Journal of the National Medical Association最新文献

A personal anecdote highlighting the myriad myths and misconceptions about why men don't often report domestic violence and the steps that society can take to ensure that everyone who has experienced such violence gets the resources and support they need.

Background: The systemic inflammatory response index (SIRI) is a recently developed composite index that assesses the entire extent of inflammation in the body, closely linked to heart failure (HF). This study aimed to evaluate the potential association between SIRI and HF.

Methods: The cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES) database from 2001 to 2018. SIRI is calculated based on the counts of monocytes, neutrophils, and lymphocytes. A weighted multiple-variable linear regression model examined the correlation between SIRI and HF. Using restrained cubic splines explored the nonlinear relationship between the two, and the robustness of the results was verified by subgroup analysis and interaction tests.

Results: Our study included 30,294 participants, 814 of whom were diagnosed with HF and 29,480 with non-HF. The multiple linear regression analysis showed that SIRI was positively correlated with HF (OR = 1.66; 95 % CI, 1.21, 2.29) and that there was no nonlinear relationship between the two. This relationship persisted in subgroup analyses.

Conclusions: The results indicate a linear positive correlation between SIRI and HF. Further extensive prospective studies are needed to validate these findings.

Objectives: This study investigates the association between statin use and all-cause mortality, as well as the association between statin use and incident diabetes or prediabetes among African Americans.

Methods: This study is based on the Jackson Heart Study (JHS), a community-based cohort study of African Americans (AAs). The baseline period for JHS was 9/26/2000 to 3/31/2004. The first follow-up period was from 10/1/2005 to 12/21/2008, and the second follow-up period was from 2/26/2009 to 1/31/2013. All study participants who were statin users or non-users at baseline were included in this study. We applied two common propensity score adjustment techniques to analyze the data: propensity score matching (PSM) and the inverse probability of treatment weighting (IPTW) algorithms.

Results: In this cohort there were 510 deaths. The baseline prevalence of statin use was 13.95% (95% CI: 12.91% - 14.98%), while the baseline rate of all-cause mortality was 11.82% (95% CI: 10.87% - 12.82%). In crude analyses, statin users had an 80% higher risk of mortality compared to non-users, with an odds ratio (OR) of 1.80 (95% CI: 1.43 - 2.27). However, after adjusting for confounders using PSM and IPTW, the adjusted ORs for the association between statin use and mortality were 0.77 (95% CI: 0.53 - 1.12) and 0.80 (95% CI: 0.68 - 0.95), respectively. A post hoc power analysis suggested that the matched analysis was underpowered. The incidence of diabetes/ prediabetes was 39.42% (95% CI: 37.39% - 41.45%), with 879 new cases observed. Statin users had a crude odds ratio (OR) of 2.02 (95% CI: 1.52 - 2.67) for developing diabetes/prediabetes compared to non-users. After adjusting for confounding using PSM) and IPTW, the adjusted ORs were 1.84 (95% CI: 1.21-2.81) and 1.82 (95% CI: 1.59-2.08), respectively.

Conclusion: Statin use was associated with a 20% decrease in all-cause mortality but an 80% increased risk of incident diabetes/prediabetes. Clinicians should consider the implications of these findings when prescribing statins to patients in this population.

Background: Minorities are underrepresented in all areas of medical education relative to the United States general population, and minority physicians are more likely to practice in disadvantaged areas and in primary care settings. Many individual and structural factors contribute to this discrepancy. We aimed to demonstrate how resident race/ethnicity representation differs across the various resident specialties.

Methods: We used publically available data from the Association of American Medical College's Report on Residents data series and averaged the four academic years from 2019 to 2020 through 2022-2023. We then calculated the odds ratio (OR) of self-reported race/ethnicity (alone and in combination) in thirty-four specialties.

Results: Across the four-year study period, there were, on average, 147026 unduplicated resident trainees. The average number of duplicated residents by self-identified ethnic category (alone and in combination) include: American Indian or Alaska Native (839, 0.6%), Asian (31627, 21.5%), Black or African American (7935, 5.4%), Hispanic, Latino, or of Spanish Origin (10900, 7.4%), Native Hawaiian or Other Pacific Islander (296, 0.2%), White (76289, 51.9%), Other (4879, 3.3%), Unknown (522, 0.4%), and Non-US Citizens (23914, 16.3%). Across race/ethnicity, there are differences in ORs of representation in different specialties. Key findings include high representation in Public Health and Preventative Medicine by Black and African American (OR=3.7) and Native Hawaiian (OR=2.6) residents, and Family Medicine in Native Americans (OR=1.9), Native Hawaiian (OR=1.7), Black (OR=1.5), and Hispanic (OR=1.3) residents. Psychiatry also had high ORs of representation in minority residents.

Conclusion: This study illustrates relative resident ethnic representation across training specialties. Minorities ethnicities were more likely to be represented in primary care and public health domains. This has implications for creating a physician workforce suitable to serve the United States Population.

Objective: As a prevalent persistent respiratory disease, chronic obstructive pulmonary disease (COPD) is featured by airflow limitation and chronic inflammation. This study focused on the identification of immune-related hub genes in COPD.

Methods: We employed the GSE38974 dataset to analyze differentially expressed genes (DEGs) of COPD. Then, we obtained COPD immune-related DEGs (COPD-IMDEGs) based on the intersection of DEGs and immune-related genes. Subsequently, we carried out Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses on COPD-IMDEGs. We established a protein-protein interaction network based on COPD-IMDEGs. The hub genes were determined by utilizing the Maximal Clique Centrality method. We utilized receiver operating characteristic (ROC) curves to analyze the clinical significance of hub genes in COPD. In addition, potential drugs targeting hub genes were predicted based on interactions between hub gene-corresponding proteins and drugs.

Results: A total of 45 COPD-IMDEGs were obtained through differential analysis. Enrichment analyses showed that COPD-IMDEGs were associated with cytokines, growth factors, and receptor ligands. Ten COPD-IMDEGs were identified as hub genes. As shown by ROC curves, these genes had potential value in identifying COPD patients. Drug prediction results showed that simvastatin and other drugs targeted hub genes.

Conclusion: This study analyzed the potential biological functions enriched by COPD-IMDEGs, identified ten genes as biological markers for diagnosing COPD, and predicted potential drugs for treating COPD.