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Background: Racial discrimination is associated with health disparities among Black Americans, a group that has experienced an increase in rates of fatal drug overdose. Prior research has found that racial discrimination in the medical setting may be a barrier to addiction treatment. Nevertheless, it is unknown how experiences of racial discrimination might impact engagement with emergency medical services for accidental drug overdose. This study will psychometrically assess a new measure of hesitancy in seeking emergency medical services for accidental drug overdose and examine prior experiences of racial discrimination and group-based medical mistrust as potential corollaries of this hesitancy.

Method: Cross-sectional survey of 200 Black adults seeking treatment for substance-use-related medical problems (i.e. substance use disorder, overdose, infectious complications of substance use, etc.). Participants will complete a survey including sociodemographic information, the Discrimination in Medical Settings Scale, Everyday Discrimination Scale, Group-Based Medical Mistrust Scale, and an original questionnaire measuring perceptions of and prior engagement with emergency services for accidental drug overdose. Analyses will include exploratory factor analysis, Cronbach's alpha, and non-parametric partial correlations controlling for age, gender, income, and education.

Conclusions: This article describes a planned cross-sectional survey of Black patients seeking treatment for substance use related health problems. Currently, there is no validated instrument to measure hesitancy in seeking emergency medical services for accidental drug overdose or how experiences of racial discrimination might relate to such hesitancy. Results of this study may provide actionable insight into medical discrimination and the rising death toll of accidental drug overdose among Black Americans.

Background: New digital learning environments have transformed medical education and training, allowing students and teachers to engage in synchronous, real-time interactions and asynchronous learning activities online. Despite extensive research on the role of digital technologies in education, understanding the interplay between digital technology, work, and learning, especially in complex fields like healthcare, remains a challenge.

Objective: The objective of this study is to examine resident physicians' perceptions and experiences of using a digital learning environment as part of their specialist medical training. The paper focuses on digital learning through video conferencing (virtual lectures and seminars) and related learning technologies. It aims to understand how resident physicians perceive pedagogical opportunities and challenges in digital learning environments during their medical training and what strategies they use to address these.

Materials and methods: The methodological approach is qualitative, aiming to capture and understand participants' experiences and views of digital learning. The empirical data gathered from open-ended responses to four course evaluation surveys and semi-structured interviews with nine physicians from a cohort of participants enrolled in two or more digital courses were analyzed through thematic analysis. The analysis revealed three main themes related to digital transformation of learning: sociotechnical, educational and administrative.

Results: The results suggest that (i) sociotechnical aspects and understanding of the context in which the learning takes place contribute to enhancing digital learning for resident physicians; (ii) insights into participants' perceptions of digital learning emphasize that interactive communication and group discussions are significant for their learning, and (iii) administrative aspects related to course design, lecture management, and instructional support are more important in digital learning environments compared to traditional teaching and learning.

Conclusion: Findings from this study confirm and extend prior studies on digital learning in healthcare, contributing to a better understanding of how digital learning environments, especially virtual lectures and seminars, can be developed and integrated into residency programs and health professions education to increase their usefulness.

Background: The benefit of therapeutic drug monitoring (TDM) and implementation of recommendations from the Selection of Therapeutic Targets in Inflammatory Bowel Disease (IBD, STRIDE) are discussed in the IBD community. We report real-world data in ulcerative colitis patients receiving first-line tumour necrosis factor inhibitor (TNFi) treatment followed by TDM, and assess how implementation of the STRIDE II recommendations might affect clinical practice.

Methods: Adult, biologically naïve UC patients starting TNFi between 2014 and 2021 at Oslo University Hospital were included in a medical chart review study, and data were collected at three and twelve months after the start of treatment. Target serum drug levels were defined as ≥7.5 mg/L for adalimumab and ≥5 mg/L for infliximab.

Results: Of 141 included patients, 36% were in clinical and biochemical (combined) remission after twelve months. Among 102 treatment persistent patients, 54% were in combined remission after twelve months. Target drug level at three months was associated with clinical remission at twelve months (OR = 2.97, 95% CI [1.24-7.12]) and biochemical remission at twelve months (OR = 2.64, 95% CI [1.03-6.77]). In total, 56% of recorded dosage adjustments were related only to serum drug levels.

Conclusions: Combined remission rates at twelve months for treatment persistent patients suggest that 46% should have been considered for a change of treatment according to the STRIDE II recommendations. A majority of dosage adjustments were made proactively. Target drug level at three months was associated with remission at twelve months and supports the use of proactive TDM.

Background: Yigu decoction (YGD) is a traditional Chinese medicine prescription for the treatment of osteoporosis, although many clinical studies have confirmed its anti-OP effect, but the specific mechanism is still not completely clear.

Methods: In this study, through the methods of network pharmacology and molecular docking, the material basis and action target of YGD in preventing and treating OP were analyzed, and the potential target and mechanism of YGD in preventing and treating OP were clarified by TMT quantitative protein and experiment.

Results: Network pharmacology and molecular docking revealed that the active components of YGD were mainly stigmasterol and flavonoids. Molecular docking mainly studied the strong binding ability of stigmasterol to the target. Animal proteomics verified the related mechanism of YGD in preventing and treating OP. Based on the KEGG enrichment of network pharmacology and histology, our animal experiments in vivo verified that YGD may play a role in the treatment of OP by mediating hif1- α/vegf/glut1 signal pathway.

Conclusions: YGD prevention and treatment of OP may be achieved by interfering with multiple targets. This study confirmed that it may promote osteoblast proliferation and protect osteoblast function by up-regulating the expression of proteins related to HIF signal pathway.

Background: Individuals with alcohol use disorder (AUD) often experience symptoms such as anxiety, depression, and decreased sleep quality. Although these are not diagnostic criteria, they may increase dependence risk and complicate treatment. This study aims to analyze comorbidities and their complex relationships in AUD patients through epidemiological surveys and network analysis.

Materials and methods: Using multi-stage stratified cluster random sampling, we selected 27,913 individuals and identified those with AUD for the study. All screened subjects were assessed with the General Health Questionnaire, Pittsburgh Sleep Quality Index, and Simple Coping Style Questionnaire, and diagnosed according to DSM-IV criteria. Network analysis and visualization were performed in R 4.4.0. The qgraph and bootnet packages in R were used to obtain partial correlation network analysis and node centrality of mental health, sleep quality, and coping styles in individuals with AUD through the estimateNetwork function. The bootnet package was used to assess the accuracy and stability of the network. The bnlearn package in R was used to construct directed acyclic graph (DAG) for individuals with AUD using the Bayesian hill-climbing algorithm.

Results: In the partial correlation network, among the three major comorbidity categories, 'anxiety/depression' was most strongly associated with 'sleep quality'. 'Anxiety/depression' and 'sleep quality' had the highest node centrality, with 'sleep latency' also showing notable centrality. The DAG results indicated that 'sleep latency' had the highest probability priority, directly affecting 'anxiety/depression' and key sleep quality symptoms such as 'subjective sleep quality', 'sleep disturbances', 'sleep duration', and 'sleep efficiency', while also indirectly influencing other symptoms.

Conclusions: Among the comorbid symptoms of AUD, sleep latency appears to be a key factor in triggering other comorbid symptoms. This study provides a basis for interventions aimed at reducing the comorbid symptoms of AUD and promoting recovery.

Background: Understanding the determinants that limit the population's access to surgical care in health services is highly relevant in order to provide data to support political interventions.

Objective: This study aimed to evaluate the time between diagnosis and elective surgery in adult patients with the longest waiting lists in Brazil; identify the determinants that interfere with access to the health service to perform surgery; and analyze the quality of life after the indicative diagnosis of surgical intervention.

Methods: A cross-sectional study was conducted with adult patients treated at three hospitals in the Southeast, North and South regions of Brazil, from October 2020 to October 2022. Data collection included socio-demographic data and assessment of quality of life using the WHOQOL-Bref instrument in the immediate postoperative period and one month after surgery.

Results: A total of 250 patients participated in the study, 55.6% patients from the Southeast, 20.4% patients from the North and 24% patients from the South, with a mean age of 51.86 (SD = 14.27) years and clinical history such as arterial hypertension (p < 0.001). The longest mean waiting time for surgery identified was 26.23 (SD = 17.62) months in the South region, with a significant difference between the evaluated institutions (p = 0.02). Differences were observed between the first place of care of the evaluated patients (p < 0.001). There was a difference in the perception of quality of life between the immediate and late postoperative periods (p = 0.007) and in the physical domain, with an increase in scores among older patients (p = 0.004) and previous clinical history (p = 0.03).

Conclusion: Access to the health system varies by region and does not meet the standards proposed by the Brazilian health system. In addition, it seems that longer waiting times for surgery more perceptibly affect the quality of life of older adults and those with other associated diseases.

As one of the three major malignant tumors in women, the morbidity of endometrial cancer is second only to that of cervical cancer and is increasing yearly. Its etiological mechanism is not clear, and the risk factors are numerous and common and are closely related to obesity, hypertension, diabetes, etc. The gut microbiota has many strains, which play a considerable part in normal digestion and absorption in the human body and the regulation of the immune response. In the last few years, research on the gut microbiota has been unprecedentedly popular, and it has been confirmed that the gut microbiota closely correlates with the occurrence and development of all kinds of benign and malignant diseases. In this article, the effects of the gut microbiota and its metabolites on the occurrence and development of endometrial cancer is reviewed, and its application in the prevention, diagnosis and treatment of endometrial cancer is explored.

Introduction: Multimorbidity is increasing globally, emphasizing the need for effective self-management strategies. The Cumulative Complexity Model (CuCoM) offers a unique perspective on understanding self-management based on workload and capacity. This study aims to validate the CuCoM in multimorbid patients and identify tailored predictors of self-management.

Methods: This multicenter cross-sectional survey recruited 1920 multimorbid patients in five primary health centres and four hospitals in China. The questionnaire assessed workload (drug intake, doctor visits and follow-up, disruption in life, and health problems), capacity (social, environmental, financial, physical, and psychological), and self-management. Data were analyzed using latent profile analysis, chi-square, multivariate linear regression, and network analysis.

Results: d Patients were classified into four profiles: low workload-low capacity (10.2%), high workload-low capacity (7.5%), low workload-high capacity (64.6%), and high workload-high capacity (17.7%). Patients with low workload and high capacity exhibited better self-management (β = 0.271, p < 0.001), while those with high workload and low capacity exhibited poorer self-management (β=-0.187, p < 0.001). Social capacity was the strongest predictor for all profiles. Environmental capacity ranked second for 'high workload-high capacity' (R² = 3.26) and 'low workload-low capacity' (R² = 5.32) profiles. Financial capacity followed for the 'low workload-high capacity' profile (R² = 5.40), while psychological capacity was key in the 'high workload-low capacity' profile (R² = 6.40). In the network analysis, socioeconomic factors exhibited the central nodes (p < 0.05).

Conclusions: Personalized interventions designed to increase capacity and reduce workload are essential for improving self-management in multimorbid patients. Upstream policies promoting health equity are also crucial for better self-management outcomes.

Introduction: Latinx individuals are disproportionately affected by alcohol use disorder (AUD). Understanding Latinx individuals' barriers and facilitators to reach AUD-related goals can help implement culturally and linguistically concordant interventions to improve alcohol-related outcomes.

Methods: We conducted semi-structured qualitative interviews with Latinx, Spanish-speaking men with AUD within 20 weeks of hospital discharge who were seen by an addiction consult team during hospitalization in an urban, safety-net hospital in San Francisco. Interviews focused on the facilitators and barriers to participants' AUD-related goals pre-, during, and post-hospitalization. We recorded and transcribed interviews and used a mixed deductive and inductive analytic approach until we reached thematic saturation (n = 10).

Results: We identified three major themes: 1. Hospitalization was an actionable moment for change; 2. Social factors were closely intertwined with AUD goals; and 3. Accessible addiction, physical health, and mental health services can help achieve AUD goals.

Conclusions: Hospitalization may serve as a facilitator for Latinx individuals with AUD to achieve AUD goals. Addressing social determinants of health including housing, immigration status, and social support networks before, during, and after hospitalization, may help facilitate AUD goals. Providing language-concordant and accessible services may decrease barriers to achieving AUD goals.

Background: Heart failure (HF) remains a significant health problem despite advances in diagnosis and treatment options. Malnutrition and increased inflammation predict poor disease prognosis. The parameters of the Naples prognostic score (NPS) include albumin, total cholesterol, neutrophil-lymphocyte ratio (NLR), and lymphocyte-monocyte ratio (LMR). We aimed to assess the potential of NPS as a predictor of long-term mortality in patients with HF.

Methods: A total of 1728 patients with HF who applied to our center between 2018 and 2022 were included in this study. The NPS was computed and the patients were divided into three groups according to their NPS values as follows: NPS = 0 (Group 1), NPS = 1-2 (Group 2), and NPS = 3-4 (Group 3). We also evaluated the association between NPS value and HF mortality.

Results: The patients were followed for a mean follow-up duration of 30 months. The mortality rate was 8.3% (145 patients). We carried out Model-1 and -2 Cox regression analyses to identify long-term mortality determinants. Model-2 was constructed by adding NPS to Model-1. NPS was significantly associated with HF mortality (Hazard Ratio: 2.194, 95% Confidence Interval: 1.176-4.091, p = 0.014). According to the Kaplan-Meier plot and log-rank analyses, there was a statistically significant difference in the long-term mortality of patients with HF and their NPS values for the entire cohort.

Conclusion: Based on our findings, NPS showed promise as an independent predictor of long-term mortality in individuals with HF.