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Assessing the relationship between HIV-related stigma and antiretroviral treatment interruption among older and younger adults in Kenya
Get PDFDespite identified negative associations between HIV-related stigma and treatment adherence and viral suppression, little research in Kenya has been conducted to unpack specific aspects of HIV-related stigma on these health outcomes or to understand differences by age. We aimed to identify relationships between internalized stigma, healthcare-related enacted stigma, and healthcare-related anticipated stigma and HIV treatment interruption, and examine the differences in association between indicators of HIV-related stigma and treatment interruption by age.
Data were obtained from The People Living with HIV (PLWH) Stigma Index data in Kenya. We included PLWH from rural and urban settings in 8 regions across Kenya from February to March 2021. The primary outcome was HIV treatment interruption defined as having interrupted or stopped HIV treatment in the last 12 months. Composite scores for the three primary exposures: internalized, healthcare-related anticipated, and healthcare-related experienced stigma were calculated as the sum of responses to stigma-specific items. Age was treated as an effect measure modifier and was categorized into 3 groups: 18-34,35-49, and 50+ years old. Poisson regression analyses with robust variance estimation for the relationship between the three HIV-related stigma indicators and antiretroviral treatment interruption were conducted.
Over 20% PLHIV in Kenya experienced a treatment interruption. In the overall population, having moderate (aPR = 2.15; 95% CI: 1.72, 2.68) and high (aPR = 2.62; 95% CI: 2.08, 3.30) levels of internalized stigma, healthcare-related anticipated stigma (aPR: = 2.10; 95% CI: 1.67, 2.62), and healthcare-related experienced stigma (aPR: = 2.22; 95% CI: 1.84, 2.68) was positively associated with treatment interruption. When stratified by age, all three stigma indicators were significantly associated with ART interruption across all age groups. Healthcare-related stigma may have a larger impact on continuum of care of PLWH than other indicators of stigma. Tailored approaches that reduce healthcare-related stigma in Kenya may play an important role in optimizing treatment interruption. Specific focus to internalized stigma may be relevant for those in the youngest age group. Further analyses utilizing longitudinal data are needed to identify how different indicators of stigma and the mediating pathways affecting treatment interruption vary across different age groups
IMPUTATION OF MISSING DATA IN DEVELOPING PREDICTIVE MODEL OF TIME-TO-EVENT OUTCOMES: A SIMULATION STUDY AND CASE STUDY
Get PDFMissing data poses a common challenge in data-driven studies. While these challenges have
garnered attention in various contexts, there is a paucity of evidence-based research focused on predicting accuracy following imputation in studies involving survival outcomes, particularly in time-to-event analyses. Given the intricate interplay of biomedical data and the growing importance of real-world evidence, addressing missing predictor variables in medical research necessitates a more rigorous approach.
This study seeks to compare and evaluate existing and contemporary methodologies for handling missing data in time-to-event outcome studies. Furthermore, it aims to replicate the most promising method in a real-world scenario. Our investigation encompasses missing completely at random (MCAR), missing at random (MAR) and not missing at random
(NMAR) patterns in simulated datasets, employing various imputation techniques to address missingness. We assess the efficacy of these methods using key metrics such as the c-index, Brier score, and root mean squared prediction error, calibration slope and calibration-in-the-large to identify the optimal approach.
Finally, we demonstrate the impact of the selected imputation method using an illustrative
example from the field of cancer research. We will compare and discuss the prediction
accuracy with and without imputation of missing data, providing valuable insights into the
practical implications of our findings
PERCEPTIONS AND ATTITUDE TOWARD ARTIFICIAL INTELLIGENCE AMONG CHINESE ONCOLOGISTS
Get PDFObjective: To explore Chinese oncologists' knowledge, perceptions, and acceptance of artificial intelligence (AI) in oncology, as well as their concerns regarding its integration into clinical practice and its impact on the doctor-patient relationship.
Methods: A cross-sectional online survey was conducted from April to June 2023, engaging 228 Chinese oncologists. The survey evaluated demographics, AI exposure, knowledge, attitudes towards AI using 5-point Likert scales, and concerns about AI's influence on clinical practice and the doctor-patient dynamic. Data were analyzed using descriptive statistics, chi-square tests, and variate analyses to identify correlations with oncologists' backgrounds.
Results: Oncologists showed a moderate understanding of AI (mean 3.39/5), with younger professionals showing greater knowledge and openness towards AI integration in healthcare. A cautious but optimistic acceptance of AI is noted (mean 3.57/5), with 74.13% acknowledging AI's potential benefits in healthcare innovation. Younger respondents (~30 years) show significantly higher trust (p=0.004) and acceptance (p=0.009) of AI compared to older respondents, while trust is significantly higher among those with master's or doctorate versus bachelor's degrees (p=0.032), and acceptance is higher for those with prior IT experience (p=0.035), highlighting a generational and experiential divide in attitudes towards AI. Major concerns include AI's potential to mislead diagnosis/treatment (71.49%), over-reliance on AI (71.05%), and data and algorithm bias (53.95%), data security and patient privacy (53.95%), and the inadequacy of legal frameworks (50.44%). Opinions on AI's impact on doctor-patient relationships were mixed, with 53.07% seeing a positive impact. Views on AI replacing doctors varied widely.
Conclusions: Chinese oncologists exhibit a cautiously optimistic attitude towards AI in oncology, recognizing its potential benefits but also expressing valid concerns. The study underscores the need for targeted education, particularly for older oncologists, to facilitate AI's adoption. To effectively integrate AI into oncology, a collaborative effort involving policymakers, developers, healthcare professionals, and legal experts is required. Emphasis on transparency, human-centered design, bias mitigation, and understanding AI's potential and limitations is crucial for enhancing patient care while balancing ethical considerations
EXPLORING THE PROLIFERATION AND ADIPOGENIC POTENTIAL OF ADIPOSE-DERIVED STEM CELL SUBPOPULATIONS
No full textThe therapeutic applications of mesenchymal stem cells (MSCs), particularly adipose-derived stem cells (ADSCs), in soft tissue regeneration have shown significant promise due to their potential to proliferate and differentiate into diverse cell types. Previous research highlights the importance of identifying subpopulations within the ADSC pool, distinguished by unique surface marker expressions, to optimize their regenerative capabilities for targeted therapeutic outcomes. This study explores the proliferative and adipogenic differentiation capacities of three ADSC subpopulations DPP4+, CD107a+, and CD201-. While rat ADSCs (rADSCs) show a consistent proliferative trend across subpopulations, mouse ADSCs (mADSCs) display a declining trend, reflecting species-specific cellular dynamics. In mADSC batches, the first batch exhibits pronounced adipogenic potential in the DPP4+ subpopulation compared to others, with consistency decreasing in later batches, possibly due to batch-to-batch variations. The CD201- subpopulation of rADSCs demonstrates superior differentiation potential compared to CD201+, while overall adipogenic capabilities across DPP4+, CD107a+, and CD201- subpopulations remain relatively consistent. Together, these insights underscore the multifaceted behavior of ADSCs in vitro and the need for the targeted use of the ADSCs for therapeutic purposes
CYSTIC FIBROSIS THERAPEUTIC OPTIONS IN PRIMARY CULTURED EPITHELIAL CELLS FROM ECCRINE SWEAT GLANDS AND NASAL AIRWAYS
Get PDFThe work presented here is focused on four current topics in cystic fibrosis (CF) research – modifier gene contributions to CF phenotypes, CFTR functional testing in primary cells, how sweat and sweat glands can expand our CF knowledge, and treatment options for people with CF (pwCF) who are not eligible for current CFTR modulator treatments. Chapter 2 discusses the impact of modifier genes on overall CF phenotype, focusing specifically on SLC26A9 in individuals with the CFTR variant G551D. Here, using a linear model, we demonstrate that genotype at the SLC26A9 SNP rs7512462 does not associate with either baseline lung function or change in lung function in response to ivacaftor in these individuals. In Chapter 3, we address eccrine sweat glands (ESGs) in CF research. We introduce several tools in this chapter that we hope will be used for future analyses in addition to our own: a) we create a single-cell RNA-seq dataset of whole micro-dissected ESGs, b) we develop a primary epithelial ESG cell culture protocol, which allows for CFTR functional testing in ESG cells, and c) we optimize the CLARITY optical clearing technique for whole ESGs and perform 3D immunofluorescence imaging on whole sweat glands using multi-photon microscopy to localize proteins of interest. Finally, in Chapter 4 we combine nonsense-mediated decay inhibition, readthrough, and highly effective CFTR modular drugs to treat primary and immortalized airway epithelial cells with nonsense variants in CFTR, focusing on the variant W1282X. This approach is potentially translatable to the ~6% of individuals with CF who are not eligible for current treatments as well as for individuals with other genetic disorders caused by nonsense variants. Taken together, this work explores multiple aspects of precision care in the context of CF, with concepts applicable to the broader study of genetic disorders
OPTIMIZING MULTIPLEXED ANALYSIS OF PROJECTIONS BY SEQUENCING (MAPSEQ) WITH ADENO-ASSOCIATED VIRUS (AAV): IN VITRO DEVELOPMENTS AND PRELIMINARY APPLICATIONS
No full textStudying the comprehensive map of brain neural connections, also known as the connectome, is pivotal for current brain research. As people's understanding of the brain deepens, the importance of studying the brain connectome also increases. The old compartment view of the brain is no longer feasible, as more and more research shows that various neural circuits act together and become functional. Neural circuit and their roles in neural functions, behaviors, and various neurological disorders urge the development of a detailed connectome. However, the research method to achieve a detailed connectome is limited because the conventional methods of neuron labeling are very low throughput. One possible solution is the Multiplex Analysis of Projections by Sequencing(MAPseq), which utilizes barcoded RNA viruses to high throughput trace multiple neuron projections simultaneously. Additionally, Brain-wide individual animal connectome sequencing(BRICseq) enables multiplex tracing of neurons from various source areas and can potentially trace the whole brain connectome with single animals. But BRICseq is both tedious and expensive, requiring a non-common virus, SINV, which is not easily accessible for many labs. Thus, developing a modified MAPseq method using AAV can be very beneficial. AAV is a commonly used virus and is easily accessible commercially. AAV-mediated MAPseq can also be less laborious because AAV can cross the blood-brain barrier. Thus, a single retro-orbital injection can be sufficient for whole-brain neural tracing. The AAV mediate MAPseq approach can also benefit brain connectome study of various species since some AAV serotypes were known to have great neurotropism in multiple species. This approach can facilitate studies about the complexity of neural networks and has great potential for constructing brain connectome atlas for various species
THE IMPACT OF NON-NUTRITIVE SWEETENERS ON GUT BACTERIA: IMPLICATIONS FOR METABOLIC SYNDROME
No full textNon-nutritive sweeteners (NNS) are commonly used as additives in low-calorie or sugar-free foods, offering sweetness without adding calories or eliciting a post- prandial glycemic response. While once endorsed by health agencies as a tool for managing metabolic health, emerging research suggests NNS might worsen the conditions its users are trying to prevent. Recent studies indicate NNS can alter the gut microbiome, potentially exacerbating weight gain and glucose intolerance and consequently increasing the risk of type 2 diabetes and cardiovascular disease. However, variability in the data complicates efforts to establish a direct causal relationship between NNS consumption and these metabolic outcomes. Some variability can be attributed to interpersonal variations in the human microbiome, which has been causally linked to personalized metabolic responses to NNS. The mechanisms through which a NNS-modulated microbiome can impact metabolic health remain poorly understood, further complicating efforts to establish causality. Understanding how different microbiomes respond to NNS is essential for elucidating the personalized mechanisms through which NNS may impact cardiometabolic health. In this thesis, I screened twenty bacterial strains, measuring how two prototypical NNS, saccharin and sucralose, inhibit growth across five dominant phyla in the gut. This screen revealed that saccharin and sucralose have species-specific and sweetener-specific impacts on bacterial growth that can be modulated by nutrient availability. To explore the mechanisms through which a microbiome modulated by NNS could impact metabolic health, I investigated the repercussions of a sweetener-altered microbiome on the metabolic health of germ-free mice. qPCR analysis of tight junction genes in the colon and liver revealed expression patterns that correlated with fasting hyperglycemia and glucose tolerance. Global transcriptomic profiling of liver tissue from mice conventionalized with an NNS-modulated microbiome revealed several differentially expressed genes in the liver, notably genes related to circadian rhythmicity and lipid metabolism. This research contributes to resolving conflicting literature on the effects of NNS on gut bacteria and proposes a potential mechanism linking NNS exposure to metabolic syndrome via the gut-liver axis
EXPLORE THE IMPACT OF JOINT COMMISSION INTERNATIONAL (JCI) ACCREDITATION ON PRIVATE HOSPITALS IN CHINA: A MIXED-METHODS STUDY
Get PDFJoint Commission International (JCI) Accreditation is the world’s leader in healthcare accreditation, given its main objective of improving the quality of healthcare and patient safety worldwide. Pursuing JCI is one of the popular tools to promote continuous quality improvement by standardizing hospital processes and providing education in different countries or regions outside of the United States, as accreditation is perceived as an external audit review mechanism to check hospitals' conformity with established standards [1]. Studying the impact of JCI accreditation on the hospital has practice significance. As of December 2022, 946 healthcare organizations, including 46 Chinese healthcare organizations, have valid JCI accreditation. Over 97.8% (45/46) of JCI-accredited healthcare organizations in China are private hospitals [2]. This study aims to contribute to understanding the impact of JCI accreditation on Chinese private hospitals. The perceptions of hospital leaders and employees regarding the motivations, challenges, and benefits of implementing JCI standards were explored. In addition, the association between JCI accreditation and the hospital’s clinical, operational, and financial performances was assessed. Qualitative and quantitative methods were applied for different aims in this study. To explore the hospital leaders’ perception regarding the impact of JCI accreditation, in-depth qualitative interviews with 15 hospital leaders, including the chief operating officer, the chief medical officer, and the chief quality officer were conducted. A cross-sectional survey was sent to 2,326 full-time employees, with 1,948 respondents returned (83.7% response rate). Statistical analyses were conducted to explore hospital employees’ attitudes toward the JCI accreditation process in five hospitals and an interrupted time series analysis (ITSA) model was used to examine the impact of JCI accreditation by analyzing 8-year data on the hospital’s clinical, operational, and financial performances. This research is the first study to assess the impact of JCI accreditation on private hospitals in China
THE DIRECT IMPACT OF HIV ANTIRETROVIRAL THERAPY ON GUT MICROBIOME, GUT VIROME, AND HOST METABOLIC HEALTH
No full textAntiretroviral therapy (ART) is highly effective in controlling HIV viral replication and converting fatal HIV infections into manageable long-term chronic carriage. Since ART became available, AIDS-related mortality and the incidence of new HIV infections significantly decreased. However, People living with HIV (PLWH) are still experiencing a high risk of non-AIDS-related chronic conditions, especially cardiometabolic disorders, including metabolic syndrome, cardiovascular diseases, and metabolic dysfunction-associated steatotic liver disease (MASLD). Previous studies have suggested that ART directly contributes to the development of metabolic co-morbidities, yet the underlying mechanisms remain unknown. We hypothesize that ART alters the gut microbiome and virome to a configuration that contributes to the development of metabolic co-morbidities. Previously, we found that combination ART (ABC/DTG/3TC; Triumeq) directly altered the gut microbiome and virome in mice. In my thesis work, I further assessed the impact of antiretrovirals (ARV) given individually or in combination on metabolic health. Combination ART (TDF/FTC/DTG; Truvada-Tivicay) as well as individual drugs exacerbated diet-induced weight gain (3TC, DTG, TAF) and glucose intolerance (FTC, ABC, cART). Preliminary microbiome profiling revealed that DTG and FTC altered both the microbiome and virome, while TDF altered the gut virome specifically. To explore the mechanisms through which ART alters the microbiome, I explored bacteria-phage-drug interactions in vitro. ART inhibited the growth of a complex bacterial community in a drug-dependent manner, and dolutegravir (DTG) altered the interaction between bacteriophage lambda and its host E. coli K-12. Altogether, these findings suggest a causal connection between ART and impact on metabolic health and provide insight into the mechanisms of microbiome modulation by ART
Cancer Preference Reflection and Elicitation for Family Support: Development of a Preference Instrument for Advanced Prostate Cancer Patients
No full textAdvanced prostate cancer patients face a difficult treatment regimen and an incurable disease. Palliative treatment decision making can be a difficult process that is associated with negative outcomes such as stress, anxiety, and depression for decision partners. Advanced prostate cancer patients often face rapid deterioration of their health, with a decision partner/proxy often stepping into the role of proxy decision-maker. This dissertation provides a rigorous qualitative exploration of the decisions that a diverse sample of advanced prostate cancer patients and their supporters face when making palliative anti-cancer treatment decisions. A discrete choice experiment to quantify advanced prostate cancer patient preferences for palliative anti-cancer treatment was developed and piloted. A synthesis of the dissertation research findings and implications is provided. This research contributes new knowledge about the experience of advanced prostate cancer patients and their supporters and proposes an innovative use of discrete choice experiments to facilitate treatment decisions in complex scenarios