Background For health care workers, immune management plays an important role in the protection against infectious diseases. This study investigated the seroprevalence of measles, mumps, rubella, and varicella-zoster in newly employed female nurses. Methods We conducted a survey on the seroprevalence of measles, mumps, rubella, and varicella-zoster in newly employed female nurses at a university hospital from 2011 to 2019, before the nurses were given their department placements and duty start. Enzyme-linked immunosorbent and chemiluminescence immunoassays were used to detect immunoglobulin G antibodies. We analyzed whether there was a significant difference in seroprevalence depending on the age, birth year, birth season, and region of residence (metropolitan residency: yes or no). Results The arithmetic mean ages of the participants were 28.6 ± 4.8, 23.5 ± 3.2, 23.6 ± 3.0, and 26.1 ± 4.5 years for measles, mumps, rubella, and varicella-zoster, respectively. The seropositivity rates were 93.9% (551/587), 60.2% (50/83), 83.3% (3,093/3,711), and 89.5% (978/1,093) for measles, mumps, rubella, and varicella-zoster, respectively. Significant differences in the seroprevalence when assessed according to the age and birth year were noted with measles, while significant differences in the seroprevalence were only noted with rubella and varicella-zoster when assessed according to birth year and age, respectively. Conclusions In this study, we identified the levels of antibody prevalence in new female nurses. Considering the seropositivity levels, cost-effectiveness, and convenience for the participants, we recommend that the measles-mumps-rubella vaccination be provided without serologic testing for all new female nurses and the varicella-zoster vaccination only be performed for persons who are negative after serologic testing. And it would be useful if the vaccinations were combined with compulsory worker health examinations, such as the pre-placement health examinations.

Background: Lead exposure is a risk factor for increased blood pressure and cardiovascular disease, even when blood lead levels (BLLs) are within the normal range. Objective: This study aimed to investigate the association between BLL and coronary artery stenosis (CAS) in asymptomatic adults using 128-slice dual-source coronary computed tomography (CT) angiography. Methods: We analyzed medical records data from 2,193 adults (1,461 men and 732 women) who elected to complete a screening health examination, coronary CT angiography, and BLL measurement during 2011–2018 and had no history of CAS symptoms, cardiovascular disease, or occupational exposure to lead. Logistic regression models were used to estimate associations between moderate-to-severe CAS ( stenosis) and a increase in blood lead, with and without adjustment for age, sex, hypertension, diabetes mellitus, dyslipidemia, body mass index, regular exercise, smoking status, and alcohol drinking. Results: BLLs ranged from , with an arithmetic mean of . The arithmetic mean was higher for men than for women ( vs. , ) and higher in the moderate-to-severe CAS group than in the no-CAS or stenosis group ( vs. , ). Moderate-to-severe CAS was significantly associated with BLL before and after adjustment, with an adjusted odds ratio for a increase in BLL of 1.14 (95% CI: 1.02, 1.26), . Conclusions: BLL was positively associated with the prevalence of moderate-to-severe CAS in Korean adults who completed an elective screening examination for early cardiovascular disease, 94% of whom had a BLL of . More efforts and a strict health policy are needed to further reduce BLLs in the general population. https://doi.org/10.1289/EHP7351

No abstract

Background Intracranial aneurysm (IA) is difficult to detect, and most patients remain undiagnosed, as screening tests have potential risks and high costs. Thus, it is important to develop risk assessment system for efficient and safe screening strategy. We designed a clinical validation study to test the efficacy and validity of an artificial intelligence (AI) based risk prediction model for intracranial aneurysm in an actual clinical setting.Materials and Methods The study population comprised individuals who visited the Chonnam National University Hwasun Hospital Health Promotion Center in Korea for voluntary medical checkups between 2007 and 2019. All participants had no history of cerebrovascular disease and underwent brain CTA for screening purpose. Presence of IA was evaluated by two specialized radiologists. The risk score was calculated using the previously developed AI model, and 0 point represents the lowest risk and 100 point represents the highest risk. To compare the prevalence according to the risk, age-sex standardization using national database was performed.Result A study collected data from 5,942 health examinations, including brain CTA data, with participants ranging from 20 to 87 years old and a mean age of 52 years. The age-sex standardized prevalence of IA was 3.20%. The prevalence in each risk group was 0.18% (lowest risk, 0–19), 2.12% (lower risk, 20–39), 2.37% (mid-risk, 40–59), 4.00% (higher risk, 60–79), and 6.44% (highest risk, 80–100). The odds ratio between the lowest and highest risk groups was 38.50. The adjusted proportions of IA patients in the higher and highest risk groups were 26.7% and 44.5%, respectively. The median risk scores among IA patients and normal participants were 74 and 54, respectively. The optimal cut-off risk score was 60.5 with an area under the curve of 0.70.Conclusion We showed the clinical efficacy and validity of a prediction algorithm for risk estimation of IA using real-world data.