An Objective and Robust Bayes Factor for the Hypothesis Test One Sample and Two Population Means.

It has been over 100 years since the discovery of one of the most fundamental statistical tests: the Student's t test. However, reliable conventional and objective Bayesian procedures are still essential for routine practice. In this work, we proposed an objective and robust Bayesian approach for hypothesis testing for one-sample and two-sample mean comparisons when the assumption of equal variances holds. The newly proposed Bayes factors are based on the intrinsic and Berger robust prior. Additionally, we introduced a corrected version of the Bayesian Information Criterion (BIC), denoted BIC-TESS, which is based on the effective sample size (TESS), for comparing two population means. We studied our developed Bayes factors in several simulation experiments for hypothesis testing. Our methodologies consistently provided strong evidence in favor of the null hypothesis in the case of equal means and variances. Finally, we applied the methodology to the original Gosset sleep data, concluding strong evidence favoring the hypothesis that the average sleep hours differed between the two treatments. These methodologies exhibit finite sample consistency and demonstrate consistent qualitative behavior, proving reasonably close to each other in practice, particularly for moderate to large sample sizes.

Outcomes of chronic total occlusion percutaneous coronary intervention in patients with prior coronary artery bypass graft surgery: Insights from the LATAM CTO registry.

OBJECTIVES: To evaluate the outcomes of chronic total occlusion (CTO) percutaneous coronary intervention (PCI) in patients with and without prior coronary artery bypass graft (CABG) surgery. BACKGROUND: Data on the outcomes of CTO PCI in patients with versus without CABG remains limited and with scarce representation from developing regions like Latin America. METHODS: We evaluated patients undergoing CTO PCI in 42 centers participating in the LATAM CTO registry between 2008 and 2020. Statistical analyses were stratified according to CABG status. The outcomes of interest were technical and procedural success and in-hospital major adverse cardiac and cerebrovascular events (MACCE). RESULTS: A total of 1662 patients were included (n = 1411 [84.9%] no-CABG and n = 251 [15.1%] prior-CABG). Compared with no-CABG, those with prior-CABG were older (67 ± 11 vs. 64 ± 11 years; p < 0.001), had more comorbidities and lower left ventricular ejection fraction (52.8 ± 12.8% vs. 54.4 ± 11.7%; p = 0.042). Anatomic complexity was higher in the prior-CABG group (J-CTO score 2.46 ± 1.19 vs. 2.10 ± 1.22; p < 0.001; PROGRESS CTO score 1.28 ± 0.89 vs. 0.91 ± 0.85; p < 0.001). Absence of CABG was associated with lower risk of technical and procedural failure (OR: 0.60, 95% CI: 0.43-0.85 and OR: 0.58, 95% CI: 0.40-0.83, respectively). No significant differences in the incidence of in-hospital MACCE (3.8% no-CABG vs. 4.4% prior-CABG; p = 0.766) were observed between groups. CONCLUSION: In a contemporary multicenter CTO-PCI registry from Latin America, prior-CABG patients had more comorbidities, higher anatomical complexity, lower success, and similar in-hospital adverse event rates compared with no-CABG patients.

The psychological impact of the COVID-19 pandemic on physicians in Puerto Rico: a cross-sectional study after the second wave in 2021.

Introduction: Health care providers faced a challenge with the emergence of COVID-19 and its rapid spread. Early studies measuring the psychological impact of COVID-19 on the general population found high levels of anxiety and sleep disorders. The primary goal of this project was to assess the psychological impact of COVID-19 on physicians in Puerto Rico. Materials and methods: A cross-sectional study of physicians in Puerto Rico was conducted anonymously and electronically from February 2021 through April 2021. The electronic survey included socio-demographic data and 4 self-administered assessment tools (Generalized Anxiety Disorder-7, Perceived Stress Scale-10, Pittsburgh Sleep Quality Index and COVID-19 Organizational Support) for anxiety, perceived stress, sleep disturbances, and organizational support during the COVID-19 pandemic. Results: A total of 145 physicians completed the survey, with a female predominance of 53.5% and a majority practicing in the San Juan metropolitan area (50.3%). Mild anxiety symptoms were reported in 26.9% of physicians, and 33.8% had moderate to severe anxiety symptoms. Moderate to high perceived stress was found in 69.9% of participants, and women reported statistically significantly higher levels of anxiety symptoms (8.84 ± 5.99; p = 0.037) and stress (19.0 ± 6.94, p = 0.001). The Pittsburgh Sleep Quality Index reported 67.9% of physicians with global scores associated with poor sleep quality. Assessment of perceived organizational support found a high perception of work support (65.7%) but low perception of personal support (43.4%) and risk support (30.3%). A correlation analysis found a negative correlation for work and personal support, but a positive correlation for risk support, all statistically significant. Conclusion: COVID-19 had a lasting psychological impact in health care providers in Puerto Rico a year after the beginning of the pandemic. Our data supports the importance of organizational support and its correlation with the development of anxiety. It is thus essential to develop strategies to identify individuals at risk of experiencing psychological disturbances and to provide effective support for medical professionals during medical emergencies for their well-being and optimal delivery of patient care.

Development of the Anthropometric Grouping Index for the Eastern Caribbean Population Using the Eastern Caribbean Health Outcomes Research Network (ECHORN) Cohort Study Data.

Improving public health initiative requires an accurate anthropometric index that is better suited to a specific community. In this study, the anthropometric grouping index is proposed as a more efficient and discriminatory alternative to the popular BMI for the Eastern Caribbean population. A completely distribution-free cluster analysis was performed to obtain the 11 categories, leading to AGI-11. Further, we studied these groups using novel non-parametric clustering summaries. Finally, two generalized linear mixed models were fitted to assess the association between elevated blood sugar, AGI-11 and BMI. Our results showed that AGI-11 tends to be more sensitive in predicting levels of elevated blood sugar compared to BMI. For instance, individuals identified as obese III according to BMI are (POR: 2.57; 95% CI: (1.68, 3.74)) more likely to have elevated blood sugar levels, while, according to AGI, individuals with similar characteristics are (POR: 3.73; 95% CI: (2.02, 6.86)) more likely to have elevated blood sugar levels. In conclusion, the findings of the current study suggest that AGI-11 could be used as a predictor of high blood sugar levels in this population group. Overall, higher values of anthropometric measures correlated with a higher likelihood of high blood sugar levels after adjusting by sex, age, and family history of diabetes.