Purpose: Anti-obesity medications (AOMs), along with lifestyle interventions, are effective means of inducing and maintaining weight loss in patients with obesity. Although the efficacy of AOMs has been reported, there have been no direct comparisons of these drugs. Therefore, in the present study, we aimed to compare the efficacy of all the AOMs available in Korea in a real-world setting. Patients and Methods: The body weight and composition of 205 adults treated with phentermine, phentermine/topiramate, liraglutide, naltrexone/bupropion, lorcaserin, or orlistat for at least 6 months were analyzed at 2 month intervals. The prevalence of the achievement of a ≥ 5% weight loss and the changes in body composition were compared between participants using each AOM at each visit. Results: A total of 132 (64.4%) participants achieved ≥ 5% weight loss within 6 months (prevalence of ≥ 5% weight loss after 6 months: phentermine, 87.2%; phentermine/topiramate, 67.7%; liraglutide, 58.1%; naltrexone/bupropion, 35.3%; lorcaserin, 75%; orlistat, 50%). At each visit, after adjustment for age, sex, and baseline body weight, phentermine use was associated with a significantly higher prevalence of ≥ 5% weight loss than the use of the other AOMs, except for liraglutide. There were significant differences in the body weight, body mass index and body fat mass among the AOM groups by visit (P for interaction < 0.05), but not in their waist circumference, skeletal muscle mass, percentage body fat, or visceral fat area. Conclusion: All the AOMs were effective at inducing and maintaining weight loss, in the absence of significant changes in muscle mass, over a 6 month period, and the short-term use of phentermine and the long-term use of phentermine/topiramate or liraglutide would be practical choices for the treatment of obesity. However, further, large-scale studies are necessary to confirm these findings.

Background: This study investigated the association between atherosclerosis and systemic inflammation markers, specifically the C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), in healthy middle-aged adults. Methods: A retrospective cross-sectional study was conducted on a total of 1264 Korean adults aged 40–65. We assessed these inflammatory markers and carotid metrics, such as carotid intima–media thickness (cIMT), plaque number (PN), plaque stenosis score (PSS), and plaque score (PS), using linear regression, logistic regression, and receiver operating characteristic analysis. Results: In males, the ESR and CRP were significantly correlated with the PN (p < 0.001 and p = 0.048, respectively). The ESR was correlated with the PN in females (p = 0.004). The NLR and PLR both correlated with the PS in males (p < 0.001 and p = 0.015, respectively) and females (p = 0.015 and p = 0.023, respectively). The odds ratio for the NLR as a risk factor for increased cIMT was 1.15 (95% confidence interval [CI], 1.03–2.15) for males and 1.05 (95% CI, 1.01–1.29) for females. The AUC for the NLR and PLR as a predictor for the PS showed significance in both men and women. Conclusions: Inflammatory markers, particularly the NLR and PLR, demonstrate a correlation with carotid atherosclerosis. Both the NLR and PLR hold potential as valuable surrogate markers for carotid atherosclerosis. To further substantiate their predictive efficacy, further prospective studies are needed.

This study aimed to determine whether nonalcoholic fatty liver disease (NAFLD) is an independent risk factor for CVD and to identify the most useful NAFLD diagnostic tool for predicting CVD. Data from a total of 23,376 Korean adults without established CVD were analyzed. Cardiovascular risk was calculated using the Framingham Risk Score (FRS) 2008. The presence of NAFLD was defined as moderate-to-severe fatty liver disease diagnosed by ultrasonography. Scores for fatty liver were calculated using four NAFLD scoring systems (Fatty Liver Index, FLI; Hepatic Steatosis Index, HSI; Simple NAFLD Score, SNS; Comprehensive NAFLD Score, CNS), and were compared and analyzed according to cardiovascular risk group. Using the FRS, 67.4% of participants were considered to be at low risk of CVD, 21.5% at intermediate risk, and 11.1% at high risk. As the risk of CVD increased, both the prevalence of NAFLD and the score from each NAFLD scoring system increased significantly (p < 0.001). In the unadjusted analysis, the CNS had the strongest association with high CVD risk; in the adjusted analysis, the FLI score was most strongly associated with high CVD risk. Fatty liver is an important independent risk factor for CVD. Therefore, the available NAFLD scoring systems could be utilized to predict CVD.

Background: Osteoporosis is characterized by a decrease in bone mineral density (BMD) and increased risk of fragility fractures. Senun iron level may interact with bone health status. This study investigated the correlations of BMD with serum iron level, hemoglobin level, and total iron-binding capacity (TIBC). Methods: We performed a retrospective analysis of data from the medical records of premenopausal women in South Korea. The women's BMDs and the Z scores of the BMDs were verified using dual-energy X-ray absorption. The participants were stratified into quartiles for analyses of the associations of BMD with serurn iron level, TIBC, and hemoglobin level. Results: A simple linear regression analysis revealed associations of changes in BMD with iron level (beta=-0.001, standard error [SE]=0.001, P<0.001), hemoglobin level (beta=0.015, SE=0.003, P<0.001), and TIBC (beta=0.001, SE=0.001, P<0.001). This pattern was also observed in a multiple linear regression analysis. A multivariate logistic regression analysis of iron level and TIBC for low BMD revealed odds ratios of 1.005 (P<0.001) and 0.995 (P<0.001), respectively. Conclusion: This study demonstrated dear relationships of changes in BMD with serum iron level and TIBC, and thus confirms the usefulness of these markers in the clinical evaluation of iron storage and BMD in younger women.

This study aimed to compare adverse reactions following BNT162b2 and influenza vaccinations in healthcare workers. This study included healthcare workers who received the BNT162b2 vaccine and/or inactivated influenza vaccine, quadrivalent (IIV4), on 18–29 October 2021 at a tertiary hospital in Korea. IIV4 was administered and BNT162b2 was subsequently administered one week later. The participants responded to a mobile questionnaire regarding adverse events. The overall adverse reaction rates were 90.6% in the BNT162b2 + IIV4 group, 90.4% in the BNT162b2 alone group, and 44.1% in the IIV4 alone group (p < 0.001). Fever occurred in 19.5%, 26.9%, and 3.3% of participants in the BNT162b2 + IIV4, BNT162b2 alone, and IIV4 alone groups, respectively (p < 0.001). The most common local and systemic adverse reactions were injection site pain (65.0%) and fatigue (58.6%), respectively. Injection-site pain was experienced by 88.7%, 88.5%, and 37.5% of the BNT162b2 + IIV4, BNT162b2 alone, and IIV4 alone groups, respectively (p < 0.001). Fatigue was experienced by 74.8%, 78.8%, and 38.6% of the BNT162b2 + IIV4, BNT162b2 alone, and IIV4 alone groups, respectively (p < 0.001). Adverse reactions occurred at a significantly higher frequency after BNT162b2 than after IIV4. The frequency of adverse reactions one week after vaccination with IIV4 and BNT162b2 was not different from that after vaccination with BNT162b2 alone. Therefore, coadministration of influenza vaccine with BNT162b2 can be expected to be safe.

Purpose: To evaluate the results of operating an in-hospital coronavirus disease 2019 screening station on an outpatient basis and to identify the effectiveness and necessity of such a screening station. Patients and Methods: This cross-sectional study included 1345 individuals who were tested for COVID-19 using real-time reverse transcription polymerase chain reaction (RT-PCR) at an in-hospital screening station on an outpatient basis. The subjects were healthcare workers (HCWs) with suspected COVID-19 symptoms or exposure to patients with confirmed COVID-19, caregivers at the hospital for complete enumeration, and patients who were scheduled to be admitted to a nonrestricted area in the hospital or to visit for outpatient treatment, but had suspected COVID-19 symptoms. The subjects were divided and compared as follows: HCW versus non-HCW groups and RT-PCR positive versus negative groups. Results: A total of 140 had symptoms, 291 wanted to be tested, and 664 were asymptomatic but were screened. Seven subjects had positive results for COVID-19. Compared with the non-HCWs, the HCWs were younger and had a lower rate of underlying medical conditions. In addition, there were more women, individuals with exposure to confirmed cases, and individuals with symptoms or those who just wanted to be tested. The frequency of all symptoms was high among the HCWs. The results of the logistic regression analysis showed that the HCWs were significantly associated with the presence of symptoms, having an odds ratio of 23.317 (confidence interval, 15.142– 35.907L; P < 0.001). The positive group had a high rate of exposure to patients with confirmed COVID-19 and had more subjects with symptoms or those who wanted to be tested. Conclusion: In-hospital screening stations are a relatively safe way to protect and support HCWs and to reduce and manage the spread of infection within the hospital effectively during an outbreak in the community.