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Background: Data on antimicrobial use at the national level is crucial to establish domestic antimicrobial stewardship policies and enable medical institutions to benchmark against each other. This study aimed to analyze antimicrobial use in Korean hospitals. Methods: We investigated the antimicrobials prescribed in Korean hospitals between 2018 and 2021, using data from the Health Insurance Review and Assessment. Primary care hospitals (PCHs), secondary care hospitals (SCHs), and tertiary care hospitals (TCHs) were included in this analysis. Antimicrobials were categorized according to the Korea National Antimicrobial Use Analysis System (KONAS) classification, which is suitable for measuring antimicrobial use in Korean hospitals. Results: Out of more than 1,900 hospitals, PCHs and TCHs represented the largest and lowest percentage of hospitals, respectively. The most frequently prescribed antimicrobial in 2021 was piperacillin/β-lactamase inhibitor (9.3%) in TCHs, ceftriaxone (11.0%) in SCHs, and cefazedone (18.9%) in PCHs. Between 2018 and 2021, the most used antimicrobial class according to the KONAS classification was ‘broad-spectrum antibacterial agents predominantly used for community-acquired infections’ in TCHs and SCHs, and 'narrow spectrum beta-lactam agents' in PCH. Total consumption of antimicrobials has decreased from 951.7 to 929.9 days of therapy (DOT)/1,000 patient-days in TCHs and from 817.8 to 752.2 DOT/1,000 patient-days in SCHs during study period, but not in PCHs (from 504.3 to 527.2 DOT/1,000 patient-days). Moreover, in 2021, while use of reserve antimicrobials has decreased from 13.6 to 10.7 DOT/1,000 patient-days in TCHs and from 4.6 to 3.3 DOT/1,000 patient-days in SCHs, it has increased from 0.7 to 0.8 DOT/1,000 patient-days in PCHs. Conclusion: This study confirms that antimicrobial use differs by hospital type in Korea. Recent increases of use of antimicrobials, including reserve antimicrobials, in PCHs reflect the challenges that must be addressed.
Commodity spot prices tend to revert to some long-term mean level and most commodity derivatives are based on futures prices, not on spot prices. So, we consider spread options on futures instead of spot or spot index, where the log spot price follows a mean-reverting process. The volatility of the mean-reverting process is driven by two different (fast and slow) scale factors. We use asymptotic analysis to obtain a closed-form approximation of the futures prices and a closed-form formula for the approximate prices of spread options on the futures. The overall improvement of our analytic formula over the classical Kirk–Bjerksund–Sternsland (KBS) formula is discussed via numerical experiments.
Predicting the course of depression is necessary for personalized treatment. Impaired glucose metabolism (IGM) was introduced as a promising depression biomarker, but no consensus was made. This study aimed to predict IGM at the time of depression diagnosis and examine the relationship between long-term prognosis and predicted results.
Methods
Clinical data were extracted from four electronic health records in South Korea. The study population included patients with depression, and the outcome was IGM within 1 year. One database was used to develop the model using three algorithms. External validation was performed using the best algorithm across the three databases. The area under the curve (AUC) was calculated to determine the model’s performance. Kaplan–Meier and Cox survival analyses of the risk of hospitalization for depression as the long-term outcome were performed. A meta-analysis of the long-term outcome was performed across the four databases.
Results
A prediction model was developed using the data of 3,668 people, with an AUC of 0.781 with least absolute shrinkage and selection operator (LASSO) logistic regression. In the external validation, the AUCs were 0.643, 0.610, and 0.515. Through the predicted results, survival analysis and meta-analysis were performed; the hazard ratios of risk of hospitalization for depression in patients predicted to have IGM was 1.20 (95% confidence interval [CI] 1.02–1.41, p = 0.027) at a 3-year follow-up.
Conclusions
We developed prediction models for IGM occurrence within a year. The predicted results were related to the long-term prognosis of depression, presenting as a promising IGM biomarker related to the prognosis of depression.
Mood disorders require consistent management of symptoms to prevent recurrences of mood episodes. Circadian rhythm (CR) disruption is a key symptom of mood disorders to be proactively managed to prevent mood episode recurrences. This study aims to predict impending mood episodes recurrences using digital phenotypes related to CR obtained from wearable devices and smartphones.
Methods
The study is a multicenter, nationwide, prospective, observational study with major depressive disorder, bipolar disorder I, and bipolar II disorder. A total of 495 patients were recruited from eight hospitals in South Korea. Patients were followed up for an average of 279.7 days (a total sample of 75 506 days) with wearable devices and smartphones and with clinical interviews conducted every 3 months. Algorithms predicting impending mood episodes were developed with machine learning. Algorithm-predicted mood episodes were then compared to those identified through face-to-face clinical interviews incorporating ecological momentary assessments of daily mood and energy.
Results
Two hundred seventy mood episodes recurred in 135 subjects during the follow-up period. The prediction accuracies for impending major depressive episodes, manic episodes, and hypomanic episodes for the next 3 days were 90.1, 92.6, and 93.0%, with the area under the curve values of 0.937, 0.957, and 0.963, respectively.
Conclusions
We predicted the onset of mood episode recurrences exclusively using digital phenotypes. Specifically, phenotypes indicating CR misalignment contributed the most to the prediction of episodes recurrences. Our findings suggest that monitoring of CR using digital devices can be useful in preventing and treating mood disorders.
In this review, we introduce our recent applications of deep learning to solar and space weather data. We have successfully applied novel deep learning methods to the following applications: (1) generation of solar farside/backside magnetograms and global field extrapolation based on them, (2) generation of solar UV/EUV images from other UV/EUV images and magnetograms, (3) denoising solar magnetograms using supervised learning, (4) generation of UV/EUV images and magnetograms from Galileo sunspot drawings, (5) improvement of global IRI TEC maps using IGS TEC ones, (6) one-day forecasting of global TEC maps through image translation, (7) generation of high-resolution magnetograms from Ca II K images, (8) super-resolution of solar magnetograms, (9) flare classification by CNN and visual explanation by attribution methods, and (10) forecasting GOES solar X-ray profiles. We present major results and discuss them. We also present future plans for integrated space weather models based on deep learning.
The explosive outbreak of COVID-19 led to a shortage of medical resources, including isolation rooms in hospitals, healthcare workers (HCWs) and personal protective equipment. Here, we constructed a new model, non-contact community treatment centres to monitor and quarantine asymptomatic and mildly symptomatic COVID-19 patients who recorded their own vital signs using a smartphone application. This new model in Korea is useful to overcome shortages of medical resources and to minimise the risk of infection transmission to HCWs.
The 14C peak in AD 775 (M12) has been measured and confirmed globally in several studies since it was first measured in annual tree rings by Miyake et al. (2012). However, M12 data measurements in early- and latewood are limited. This paper presents the Δ14C values in early- and latewood from AD 762–776 Zelkova serrata tree rings from Bangu-dong, Ulsan, South Korea (35°33′N, 129°20′E). The results indicate no early rise in Δ14C values in the latewood of AD 774 in this sample located at mid-latitude. A comparison of the results of this and previous studies suggests latitude dependence (Büntgen et al. 2018); that is, the early rise of Δ14C in AD 774 was not observed at mid-latitudes in South Korea but was observed at high latitudes in Finland. The half-oxidation time of 14C was estimated from a detailed analysis of a small bomb peak in AD 1962. Based on the half-oxidation time, the Δ14C rise in the latewood, but not in the earlywood, of AD 774 in Finland, and the absence of a Δ14C rise in both the early- and latewood of AD 774 in South Korea, the 14C spike was estimated to have been produced from late April to mid-June in AD 774.
There is limited evidence on the interaction by alcohol dehydrogenase 2 (ADH1B) (rs1229984) and aldehyde dehydrogenase 2 (ALDH2) (rs671) regarding the associations of alcohol and a methyl diet (low folate and high alcohol intake) with cancer risk, partly because of rare polymorphisms in Western populations.
Design:
In a case–control study, we estimated the ORs and 95 % CIs to evaluate the associations of ADH1B and ALDH2 genotypes with colorectal cancer (CRC) and the joint association between methyl diets and ADH1B and ALDH2 polymorphisms with CRC risk using logistic regression models.
Setting:
A hospital-based case–control study.
Participants:
In total, 1001 CRC cases and 899 cancer-free controls admitted to two university hospitals.
Results:
We found that alcohol intake increased the risk of CRC; OR (95 % CI) was 2·02 (1·41, 2·87) for ≥60 g/d drinkers compared with non-drinkers (Ptrend < 0·001). The associations for two polymorphisms with CRC were not statistically significant. However, we found a potential interaction of ALDH2 with methyl diets and CRC. We observed a 9·08-fold (95 % CI 1·93, 42·60) higher risk of CRC for low-methyl diets compared with high-methyl diets among individuals with an A allele of ALDH2, but the association was not apparent among those with ALDH2 GG (Pinteraction = 0·02).
Conclusions:
Our data support the evidence that gene–methyl diet interactions may be involved in CRC risk in East Asian populations, showing that a low-methyl diet increased the risk of CRC among individuals with an A allele of ALDH2.
Bovine spongiform encephalopathy (BSE) involves insertion/deletion (in/del) polymorphisms in the prion protein gene (PRNP) promoter region that are associated with vulnerability to disease progression. Recently, a second member of the prion gene family, prion-like protein gene (PRND), has been reported to show the PRND R132Q polymorphism, which is associated with the susceptibility to BSE in German Fleckvieh breeds. The objective of this study was to examine the genotype, allele, and haplotype frequencies of PRND gene in Korean cattle and evaluate their susceptibility to BSE. We did this in 277 Korean native cattle (Hanwoo) and 124 Korean dairy cattle (Holstein) by direct sequencing and compared the R132Q genotype frequency between BSE-affected German cattle and Korean cattle. The results indicated a total of 5 single nucleotide polymorphisms (SNPs) including PRND c.149G > A (p.50Arg > His; R50H), PRND c.285C > T (C4819T), PRND c.395G > A (p.132Arg > Gln; R132Q) and PRND c.528T > A (T5063A) in the open reading frame (ORF) and c.602C > G in the 3′ untranslated region (UTR) of exon 2 in Korean Holstein and Hanwoo cattle. Except for c.149G > A, the remaining 4 SNPs showed significantly different genotype and allele frequencies between the Korean Holstein and Hanwoo (P < 0·01). There were no significant differences in genotype distribution of c.395G > A SNP between BSE-affected German and Korean Holstein cattle (P = 0·6778), but a significant difference was detected between BSE-affected German cattle and Hanwoo cattle (P = 0·0028). The results suggest that Hanwoo cattle may possess a relatively more BSE-resistant genotype than Korean Holstein cattle.
We trace Sn nanoparticles (NPs) produced from SnO2 nanotubes (NTs) during lithiation initialized by high energy e-beam irradiation. The growth dynamics of Sn NPs is visualized in liquid electrolytes by graphene liquid cell transmission electron microscopy. The observation reveals that Sn NPs grow on the surface of SnO2 NTs via coalescence and the final shape of agglomerated NPs is governed by surface energy of the Sn NPs and the interfacial energy between Sn NPs and SnO2 NTs. Our result will likely benefit more rational material design of the ideal interface for facile ion insertion.
A vertebrate burrow-bearing layer of late Pleistocene age is commonly found at many Paleolithic archaeological sites in Korea. The burrows are straight to slightly curved in horizontal (plan) view and gently inclined in lateral (sectional) view. They are interpreted as having been produced by rodent-like mammals based on their size and architecture. The significance of such burrow-bearing layers as a characteristic stratigraphic marker unit is demonstrated by high burrow abundance, consistent stratigraphic position, lack of stratigraphic recurrence at these sites, and widespread geographic extent. Three dating methods, tephrochronology, radiocarbon, and OSL dating, were used to infer the age of these burrow-bearing layers. The dating results indicate that they were formed between ca. 40,000 and 25,000 yr (MIS 3−2), and this suggests that this layer can be used as a stratigraphic time-marker in late Pleistocene paleosol sequences for this region.
Subjective memory impairment (SMI) is common among older adults. Increasing evidence suggests that SMI is a risk factor for future cognitive decline, as well as for mild cognitive impairment and dementia. Medial temporal lobe structures, including the hippocampus and entorhinal cortex, are affected in the early stages of Alzheimer's disease. The current study examined the gray matter (GM) volume and microstructural changes of hippocampal and entorhinal regions in individuals with SMI, compared with elderly control participants without memory complaints.
Methods:
A total of 45 participants (mean age: 70.31 ± 6.07 years) took part in the study, including 18 participants with SMI and 27 elderly controls without memory complaints. We compared the GM volume and diffusion tensor imaging (DTI) measures in the hippocampal and entorhinal regions between SMI and control groups.
Results:
Individuals with SMI had lower entorhinal cortical volumes than control participants, but no differences in hippocampal volume were found between groups. In addition, SMI patients exhibited DTI changes (lower fractional anisotropy (FA) and higher mean diffusivity in SMI) in the hippocampal body and entorhinal white matter compared with controls. Combining entorhinal cortical volume and FA in the hippocampal body improved the accuracy of classification between SMI and control groups.
Conclusions:
These findings suggest that the entorhinal region exhibits macrostructural as well as microstructural changes in individuals with SMI, whereas the hippocampus exhibits only microstructural alterations.
Personality may predispose family caregivers to experience caregiving differently in similar situations and influence the outcomes of caregiving. A limited body of research has examined the role of some personality traits for health-related quality of life (HRQoL) among family caregivers of persons with dementia (PWD) in relation to burden and depression.
Methods:
Data from a large clinic-based national study in South Korea, the Caregivers of Alzheimer's Disease Research (CARE), were analyzed (N = 476). Path analysis was performed to explore the association between family caregivers’ personality traits and HRQoL. With depression and burden as mediating factors, direct and indirect associations between five personality traits and HRQoL of family caregivers were examined.
Results:
Results demonstrated the mediating role of caregiver burden and depression in linking two personality traits (neuroticism and extraversion) and HRQoL. Neuroticism and extraversion directly and indirectly influenced the mental HRQoL of caregivers. Neuroticism and extraversion only indirectly influenced their physical HRQoL. Neuroticism increased the caregiver's depression, whereas extraversion decreased it. Neuroticism only was mediated by burden to influence depression and mental and physical HRQoL.
Conclusions:
Personality traits can influence caregiving outcomes and be viewed as an individual resource of the caregiver. A family caregiver's personality characteristics need to be assessed for tailoring support programs to get the optimal benefits from caregiver interventions.