Background: Misconceptions regarding activities after pacemaker implantation can result in restrictions in daily life. This study aims at measuring the correction of misconceptions following an educational intervention utilizing a picture based brochure and personal counseling. Methods: One hundred and twenty-eight patients were enrolled in a quasi experimental study on the day after pacemaker implantation. Patients’ perceptions about safety of various daily activities, medical procedures, and usage of appliances, in the presence of pacemaker was assessed using a questionnaire before and ten days after an educational intervention using a pictorial brochure. The number of correct responses before and after the intervention was compared to assess the change in patients’ perception. Results: A total of 128 patients were interviewed at baseline, of which 115 followed-up at 10 days. Mean age of patients was 60.31 ± 12.81 years. In total, 76 (59.4%) were male and 61(47.7%) were illiterate. Mean correct responses increased from 64.47 ± 29.48% to 92.29 ± 14.42% (p < 0.001). Percent of questions answered correctly improved in all three categories after the intervention. Correct answers increased from 74.57 ± 24.94% to 95.65 ± 11.48% (p  < 0.001) for routine daily activities, 51.09 ± 33.9% to 84.78 ± 20.86% (p < 0.001) for medical procedures and 64.03 ± 37.36% to 92.57 ± 18.79% (p  < 0.001) for domestic appliance usage. Conclusion Misconception that can adversely affect pacemaker patient’s quality of life can be corrected by counseling with pictorial based brochures regardless of the patient’s baseline knowledge or education.

Background: Misconceptions regarding activities after pacemaker implantation can result in restrictions in daily life. This study aims at measuring the correction of misconceptions following an educational intervention utilizing a picture based brochure and personal counseling. Methods: One hundred and twenty-eight patients were enrolled in a quasi experimental study on the day after pacemaker implantation. Patients’ perceptions about safety of various daily activities, medical procedures, and usage of appliances, in the presence of pacemaker was assessed using a questionnaire before and ten days after an educational intervention using a pictorial brochure. The number of correct responses before and after the intervention was compared to assess the change in patients’ perception. Results: A total of 128 patients were interviewed at baseline, of which 115 followed-up at 10 days. Mean age of patients was 60.31 ± 12.81 years. In total, 76 (59.4%) were male and 61(47.7%) were illiterate. Mean correct responses increased from 64.47 ± 29.48% to 92.29 ± 14.42% (p < 0.001). Percent of questions answered correctly improved in all three categories after the intervention. Correct answers increased from 74.57 ± 24.94% to 95.65 ± 11.48% (p  < 0.001) for routine daily activities, 51.09 ± 33.9% to 84.78 ± 20.86% (p < 0.001) for medical procedures and 64.03 ± 37.36% to 92.57 ± 18.79% (p  < 0.001) for domestic appliance usage. Conclusion Misconception that can adversely affect pacemaker patient’s quality of life can be corrected by counseling with pictorial based brochures regardless of the patient’s baseline knowledge or education.

Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused devastation in over 200 countries. Italy, Spain, and the United States (US) were most severely affected by the first wave of the pandemic. The reasons why some countries were more strongly affected than others remain unknown. We identified the most-affected and lessaffected countries and states and explored environmental, host, and infrastructure risk factors that may explain differences in the SARS-CoV-2 mortality burden. Methods: We identified the top 10 countries/US states with the highest deaths per population until May 2020. For each of these 10 case countries/states, we identified 6 control countries/ states with a similar population size and at least 3 times fewer deaths per population. We extracted data for 30 risk factors from publicly available, trusted sources. We compared case and control countries/states using the non-parametric Wilcoxon rank-sum test, and conducted a secondary cluster analysis to explore the relationship between the number of cases per population and the number of deaths per population using a scalable EM (expectation– maximization) clustering algorithm. Results: Statistically significant differences were found in 16 of 30 investigated risk factors, the most important of which were temperature, neonatal and under-5 mortality rates, the percentage of under-5 deaths due to acute respiratory infections (ARIs) and diarrhea, and tuberculosis incidence (p < 0.05) Conclusion Countries with a higher burden of baseline pediatric mortality rates, higher pediatric mortality from preventable diseases like diarrhea and ARI, and higher tuberculosis incidence had lower rates of coronavirus disease 2019-associated mortality, supporting the hygiene hypothesis.

Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused devastation in over 200 countries. Italy, Spain, and the United States (US) were most severely affected by the first wave of the pandemic. The reasons why some countries were more strongly affected than others remain unknown. We identified the most-affected and lessaffected countries and states and explored environmental, host, and infrastructure risk factors that may explain differences in the SARS-CoV-2 mortality burden. Methods: We identified the top 10 countries/US states with the highest deaths per population until May 2020. For each of these 10 case countries/states, we identified 6 control countries/ states with a similar population size and at least 3 times fewer deaths per population. We extracted data for 30 risk factors from publicly available, trusted sources. We compared case and control countries/states using the non-parametric Wilcoxon rank-sum test, and conducted a secondary cluster analysis to explore the relationship between the number of cases per population and the number of deaths per population using a scalable EM (expectation– maximization) clustering algorithm. Results: Statistically significant differences were found in 16 of 30 investigated risk factors, the most important of which were temperature, neonatal and under-5 mortality rates, the percentage of under-5 deaths due to acute respiratory infections (ARIs) and diarrhea, and tuberculosis incidence (p < 0.05) Conclusion Countries with a higher burden of baseline pediatric mortality rates, higher pediatric mortality from preventable diseases like diarrhea and ARI, and higher tuberculosis incidence had lower rates of coronavirus disease 2019-associated mortality, supporting the hygiene hypothesis.