Background: The coronavirus disease 2019 (COVID-19) pandemic and the consequent social distancing period are thought to have influenced the incidence of osteoporotic fracture in various ways, but the exact changes have not yet been well elucidated. The purpose of this study was to investigate the impact of the COVID-19 pandemic on the incidence of osteoporotic fracture using a nationwide cohort. Methods: The monthly incidence rates of vertebral; hip; and non-vertebral, non-hip fractures were collected from a nationwide database of the Korean National Health Insurance Review and Assessment from July 2016 to June 2021. Segmented regression models were used to assess the change in levels and trends in the monthly incidence of osteoporotic fractures. Results: There was a step decrease in the incidence of vertebral fractures for both males (6.181 per 100,000, P=0.002) and females (19.299 per 100,000, P=0.006). However, there was a negative trend in the incidence of hip fracture among both males (-0.023 per 100,000 per month, P=0.023) and females (-0.032 per 100,000 per month, P=0.019). No impact of COVID-19-related social distancing was noted. Conclusions In conclusion, during the early days of the COVID-19 pandemic, vertebral fracture incidence considerably decreased with the implementation of social distancing measures.

No abstract available.
Aged, 80 and over ; Anti-Bacterial Agents/therapeutic use ; Community-Acquired Infections/diagnosis/*microbiology/therapy ; Debridement ; Drainage ; Female ; Genotype ; Humans ; Methicillin-Resistant Staphylococcus aureus/classification/genetics/*isolation & purification ; Microbial Sensitivity Tests ; Republic of Korea ; Staphylococcal Infections/diagnosis/*microbiology/therapy ; Treatment Outcome

OBJECTIVES: To successfully introduce an Internet of Things (IoT) system in the hospital environment, this study aimed to identify issues that should be considered while implementing an IoT based on a user demand survey and practical experiences in implementing IoT environment monitoring systems. METHODS: In a field test, two types of IoT monitoring systems (on-premises and cloud) were used in Department of Laboratory Medicine and tested for approximately 10 months from June 16, 2016 to April 30, 2017. Information was collected regarding the issues that arose during the implementation process. RESULTS: A total of five issues were identified: sensing and measuring, transmission method, power supply, sensor module shape, and accessibility. CONCLUSIONS: It is expected that, with sufficient consideration of the various issues derived from this study, IoT monitoring systems can be applied to other areas, such as device interconnection, remote patient monitoring, and equipment/environmental monitoring.
Electric Power Supplies ; Environmental Monitoring ; Hospitals, General* ; Internet ; Methods ; Monitoring, Physiologic

The aim of this study was to examine the feasibility of the Smart dynamometer as a rehabilitation exercise device in a daily care by comparing with the existing medical devices. We used and analyzed clinical and measurement data of breast cancer survivors who have used Smart dynamometer during their rehabilitation after breast cancer surgery. The Smart dynamometer was compared with the two existing devices of Takei dynamometer and surface electromyography (sEMG) that were used in routine care, respectively. Three key components of the rehabilitation exercise devices were analyzed to validate the feasibility of the Smart dynamometer: grip strength, reaction time, and grip endurance time. Pearson's correlation analysis was performed to compare the statistical significance between the devices. The data of 12 and 15 female breast cancer patients were analyzed for comparing the Smart dynamometer with Takei dynamometer and sEMG, respectively. There was a very weak correlation between the maximum values from the Takei and the Smart dynamometers in the affected and non-affected arms of breast cancer patients (r = 0.5321, 0.4733). Comparisons of 3 features between the Smart dynamometer and sEMG showed that there were strong positive correlations for both reaction time and endurance time in the affected and non-affected arms (r > 0.9). The feasibility of the Smart dynamometer for the possible use in a daily rehabilitation exercise was partially verified. Moreover, since the Smart dynamometer was highly correlated with time-related variables, it was important and significant to measure both grip strength and time-related information.
Arm ; Breast Neoplasms ; Breast ; Electromyography ; Feasibility Studies ; Female ; Hand Strength ; Humans ; Reaction Time ; Rehabilitation ; Self Care ; Survivors

Background: As society becomes more complex, the incidence of mandibular fractures is increasing. This study aimed to analyze the incidence and type and identify etiological factors of mandibular fractures to use them in future treatments.Material and methodsData were collected from 224 patients who visited the department of oral and maxillofacial surgery at the Kyung Hee Medical Center dental hospital during a 6-year period (2016 to 2021). A logistic regression model was used for data analysis. Results: In a total of 224 patients, 362 fractures were appeared. The average age of the patients was 34.1 years, with the highest incidence in the 20s. And the ratio between male and female was 4.09:1. Symphysis fractures were the most prevalent of all patients (52.7%), followed by unilateral condyle (37.1%), angle (36.2%), bilateral condyle (9.4%), body (8%), and coronoid (2.2%). The most common cause of fracture was daily-life activity (57.6%), followed by violence (30.4%), traffic accidents (8.5%), and syncope (3.6%). Patients with symphysis fracture were at low risk (OR < 1) of angle, body, and unilateral condyle fractures. Similarly, patients with unilateral fracture were at low risk (OR < 1) of symphysis, angle, body, and others site fractures. In contrast, patient with bilateral condyle fracture were at high risk (OR > 1) of coronoid fractures. And younger patients were high risk of mandibular angle fractures. Conclusion Through this study, it was confirmed that etiological factors of mandibular fractures were like those of previous studies.

Background: This review explores the discriminative ability of fracture risk assessment tool (FRAX) in major osteoporotic fracture (MOF) and hip fracture (HF) risk prediction and the densitometric diagnosis of osteoporosis in Asian populations. Methods: We systematically searched the EMBASE, Cochrane, and PubMed databases from the earliest indexing date to January 2024. Studies were included if FRAX was used to identify future osteoporotic fractures or a densitometric diagnosis of osteoporosis in an Asian population and reported the area under the curve (AUC) values. Meta-analyses were conducted after quality assessment for AUC with 95% confidence intervals across the following categories: standard FRAX without/with bone mineral density (BMD), adjusted FRAX, and BMD alone for fracture prediction, as well as standard FRAX for densitometric diagnosis of osteoporosis. Results: A total of 42 studies were included. The AUC values for predicting fracture risk using FRAX-MOF with BMD (0.73 [0.70–0.77]) was highest compared to FRAX-MOF without BMD (0.72 [0.66–0.77]), and adjusted FRAX-MOF (0.71 [0.65–0.77]). The AUC values for predicting fracture risk using FRAX-HF with BMD (0.77 [0.71–0.83]) was highest compared to FRAX-HF without BMD (0.72 [0.65–0.80]), and adjusted FRAX-HF (0.75 [0.63–0.86]). The AUC values for BMD alone (0.68 [0.62–0.73]) was lowest for fracture prediction. The AUC values for identifying a densitometric diagnosis of osteoporosis was 0.77 [0.70–0.84] and 0.76 [0.67-0.86] using FRAX-MOF and FRAX-HF, respectively. Conclusions FRAX with BMD tends to perform more reliably in predicting HF compared to MOF in Asia. However, its accuracy in predicting fracture risk in Asian populations can be improved through region-specific, long-term epidemiological data.

Background: This review explores the discriminative ability of fracture risk assessment tool (FRAX) in major osteoporotic fracture (MOF) and hip fracture (HF) risk prediction and the densitometric diagnosis of osteoporosis in Asian populations. Methods: We systematically searched the EMBASE, Cochrane, and PubMed databases from the earliest indexing date to January 2024. Studies were included if FRAX was used to identify future osteoporotic fractures or a densitometric diagnosis of osteoporosis in an Asian population and reported the area under the curve (AUC) values. Meta-analyses were conducted after quality assessment for AUC with 95% confidence intervals across the following categories: standard FRAX without/with bone mineral density (BMD), adjusted FRAX, and BMD alone for fracture prediction, as well as standard FRAX for densitometric diagnosis of osteoporosis. Results: A total of 42 studies were included. The AUC values for predicting fracture risk using FRAX-MOF with BMD (0.73 [0.70–0.77]) was highest compared to FRAX-MOF without BMD (0.72 [0.66–0.77]), and adjusted FRAX-MOF (0.71 [0.65–0.77]). The AUC values for predicting fracture risk using FRAX-HF with BMD (0.77 [0.71–0.83]) was highest compared to FRAX-HF without BMD (0.72 [0.65–0.80]), and adjusted FRAX-HF (0.75 [0.63–0.86]). The AUC values for BMD alone (0.68 [0.62–0.73]) was lowest for fracture prediction. The AUC values for identifying a densitometric diagnosis of osteoporosis was 0.77 [0.70–0.84] and 0.76 [0.67-0.86] using FRAX-MOF and FRAX-HF, respectively. Conclusions FRAX with BMD tends to perform more reliably in predicting HF compared to MOF in Asia. However, its accuracy in predicting fracture risk in Asian populations can be improved through region-specific, long-term epidemiological data.

Background: This review explores the discriminative ability of fracture risk assessment tool (FRAX) in major osteoporotic fracture (MOF) and hip fracture (HF) risk prediction and the densitometric diagnosis of osteoporosis in Asian populations. Methods: We systematically searched the EMBASE, Cochrane, and PubMed databases from the earliest indexing date to January 2024. Studies were included if FRAX was used to identify future osteoporotic fractures or a densitometric diagnosis of osteoporosis in an Asian population and reported the area under the curve (AUC) values. Meta-analyses were conducted after quality assessment for AUC with 95% confidence intervals across the following categories: standard FRAX without/with bone mineral density (BMD), adjusted FRAX, and BMD alone for fracture prediction, as well as standard FRAX for densitometric diagnosis of osteoporosis. Results: A total of 42 studies were included. The AUC values for predicting fracture risk using FRAX-MOF with BMD (0.73 [0.70–0.77]) was highest compared to FRAX-MOF without BMD (0.72 [0.66–0.77]), and adjusted FRAX-MOF (0.71 [0.65–0.77]). The AUC values for predicting fracture risk using FRAX-HF with BMD (0.77 [0.71–0.83]) was highest compared to FRAX-HF without BMD (0.72 [0.65–0.80]), and adjusted FRAX-HF (0.75 [0.63–0.86]). The AUC values for BMD alone (0.68 [0.62–0.73]) was lowest for fracture prediction. The AUC values for identifying a densitometric diagnosis of osteoporosis was 0.77 [0.70–0.84] and 0.76 [0.67-0.86] using FRAX-MOF and FRAX-HF, respectively. Conclusions FRAX with BMD tends to perform more reliably in predicting HF compared to MOF in Asia. However, its accuracy in predicting fracture risk in Asian populations can be improved through region-specific, long-term epidemiological data.

Background: This study aimed to describe the maternal, obstetrical, and neonatal outcomes in pregnant women with coronavirus disease 2019 (COVID-19) and identify the predictors associated with the severity of COVID-19. Methods: This multicenter observational study included consecutive pregnant women admitted because of COVID-19 confirmed using reverse transcriptase-polymerase chain reaction (RT-PCR) test at 15 hospitals in the Republic of Korea between January 2020 and December 2021. Results: A total of 257 women with COVID-19 and 62 newborns were included in this study. Most of the patients developed this disease during the third trimester. Nine patients (7.4%) developed pregnancy-related complications. All pregnant women received inpatient treatment, of whom 9 (3.5%) required intensive care, but none of them died. The gestational age at COVID-19 diagnosis (odds ratio [OR], 1.096, 95% confidence interval [CI], 1.04–1.15) and parity (OR, 1.703, 95% CI, 1.13–2.57) were identified as significant risk factors of severe diseases. Among women who delivered, 78.5% underwent cesarean section. Preterm birth (38.5%), premature rupture of membranes (7.7%), and miscarriage (4.6%) occurred, but there was no stillbirth or neonatal death. The RT-PCR test of newborns’ amniotic fluid and umbilical cord blood samples was negative for severe acute respiratory syndrome coronavirus 2. Conclusion At the time of COVID-19 diagnosis, gestational age and parity of pregnant women were the risk factors of disease severity. Vertical transmission of COVID-19 was not observed, and maternal severity did not significantly affect the neonatal prognosis.