets compared to single imputation methods (DSI). In summary, we have demonstrated that this DMI pipeline is effective at overcoming challenges introduced by missing values in temporal proteome dynamics studies
Robust Quantification of Percent Emphysema on CT via Domain Attention: the Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study
Robust quantification of pulmonary emphysema on computed tomography (CT)
remains challenging for large-scale research studies that involve scans from
different scanner types and for translation to clinical scans. Existing studies
have explored several directions to tackle this challenge, including density
correction, noise filtering, regression, hidden Markov measure field (HMMF)
model-based segmentation, and volume-adjusted lung density. Despite some
promising results, previous studies either required a tedious workflow or
limited opportunities for downstream emphysema subtyping, limiting efficient
adaptation on a large-scale study. To alleviate this dilemma, we developed an
end-to-end deep learning framework based on an existing HMMF segmentation
framework. We first demonstrate that a regular UNet cannot replicate the
existing HMMF results because of the lack of scanner priors. We then design a
novel domain attention block to fuse image feature with quantitative scanner
priors which significantly improves the results.Comment: 5 pages, 5 figures. Accepted to IEEE International Symposium on
Biomedical Imaging 2024 (ISBI 2024). Camera-ready versio
Statin use and risk of developing diabetes: results from the Diabetes Prevention Program
Objective
Several clinical trials of cardiovascular disease prevention with statins have reported increased risk of type 2 diabetes (T2DM) with statin therapy. However, participants in these studies were at relatively low risk for diabetes. Further, diabetes was often based on self-report and was not the primary outcome. It is unknown whether statins similarly modify diabetes risk in higher risk populations.
Research design and methods
During the Diabetes Prevention Program Outcomes Study (n=3234), the long-term follow-up to a randomized clinical trial of interventions to prevent T2DM, incident diabetes was assessed by annual 75 g oral glucose tolerance testing and semiannual fasting glucose. Lipid profile was measured annually, with statin treatment determined by a participant’s own physician outside of the protocol. Statin use was assessed at baseline and semiannual visits.
Results
At 10 years, the cumulative incidence of statin initiation prior to diabetes diagnosis was 33%–37% among the randomized treatment groups (p=0.36). Statin use was associated with greater diabetes risk irrespective of treatment group, with pooled HR (95% CI) for incident diabetes of 1.36 (1.17 to 1.58). This risk was not materially altered by adjustment for baseline diabetes risk factors and potential confounders related to indications for statin therapy.
Conclusions
In this population at high risk for diabetes, we observed significantly higher rates of diabetes with statin therapy in all three treatment groups. Confounding by indication for statin use does not appear to explain this relationship. The effect of statins to increase diabetes risk appears to extend to populations at high risk for diabetes.
Trial registration number
NCT00038727; Results
Acculturation is associated with left ventricular mass in a multiethnic sample: the Multi-Ethnic Study of Atherosclerosis
BackgroundAcculturation involves stress-related processes and health behavioral changes, which may have an effect on left ventricular (LV) mass, a risk factor for cardiovascular disease (CVD). We examined the relationship between acculturation and LV mass in a multiethnic cohort of White, African-American, Hispanic and Chinese subjects.MethodsCardiac magnetic resonance assessment was available for 5004 men and women, free of clinical CVD at baseline. Left ventricular mass index was evaluated as LV mass indexed by body surface area. Acculturation was characterized based on language spoken at home, place of birth and length of stay in the United States (U.S.), and a summary acculturation score ranging from 0 = least acculturated to 5 = most acculturated. Mean LV mass index adjusted for traditional CVD risk factors was compared across acculturation levels.ResultsUnadjusted mean LV mass index was 78.0 ± 16.3 g/m(2). In adjusted analyses, speaking exclusively English at home compared to non-English language was associated with higher LV mass index (81.3 ± 0.4 g/m(2) vs 79.9 ± 0.5 g/m(2), p = 0.02). Among foreign-born participants, having lived in the U.S. for ≥ 20 years compared to < 10 years was associated with greater LV mass index (81.6 ± 0.7 g/m(2) vs 79.5 ± 1.1 g/m(2), p = 0.02). Compared to those with the lowest acculturation score, those with the highest score had greater LV mass index (78.9 ± 1.1 g/m(2) vs 81.1 ± 0.4 g/m(2), p = 0.002). There was heterogeneity in which measure of acculturation was associated with LV mass index across ethnic groups.ConclusionsGreater acculturation is associated with increased LV mass index in this multiethnic cohort. Acculturation may involve stress-related processes as well as behavioral changes with a negative effect on cardiovascular health
Lifestyle and metformin interventions have a durable effect to lower CRP and tPA levels in the diabetes prevention program except in those who develop diabetes.
OBJECTIVE: We evaluate whether lifestyle and metformin interventions used to prevent diabetes have durable effects on markers of inflammation and coagulation and whether the effects are influenced by the development of diabetes.
RESEARCH DESIGN AND METHODS: The Diabetes Prevention Program was a controlled clinical trial of 3,234 subjects at high risk for diabetes who were randomized to lifestyle, metformin, or placebo interventions for 3.4 years. Diabetes was diagnosed semiannually by fasting glucose and annually by oral glucose tolerance testing. In addition to baseline testing, anthropometry was performed every 6 months; fasting insulin yearly; and hs-CRP, tissue plasminogen activator (tPA), and fibrinogen at 1 year and end of study (EOS).
RESULTS: CRP and tPA levels were unchanged in the placebo group but fell in the lifestyle and metformin groups at 1 year and remained lower at EOS. These reductions were not seen in those who developed diabetes over the course of the study despite intervention. Fibrinogen was lower at 1 year in the lifestyle group. Differences in weight and weight change explained most of the influence of diabetes on the CRP response in the lifestyle group, but only partly in the placebo and metformin groups. Weight, insulin sensitivity, and hyperglycemia differences each accounted for the influence of diabetes on the tPA response.
CONCLUSIONS: Lifestyle and metformin interventions have durable effects to lower hs-CRP and tPA. Incident diabetes prevented these improvements, and this was accounted for by differences in weight, insulin resistance, and glucose levels
Building an Ethical and Trustworthy Biomedical AI Ecosystem for the Translational and Clinical Integration of Foundation Models
Foundation Models (FMs) are gaining increasing attention in the biomedical artificial intelligence (AI) ecosystem due to their ability to represent and contextualize multimodal biomedical data. These capabilities make FMs a valuable tool for a variety of tasks, including biomedical reasoning, hypothesis generation, and interpreting complex imaging data. In this review paper, we address the unique challenges associated with establishing an ethical and trustworthy biomedical AI ecosystem, with a particular focus on the development of FMs and their downstream applications. We explore strategies that can be implemented throughout the biomedical AI pipeline to effectively tackle these challenges, ensuring that these FMs are translated responsibly into clinical and translational settings. Additionally, we emphasize the importance of key stewardship and co-design principles that not only ensure robust regulation but also guarantee that the interests of all stakeholders-especially those involved in or affected by these clinical and translational applications-are adequately represented. We aim to empower the biomedical AI community to harness these models responsibly and effectively. As we navigate this exciting frontier, our collective commitment to ethical stewardship, co-design, and responsible translation will be instrumental in ensuring that the evolution of FMs truly enhances patient care and medical decision-making, ultimately leading to a more equitable and trustworthy biomedical AI ecosystem
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