Background: The World Health Organization has declared the end of the coronavirus disease 2019 (COVID-19) public health emergency. However, this did not indicate the end of COVID-19. Several months after the infection, numerous patients complain of respiratory or nonspecific symptoms; this condition is called long COVID. Even patients with mild COVID-19 can experience long COVID, thus the burden of long COVID remains considerable. Therefore, we conducted this study to comprehensively analyze the effects of long COVID using multi-faceted assessments. Materials and Methods: We conducted a prospective cohort study involving patients diagnosed with COVID-19 between February 2020 and September 2021 in six tertiary hospitals in Korea. Patients were followed up at 1, 3, 6, 12, 18, and 24 months after discharge. Long COVID was defined as the persistence of three or more COVID-19-related symptoms. The primary outcome of this study was the prevalence of long COVID after the period of COVID-19. Results: During the study period, 290 patients were enrolled. Among them, 54.5 and 34.6% experienced long COVID within 6 months and after more than 18 months, respectively. Several patients showed abnormal results when tested for post-traumatic stress disorder (17.4%) and anxiety (31.9%) after 18 months. In patients who underwent follow-up chest computed tomography 18 months after COVID-19, abnormal findings remained at 51.9%. Males (odds ratio [OR], 0.17; 95% confidence interval [CI], 0.05–0.53; P=0.004) and elderly (OR, 1.04; 95% CI, 1.00–1.09; P=0.04) showed a significant association with long COVID after 12–18 months in a multivariable logistic regression analysis. Conclusion Many patients still showed long COVID after 18 months post SARS-CoV-2 infection. When managing these patients, the assessment of multiple aspects is necessary.

Background: The World Health Organization has declared the end of the coronavirus disease 2019 (COVID-19) public health emergency. However, this did not indicate the end of COVID-19. Several months after the infection, numerous patients complain of respiratory or nonspecific symptoms; this condition is called long COVID. Even patients with mild COVID-19 can experience long COVID, thus the burden of long COVID remains considerable. Therefore, we conducted this study to comprehensively analyze the effects of long COVID using multi-faceted assessments. Materials and Methods: We conducted a prospective cohort study involving patients diagnosed with COVID-19 between February 2020 and September 2021 in six tertiary hospitals in Korea. Patients were followed up at 1, 3, 6, 12, 18, and 24 months after discharge. Long COVID was defined as the persistence of three or more COVID-19-related symptoms. The primary outcome of this study was the prevalence of long COVID after the period of COVID-19. Results: During the study period, 290 patients were enrolled. Among them, 54.5 and 34.6% experienced long COVID within 6 months and after more than 18 months, respectively. Several patients showed abnormal results when tested for post-traumatic stress disorder (17.4%) and anxiety (31.9%) after 18 months. In patients who underwent follow-up chest computed tomography 18 months after COVID-19, abnormal findings remained at 51.9%. Males (odds ratio [OR], 0.17; 95% confidence interval [CI], 0.05–0.53; P=0.004) and elderly (OR, 1.04; 95% CI, 1.00–1.09; P=0.04) showed a significant association with long COVID after 12–18 months in a multivariable logistic regression analysis. Conclusion Many patients still showed long COVID after 18 months post SARS-CoV-2 infection. When managing these patients, the assessment of multiple aspects is necessary.

Background: The World Health Organization has declared the end of the coronavirus disease 2019 (COVID-19) public health emergency. However, this did not indicate the end of COVID-19. Several months after the infection, numerous patients complain of respiratory or nonspecific symptoms; this condition is called long COVID. Even patients with mild COVID-19 can experience long COVID, thus the burden of long COVID remains considerable. Therefore, we conducted this study to comprehensively analyze the effects of long COVID using multi-faceted assessments. Materials and Methods: We conducted a prospective cohort study involving patients diagnosed with COVID-19 between February 2020 and September 2021 in six tertiary hospitals in Korea. Patients were followed up at 1, 3, 6, 12, 18, and 24 months after discharge. Long COVID was defined as the persistence of three or more COVID-19-related symptoms. The primary outcome of this study was the prevalence of long COVID after the period of COVID-19. Results: During the study period, 290 patients were enrolled. Among them, 54.5 and 34.6% experienced long COVID within 6 months and after more than 18 months, respectively. Several patients showed abnormal results when tested for post-traumatic stress disorder (17.4%) and anxiety (31.9%) after 18 months. In patients who underwent follow-up chest computed tomography 18 months after COVID-19, abnormal findings remained at 51.9%. Males (odds ratio [OR], 0.17; 95% confidence interval [CI], 0.05–0.53; P=0.004) and elderly (OR, 1.04; 95% CI, 1.00–1.09; P=0.04) showed a significant association with long COVID after 12–18 months in a multivariable logistic regression analysis. Conclusion Many patients still showed long COVID after 18 months post SARS-CoV-2 infection. When managing these patients, the assessment of multiple aspects is necessary.

Purpose: Most bee sting injuries are benign, although sometimes they can result in life threatening outcomes, such as anaphylaxis and death. The purpose of this study was to investigate the epidemiologic status of bee sting injuries in Korea and to identify risk factors associated with severe systemic reactions (SSRs). Materials and Methods: Cases were extracted from a multicenter retrospective registry for patients who had visited emergency departments (EDs) for bee sting injuries. SSRs were defined as hypotension or altered mental status upon ED arrival, hospitalization, or death. Patient demographics and injury characteristics were compared between SSR and non-SSR groups. Logistic regression was performed to identify risk factors for bee sting-associated SSRs, and the characteristics of fatality cases were summarized. Results: Among the 9673 patients with bee sting injuries, 537 had an SSR and 38 died. The most frequent injury sites included the hands and head/face. Logistic regression analysis revealed that the occurrence of SSRs was associated with male sex [odds ratio (95% confidence interval); 1.634 (1.133–2.357)] and age [1.030 (1.020–1.041)]. Additionally, the risk of SSRs from trunk and head/ face stings was high [2.858 (1.405–5.815) and 2.123 (1.333–3.382), respectively]. Bee venom acupuncture [3.685 (1.408–9.641)] and stings in the winter [4.573 (1.420–14.723)] were factors that increased the risk of SSRs. Conclusion Our findings emphasize the need for implementing safety policies and education on bee sting-related incidents to protect high-risk groups.

Background: Human breast milk is essential and provides irreplaceable nutrients for early humans. However, breastfeeding is not easy for various reasons in medical institution environments. Therefore, in order to improve the breastfeeding environment, we investigated the difficult reality of breastfeeding through questionnaire responses from medical institution workers. Methods: A survey was conducted among 179 medical institution workers with experience in childbirth within the last five years. The survey results of 175 people were analyzed, with incoherent answers excluded. Results: Of the 175 people surveyed, a total of 108 people (61.7%) worked during the day, and 33 people (18.9%) worked in three shifts. Among 133 mothers who stayed with their babies in the same nursing room, 111 (93.3%) kept breastfeeding for more than a month, but among those who stayed apart, only 10 (71.4%) continued breastfeeding for more than a month (P = 0.024). Ninety-five (88.0%) of daytime workers, 32 (94.1%) two-shift workers, and 33 (100%) three-shift workers continued breastfeeding for more than a month (P = 0.026). Workers in general hospitals tended to breastfeed for significantly longer than those that worked in tertiary hospitals (P = 0.003). A difference was also noted between occupation categories (P = 0.019), but a more significant difference was found in the comparison between nurses and doctors (P = 0.012). Longer breastfeeding periods were noted when mothers worked three shifts (P = 0.037). Depending on the period planned for breastfeeding prior to childbirth, the actual breastfeeding maintenance period after birth showed a significant difference (P = 0.002). Of 112 mothers who responded to the question regarding difficulties in breastfeeding after returning to work, 87 (77.7%) mentioned a lack of time caused by being busy at work, 82 (73.2%) mentioned the need for places and appropriate circumstances. Conclusion In medical institutions, it is recommended that environmental improvements in medical institutions, the implementation of supporting policies, and the provision of specialized education on breastfeeding are necessary to promote breastfeeding.

Purpose: Access block due to the lack of hospital beds causes crowding of emergency departments (ED). We initiated the “boarding restriction protocol” that limits the time of stay in the ED for patients awaiting hospitalization to 24 hours from arrival. The purpose of this study was to determine the effect of the boarding restriction protocol on ED crowding. Materials and Methods: The primary outcome was ED occupancy rate, which was calculated as the ratio of the number of occupying patients to the total number of ED beds. Time factors, such as length of stay (LOS), treatment time, and boarding time, were investigated. Results: The mean of the ED occupancy rate decreased from 1.532±0.432 prior to implementation of the protocol to 1.273±0.353 after (p<0.001). According to time series analysis, the absolute effect caused by the protocol was -0.189 (-0.277 to -0.110) (p=0.001). The proportion of patients with LOS exceeding 24 hours decreased from 7.6% to 4.0% (p<0.001). Among admitted patients, ED LOS decreased from 770.7 (421.4–1587.1) minutes to 630.2 (398.0–1156.8) minutes (p<0.001); treatment time increased from 319.6 (198.5–482.8) minutes to 344.7 (213.4–519.5) minutes (p<0.001); and boarding time decreased from 298.9 (109.5–1149.0) minutes to 204.1 (98.7–545.7) minutes (p<0.001). In pre-protocol period, boarding patients accumulated in the ED during the weekdays and resolved on Friday, but this pattern was alleviated in post-period. Conclusion The boarding restriction protocol was effective in alleviating ED crowding by reducing the accumulation of boarding patients in the ED during the weekdays

Objective: It is important to identify high-risk elderly patients in the emergency department (ED), and various screening tools should be used. This study aimed to find the most appropriate tool by comparing frailty screening tools used in the ED. Methods: The authors searched PubMed, EMBASE, Cochrane library, and KoreaMed databases for medical literature. Two or more frailty screening tools were studied. Sensitivities and values of the area under the receiver operating characteristic curve of each tool used in individual studies were compared. Results: After the screening process, six studies using 12 tools were selected. Most of the tools had low sensitivities. The sensitivities were 90% or more in case of the Clinical Frailty Scale (CFS) and Program of Research to Integrate Services for the Maintenance of Autonomy (PRISMA-7). Seniors at Risk (ISAR) tools for frailty screening, Vulnerable Elders Survey (VES-13) and Geriatric (G8) tools were identified for predicting postoperative mortality, and CFS, Fried and Stable, Unstable, Help to walk, Bedbound (SUHB) tools were used for determining bad composite outcomes. The areas under the curve values predicting outcome were as follows: 0.63-0.67 for death, 0.52-0.64 for postoperative death, 0.52-0.68 for postoperative adverse outcome, 0.55-0.64 for poor prognosis, 0.65-0.69 for activity daily living disability, 0.66-0.78 for functional decline, 0.58-0.61 for hospitalization, 0.57-0.59 for fall, and 0.77-0.91 for frailty screening. Conclusion It was difficult to select the most appropriate tool among the 12 frailty tools included in this review. However, Fatigue, Resistance, Ambulation, Illnesses, Loss of weight (FRAIL), Study of Osteoporotic Fracture (SOF), CFS, VES-13, and PRISMA-7 were relatively useful in the ED.