Exploring depressive symptom trajectories in COVID-19 patients with clinically mild condition in South Korea using remote patient monitoring: longitudinal data analysis.

Background: During the height of the COVID-19 pandemic, the Korean government temporarily allowed full scale telehealth care for safety and usability. However, limited studies have evaluated the impact of telehealth by analyzing the physical and/or mental health data of patients with COVID-19 diagnosis collected through telehealth targeting Korean population. Objective: This study aimed to identify subgroup of depressive symptom trajectories in patients with clinically mild COVID-19 using collected longitudinal data from a telehealth-based contactless clinical trial. Methods: A total of 199 patients with COVID-19 were accrued for contactless clinical trial using telehealth from March 23 to July 20, 2022. Depressive symptoms were measured using the patient health questionnaire-9 on the start day of quarantine, on the final day of quarantine, and 1 month after release from quarantine. Additionally, acute COVID-19 symptoms were assessed every day during quarantine. This study used a latent class mixed model to differentiate subgroups of depressive symptom trajectories and a logistic regression model with Firth's correction to identify associations between acute COVID-19 symptoms and the subgroups. Results: Two latent classes were identified: class 1 with declining linearity at a slow rate and class 2 with increasing linearity. Among COVID-19 symptoms, fever, chest pain, and brain fog 1 month after release from quarantine showed strong associations with class 2 (fever: OR, 19.43, 95% CI, 2.30-165.42; chest pain: OR, 6.55, 95% CI, 1.15-34.61; brain fog: OR, 7.03, 95% CI 2.57-20.95). Sleeping difficulty and gastrointestinal symptoms were also associated with class 2 (gastrointestinal symptoms: OR, 4.76, 95% CI, 1.71-14.21; sleeping difficulty: OR, 3.12, 95% CI, 1.71-14.21). Conclusion: These findings emphasize the need for the early detection of depressive symptoms in patients in the acute phase of COVID-19 using telemedicine. Active intervention, including digital therapeutics, may help patients with aggravated depressive symptoms.

Longitudinal immune kinetics of COVID-19 booster versus primary series vaccination: Insight into the annual vaccination strategy.

Background: Data on the durability of booster dose immunity of COVID-19 vaccines are relatively limited. Methods: Immunogenicity was evaluated for up to 9-12 months after the third dose of vaccination in 94 healthy adults. Results: Following the third dose, the anti-spike immunoglobulin G (IgG) antibody response against the wild-type was boosted markedly, which decreased gradually over time. However, even 9-12 months after the booster dose, both the median and geometric mean of anti-spike IgG antibody levels were higher than those measured 4 weeks after the second dose. Breakthrough infection during the Omicron-dominant period boosted neutralizing antibody titers against Omicron sublineages (BA.1 and BA.5) and the ancestral strain. T-cell immune response was efficiently induced and maintained during the study period. Conclusions: mRNA vaccine booster dose elicited durable humoral immunity for up to 1 year after the third dose and T-cell immunity was sustained during the study period, supporting an annual COVID-19 vaccination strategy.

Identification of Predictors for Clinical Deterioration in Patients With COVID-19 via Electronic Nursing Records: Retrospective Observational Study.

BACKGROUND: Few studies have used standardized nursing records with Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) to identify predictors of clinical deterioration. OBJECTIVE: This study aims to standardize the nursing documentation records of patients with COVID-19 using SNOMED CT and identify predictive factors of clinical deterioration in patients with COVID-19 via standardized nursing records. METHODS: In this study, 57,558 nursing statements from 226 patients with COVID-19 were analyzed. Among these, 45,852 statements were from 207 patients in the stable (control) group and 11,706 from 19 patients in the exacerbated (case) group who were transferred to the intensive care unit within 7 days. The data were collected between December 2019 and June 2022. These nursing statements were standardized using the SNOMED CT International Edition released on November 30, 2022. The 260 unique nursing statements that accounted for the top 90% of 57,558 statements were selected as the mapping source and mapped into SNOMED CT concepts based on their meaning by 2 experts with more than 5 years of SNOMED CT mapping experience. To identify the main features of nursing statements associated with the exacerbation of patient condition, random forest algorithms were used, and optimal hyperparameters were selected for nursing problems or outcomes and nursing procedure-related statements. Additionally, logistic regression analysis was conducted to identify features that determine clinical deterioration in patients with COVID-19. RESULTS: All nursing statements were semantically mapped to SNOMED CT concepts for "clinical finding," "situation with explicit context," and "procedure" hierarchies. The interrater reliability of the mapping results was 87.7%. The most important features calculated by random forest were "oxygen saturation below reference range," "dyspnea," "tachypnea," and "cough" in "clinical finding," and "oxygen therapy," "pulse oximetry monitoring," "temperature taking," "notification of physician," and "education about isolation for infection control" in "procedure." Among these, "dyspnea" and "inadequate food diet" in "clinical finding" increased clinical deterioration risk (dyspnea: odds ratio [OR] 5.99, 95% CI 2.25-20.29; inadequate food diet: OR 10.0, 95% CI 2.71-40.84), and "oxygen therapy" and "notification of physician" in "procedure" also increased the risk of clinical deterioration in patients with COVID-19 (oxygen therapy: OR 1.89, 95% CI 1.25-3.05; notification of physician: OR 1.72, 95% CI 1.02-2.97). CONCLUSIONS: The study used SNOMED CT to express and standardize nursing statements. Further, it revealed the importance of standardized nursing records as predictive variables for clinical deterioration in patients.

Sodium Intake Estimation in Hospital Patients Using AI-Based Imaging: Prospective Pilot Study.

BACKGROUND: Measurement of sodium intake in hospitalized patients is critical for their care. In this study, artificial intelligence (AI)-based imaging was performed to determine sodium intake in these patients. OBJECTIVE: The applicability of a diet management system was evaluated using AI-based imaging to assess the sodium content of diets prescribed for hospitalized patients. METHODS: Based on the information on the already investigated nutrients and quantity of food, consumed sodium was analyzed through photographs obtained before and after a meal. We used a hybrid model that first leveraged the capabilities of the You Only Look Once, version 4 (YOLOv4) architecture for the detection of food and dish areas in images. Following this initial detection, 2 distinct approaches were adopted for further classification: a custom ResNet-101 model and a hyperspectral imaging-based technique. These methodologies focused on accurate classification and estimation of the food quantity and sodium amount, respectively. The 24-hour urine sodium (UNa) value was measured as a reference for evaluating the sodium intake. RESULTS: Results were analyzed using complete data from 25 participants out of the total 54 enrolled individuals. The median sodium intake calculated by the AI algorithm (AI-Na) was determined to be 2022.7 mg per day/person (adjusted by administered fluids). A significant correlation was observed between AI-Na and 24-hour UNa, while there was a notable disparity between them. A regression analysis, considering patient characteristics (eg, gender, age, renal function, the use of diuretics, and administered fluids) yielded a formula accounting for the interaction between AI-Na and 24-hour UNa. Consequently, it was concluded that AI-Na holds clinical significance in estimating salt intake for hospitalized patients using images without the need for 24-hour UNa measurements. The degree of correlation between AI-Na and 24-hour UNa was found to vary depending on the use of diuretics. CONCLUSIONS: This study highlights the potential of AI-based imaging for determining sodium intake in hospitalized patients.

Decellularized brain extracellular matrix based NGF-releasing cryogel for brain tissue engineering in traumatic brain injury.

Traumatic brain injuries(TBI) pose significant challenges to human health, specifically neurological disorders and related motor activities. After TBI, the injured neuronal tissue is known for hardly regenerated and recovered to their normal neuron physiology and tissue compositions. For this reason, tissue engineering strategies that promote neuronal regeneration have gained increasing attention. This study explored the development of a novel neural tissue regeneration cryogel by combining brain-derived decellularized extracellular matrix (ECM) with heparin sulfate crosslinking that can perform nerve growth factor (NGF) release ability. Morphological and mechanical characterizations of the cryogels were performed to assess their suitability as a neural regeneration platform. After that, the heparin concnentration dependent effects of varying NGF concentrations on cryogel were investigated for their controlled release and impact on neuronal cell differentiation. The results revealed a direct correlation between the concentration of released NGF and the heparin sulfate ratio in cryogel, indicating that the cryogel can be tailored to carry higher loads of NGF with heparin concentration in cryogel that induced higher neuronal cell differentiation ratio. Furthermore, the study evaluated the NGF loaded cryogels on neuronal cell proliferation and brain tissue regeneration in vivo. The in vivo results suggested that the NGF loaded brain ECM derived cryogel significantly affects the regeneration of brain tissue. Overall, this research contributes to the development of advanced neural tissue engineering strategies and provides valuable insights into the design of regenerative cryogels that can be customized for specific therapeutic applications.

Deep learning-based long-term risk evaluation of incident type 2 diabetes using electrocardiogram in a non-diabetic population: a retrospective, multicentre study.

Background: Diabetes is a major public health concern. We aimed to evaluate the long-term risk of incident type 2 diabetes in a non-diabetic population using a deep learning model (DLM) detecting prevalent type 2 diabetes using electrocardiogram (ECG). Methods: In this retrospective study, participants who underwent health checkups at two tertiary hospitals in Seoul, South Korea, between Jan 1, 2001 and Dec 31, 2022 were included. Type 2 diabetes was defined as glucose ≥126 mg/dL or glycated haemoglobin (HbA1c) ≥ 6.5%. For survival analysis on incident type 2 diabetes, we introduced an additional variable, diabetic ECG, which is determined by the DLM trained on ECG and corresponding prevalent diabetes. It was assumed that non-diabetic individuals with diabetic ECG had a higher risk of incident type 2 diabetes than those with non-diabetic ECG. The one-dimensional ResNet-based model was adopted for the DLM, and the Guided Grad-CAM was used to localise important regions of ECG. We divided the non-diabetic group into the diabetic ECG group (false positive) and the non-diabetic ECG (true negative) group according to the DLM decision, and performed a Cox proportional hazard model, considering the occurrence of type 2 diabetes more than six months after the visit. Findings: 190,581 individuals were included in the study with a median follow-up period of 11.84 years. The areas under the receiver operating characteristic curve for prevalent type 2 diabetes detection were 0.816 (0.807-0.825) and 0.762 (0.754-0.770) for the internal and external validations, respectively. The model primarily focused on the QRS duration and, occasionally, P or T waves. The diabetic ECG group exhibited an increased risk of incident type 2 diabetes compared with the non-diabetic ECG group, with hazard ratios of 2.15 (1.82-2.53) and 1.92 (1.74-2.11) for internal and external validation, respectively. Interpretation: In the non-diabetic group, those whose ECG was classified as diabetes by the DLM were at a higher risk of incident type 2 diabetes than those whose ECG was not. Additional clinical research on the relationship between the phenotype of ECG and diabetes to support the results and further investigation with tracked data and various ECG recording systems are suggested for future works. Funding: National Research Foundation of Korea.

Nighttime Outdoor Artificial Light and Risk of Age-Related Macular Degeneration.

Importance: Light pollution's impact on human health is increasingly recognized, but its link to exudative age-related macular degeneration (EAMD) remains unclear. Objective: To investigate the association between exposure to outdoor artificial light at night (OALAN) and the risk of incident EAMD. Design, Setting, and Participants: In this nationwide population-based case-control study, all individuals 50 years or older with newly diagnosed EAMD between January 1, 2010, and December 31, 2011, were identified with reference to the Korean National Health Insurance Service registration program database for rare and intractable diseases. Birth year- and sex-matched controls (with no EAMD diagnosis until 2020) were selected at a 1:30 ratio. Data were acquired from May 1 to December 31, 2021, and analyzed from June 1 to November 30, 2022. Exposures: Mean levels of OALAN at participants' residential addresses during 2008 and 2009 were estimated using time-varying satellite data for a composite view of persistent nighttime illumination at an approximate scale of 1 km2. Main Outcomes and Measures: The hazard ratios (HRs) and 95% CIs of the association between residential OALAN and risk of incident EAMD were determined based on maximum likelihood estimation after adjusting for sociodemographic characteristics, comorbidities, and area-level risk factors (ie, nighttime traffic noise and particulate matter of aerodynamic diameter ≤10 µm in each participant's administrative district of residence). Results: A total of 126 418 participants were included in the analysis (mean [SD] age, 66.0 [7.9] years; 78 244 men [61.9%]). Of these, 4078 were patients with newly diagnosed EAMD and 122 340 were EAMD-free matched controls. In fully adjusted models, an IQR (55.8 nW/cm2/sr) increase in OALAN level was associated with an HR of 1.67 (95% CI, 1.56-1.78) for incident EAMD. The exposure-response curve demonstrated a nonlinear, concave upward slope becoming more pronounced at higher levels of light exposure (ie, at approximately 110 nW/cm2/sr). In a subgroup analysis, an IQR increase in OALAN was associated with increased risk of incident EAMD in urban areas (HR, 1.46 [95% CI, 1.33-1.61]) but not in rural areas (HR, 1.01 [95% CI, 0.84-1.22]). Conclusions and Relevance: In this nationwide population-based case-control study, higher levels of residential OALAN were associated with an increased risk of incident EAMD. Future studies with more detailed information on exposure, individual adaptive behaviors, and potential mediators are warranted.

A new exceptionally well-preserved basal actinopterygian fish in the juvenile stage from the Upper Triassic Amisan Formation of South Korea.

The study of the large paraphyletic group of extinct 'palaeoniscoid' fishes has shed light on the diversity and evolutionary history of basal actinopterygians. However, only a little ontogenetic information about 'palaeoniscoids' is known because their records in the early stages of development are scarce. Here, we report on a growth series of 'palaeoniscoids' in the juvenile stage from the Upper Triassic Amisan Formation of South Korea. Fourteen specimens, including five counterpart specimens, represent a new taxon, Megalomatia minima gen. et sp. nov., exhibiting ontogeny and exceptional preservation with the eyes possibly containing the crystalline lens, the otoliths, and the lateral line canals without covering scales. This discovery allows us to discuss the adaptations and evolution of basal actinopterygians in more detail than before. The otoliths in situ of Megalomatia support the previous interpretation that basal actinopterygians have a sagitta as the largest otolith. The trunk lateral line canal, which runs under the scales instead of passing through them, represents a plesiomorphic gnathostome trait. Notably, the large protruded eyes suggest that Megalomatia probably has binocular vision, which would have played a significant role in targeting and catching prey with the primitive jaw structure. In addition, the firstly formed skeletal elements such as the jaws, pectoral girdle, and opercular series, and the posteroanterior pattern of squamation development are likely linked to the adaptation of young individuals to increase their viability for feeding, respiration, and swimming.

Trends in Childhood Glaucoma Prevalence and Incidence in South Korea, 2002-2019: A Nationwide Population-Based Study.

PRCIS: This nationwide analysis identified the prevalence and incidence of childhood glaucoma for an 18-year period. The prevalence and incidence of primary congenital glaucoma showed increasing trends. Juvenile open-angle glaucoma, meanwhile, showed a decreasing tendency. PURPOSE: We aimed to determine the trends in the prevalence and incidence of childhood glaucoma in the entire population of South Korea. PATIENTS AND METHODS: A nationwide retrospective cohort study was performed with an age- and sex-specific population of South Korea. The Korean National Health Insurance Service (KNHIS) claims database for 2002 to 2019 was accessed to identify cases of ophthalmologist-confirmed primary childhood glaucoma (i.e., primary congenital glaucoma [PCG] and juvenile open-angle glaucoma [JOAG]). Incidence for PCG was estimated for a same-birth-year population, while that for JOAG was estimated using age- and sex-specific population figures. To verify the glaucoma cases, we also analyzed the diagnostic codes as well as any information on medication prescriptions and/or ocular-surgery history. RESULTS: During the 18-year observational period, totals of 505 and 7538 patients were diagnosed as PCG and JOAG, respectively. The mean prevalences of PCG and JOAG were 3.96±0.72 and 14.17±5.18, respectively. The prevalence of PCG showed an overall increasing trend during the study period, but the pattern was not significant (ß=0.049, P=0.143); that of JOAG, meanwhile, showed a significant decreasing tendency (ß=-0.713, P=0.001). PCG prevalence showed no difference between urban and rural areas, but JOAG showed a higher prevalence in rural areas (P<0.001). As for mean incidence, the rates for PCG and JOAG were 1.54±0.49 and 5.02±1.95 (per 100,000 person-years), respectively, and were higher in males (P<0.001 and P=0.013). CONCLUSION: This study identified childhood glaucoma prevalence and incidence in a general population of East Asian ethnicity. This data could help to promote better understanding of the typical epidemiological features and clinical courses of childhood glaucoma patients.

In-hospital real-time prediction of COVID-19 severity regardless of disease phase using electronic health records.

Coronavirus disease 2019 (COVID-19) has strained healthcare systems worldwide. Predicting COVID-19 severity could optimize resource allocation, like oxygen devices and intensive care. If machine learning model could forecast the severity of COVID-19 patients, hospital resource allocation would be more comfortable. This study evaluated machine learning models using electronic records from 3,996 COVID-19 patients to forecast mild, moderate, or severe disease up to 2 days in advance. A deep neural network (DNN) model achieved 91.8% accuracy, 0.96 AUROC, and 0.90 AUPRC for 2-day predictions, regardless of disease phase. Tree-based models like random forest achieved slightly better metrics (random forest: 94.1% of accuracy, 0.98 AUROC, 0.95 AUPRC; Gradient boost: 94.1% of accuracy, 0.98 AUROC, 0.94 AUPRC), prioritizing treatment factors like steroid use. However, the DNN relied more on fixed patient factors like demographics and symptoms in aspect to SHAP value importance. Since treatment patterns vary between hospitals, the DNN may be more generalizable than tree-based models (random forest, gradient boost model). The results demonstrate accurate short-term forecasting of COVID-19 severity using routine clinical data. DNN models may balance predictive performance and generalizability better than other methods. Severity predictions by machine learning model could facilitate resource planning, like ICU arrangement and oxygen devices.

Evolution of neutralizing antibodies through vaccination and breakthrough infections in the era of COVID-19 endemicity.

Despite a high vaccination rate, the COVID-19 pandemic continues with immune-evading Omicron variants. The success of additional antigenic stimulation through breakthrough infection (BI) and updated vaccination in overcoming antigenic imprinting needs to be determined. Participants in a long-term follow-up cohort of healthcare worker (HCW) vaccinee were categorized according to their infection/vaccination status. Anti-SARS-CoV-2 spike/nucleocapsid protein antibodies were measured, and plaque reduction neutralization tests (PRNTs) against wild-type (WT), BA.5, BN.1, and XBB.1.5 were conducted. The neutralization activity of intravenous immunoglobulin (IVIG) products was evaluated to assess the immune status of the general population. Ninety-five HCWs were evaluated and categorized into seven groups. The WT PRNT ND50 value was highest regardless of infection/vaccination status, and groups with recent antigenic stimulation showed high PRNT titers overall. Groups with double Omicron stimulation, either by BI plus BA.4/5 bivalent vaccination or repeated BI, exhibited significantly higher BA.5 and BN.1 PRNT to WT PRNT ratios than those with single Omicron stimulation. Overall group immunity was estimated to be boosted in January 2023, reflecting the effect of the BA.4/5 bivalent booster and additional BIs, but slightly declined in June 2023. A substantial increase in the antibody concentrations of IVIG products was noticed in 2022, and recently produced IVIG products exhibited a substantial level of cross-reactive neutralizing activity against emerging variants. Neutralizing activity against emerging variants could be enhanced by repeated antigenic stimulation via BI and/or updated vaccination. Overall group immunity was elevated accordingly, and IVIG products showed substantial activity against circulating strains.

Implantable Self-Reporting Stents for Detecting In-Stent Restenosis and Cardiac Functional Dynamics.

Despite the increasing number of stents implanted each year worldwide, patients remain at high risk for developing in-stent restenosis. Various self-reporting stents have been developed to address this challenge, but their practical utility has been limited by low sensitivity and limited data collection. Herein, we propose a next-generation self-reporting stent that can monitor blood pressure and blood flow inside the blood arteries. This proposed self-reporting stent utilizes a larger inductor coil encapsulated on the entire surface of the stent strut, resulting in a 2-fold increase in the sensing resolution and coupling distance between the sensor and external antenna. The dual-pressure sensors enable the detection of blood flow in situ. The feasibility of the proposed self-reporting stent is successfully demonstrated through in vivo analysis in rats, verifying its biocompatibility and multifunctional utilities. This multifunctional self-reporting stent has the potential to greatly improve cardiovascular care by providing real-time monitoring and unprecedented insight into the functional dynamics of the heart.

Visual Impairment Risk After Alcohol Abstinence in Patients With Newly Diagnosed Open-Angle Glaucoma.

Importance: Recent studies indicate that alcohol consumption is linked to increased intraocular pressure and higher prevalence of open-angle glaucoma (OAG). However, there is insufficient evidence to establish any correlation between alcohol abstinence and improved outcomes in patients with OAG. Objective: To evaluate the association between alcohol consumption status (and its changes) and risk of incident severe visual impairment (VI) or blindness in patients with newly diagnosed OAG. Design, Setting, and Participants: This retrospective, nationwide, population-based cohort study used the Korean National Health Insurance Service's claims and health examination database to enroll patients who were newly diagnosed with OAG between January 1, 2010, and December 31, 2011, and had been alcohol drinkers before their OAG diagnosis. The cohort was followed up until December 2020. The data were analyzed from February to December 2022. Exposures: The patients were categorized into 2 groups based on their post-OAG diagnosis alcohol consumption status: sustainers and abstainers. The risks of severe VI or blindness were compared using weighted Cox proportional hazards regression models along with inverse probability of treatment weighting. Main Outcomes and Measures: Incident severe VI or blindness. Results: Among 13 643 patients with newly diagnosed OAG (mean [SD] age, 53.7 [11.9] years; 12 066 men [88.4%]) who were drinkers, 2866 (21.0%) quit drinking after the diagnosis. During 91 366 person-years of follow-up, patients abstaining from alcohol after their OAG diagnosis had a lower risk of severe VI or blindness than did those who had sustained drinking (adjusted hazard ratio [AHR] after inverse probability of treatment weighting, 0.63; 95% CI, 0.45-0.87). Among the sustained drinkers, both mild consumption (<105 g/wk; AHR, 1.52; 95% CI, 1.01-2.28) and moderate to heavy consumption (≥105 g/wk; AHR, 1.78; 95% CI, 1.11-2.86) after OAG diagnosis were associated with higher risk of severe VI or blindness relative to abstainers. Frequent drinking (≥4 d/wk) also was associated with a higher risk of severe VI or blindness (AHR, 2.56; 95% CI, 1.52-4.33) compared with abstinence. Conclusions and Relevance: In this cohort study of patients with OAG who were drinkers, abstaining from alcohol after an OAG diagnosis was associated with lower risk of severe VI or blindness. These findings suggest that lifestyle interventions, such as alcohol abstinence, could be essential for patients with newly diagnosed OAG.

Longitudinal kinetics of neutralizing antibodies against circulating SARS-CoV-2 variants and estimated level of group immunity of booster-vaccinated individuals during omicron-dominated COVID-19 outbreaks in the Republic of Korea, 2022.

The coronavirus disease 2019 pandemic persisted for 3 years and is now transitioning to endemicity. We illustrated the change in group immunity induced by vaccination (monovalent vaccines) and breakthrough infections (BIs) in a healthcare worker (HCW) cohort. Five sampling points were analyzed: before the third dose and 1, 3, 5, and 8 months after the vaccination. The last two points corresponded roughly to 1 and 4 months after omicron BA.1/BA.2 BI. A semi-quantitative anti-spike binding antibody (Sab) assay and plaque reduction neutralization test (PRNT) against circulating variants were conducted. A linear regression model was utilized to deduce correlation equations. Baseline characteristics and antibody titers after the third dose were not different between 106 HCWs with or without BI (54/52). One month after the third dose, BA.1 PRNT increased with wild-type (WT), but 3 months after the third dose, it decreased more rapidly than WT PRNT. After BI, BA.1 PRNT increased robustly and waned slower than WT. A linear equation of waning kinetics was deduced between log10Sab and months, and the slope became gradual after BI. The estimated BA.5 PRNT titers at the beginning of the BA.5 outbreak were significantly higher than the BA.1 PRNT titers of the initial BA.1/BA.2 wave, which might be associated with the smaller size of the BA.5 wave. BA.1/BA.2 BI after the third dose elicited robust and broad neutralizing activity, preferentially maintaining cross-neutralizing longevity against BA.1 and BA.5. The estimated kinetics provide an overview of group immunity through the third vaccination and BA.1/BA.2 BI, correlating with the actual outbreaks. IMPORTANCE This study analyzed changes in group immunity induced by coronavirus disease 2019 (COVID-19) vaccination and BA.1/BA.2 breakthrough infections (BIs) in a healthcare worker cohort. We investigated the longitudinal kinetics of neutralizing antibodies against circulating variants and confirmed that BA.1/BA.2 BIs enhance the magnitude and durability of cross-neutralization against BA.1 and BA.5. Correlation equations between semi-quantitative anti-spike antibody and plaque reduction neutralization test titers were deduced from the measured values using a linear regression model. Based on the equations, group immunity was estimated to last up to 11 months following the third dose of the COVID-19 vaccine. The estimated group immunity suggests that the augmented immunity and flattened waning slope through BI could correlate with the overall outbreak size. Our findings could provide a better understanding to establish public health strategies against future endemicity.

Prediction of incident chronic kidney disease in a population with normal renal function and normo-proteinuria.

Regarding the irreversible clinical course of chronic kidney disease, identifying high-risk subjects susceptible to Chronic Kidney Disease (CKD) has an important clinical implication. Previous studies have developed risk prediction models identifying high-risk individuals within a group, including those who may have experienced minor renal damage, to provide an opportunity for initiating therapies or interventions at earlier stages of CKD. To date, there were no other studies developed a prediction model with quantitative risk factors to detect the earliest stage of CKD that individuals with normal renal function in the general population may experience. We derived 11,495,668 individuals with an estimated glomerular filtration rate (eGFR) ≥90 mL/min/1.73 m2 and normo-proteinuria, who underwent health screening ≥2 times between 2009 and 2016 from the prospective nationwide registry cohort. The primary outcome was the incident CKD, defined by an eGFR <60 mL/min/1.73 m2. Sex-specific multivariate Cox regression models predicting the 8-year incident CKD risk were developed. The performance of developed models was assessed using Harrell's C and the area under the receiver operating characteristics curve (AUROC) with 10-fold cross-validation. Both men and women, who met the definition of incident CKD, were older and had more medical treatment history in hypertension and diabetes. Harrell's C and AUROC of the developed prediction models were 0.82 and 0.83 for men and 0.79 and 0.80 for women. This study developed sex-specific prediction equations with reasonable performance in a population with normal renal function.

Automatic Classification of GI Organs in Wireless Capsule Endoscopy Using a No-Code Platform-Based Deep Learning Model.

The first step in reading a capsule endoscopy (CE) is determining the gastrointestinal (GI) organ. Because CE produces too many inappropriate and repetitive images, automatic organ classification cannot be directly applied to CE videos. In this study, we developed a deep learning algorithm to classify GI organs (the esophagus, stomach, small bowel, and colon) using a no-code platform, applied it to CE videos, and proposed a novel method to visualize the transitional area of each GI organ. We used training data (37,307 images from 24 CE videos) and test data (39,781 images from 30 CE videos) for model development. This model was validated using 100 CE videos that included "normal", "blood", "inflamed", "vascular", and "polypoid" lesions. Our model achieved an overall accuracy of 0.98, precision of 0.89, recall of 0.97, and F1 score of 0.92. When we validated this model relative to the 100 CE videos, it produced average accuracies for the esophagus, stomach, small bowel, and colon of 0.98, 0.96, 0.87, and 0.87, respectively. Increasing the AI score's cut-off improved most performance metrics in each organ (p < 0.05). To locate a transitional area, we visualized the predicted results over time, and setting the cut-off of the AI score to 99.9% resulted in a better intuitive presentation than the baseline. In conclusion, the GI organ classification AI model demonstrated high accuracy on CE videos. The transitional area could be more easily located by adjusting the cut-off of the AI score and visualization of its result over time.

Low-dose aspirin in the primary prevention of cardiovascular diseases: A retrospective, propensity score matched study.

BACKGROUND AND AIMS: Although the guidelines have been revised recently, the effect of aspirin for the primary prevention of cardiovascular disease (CVD) is still controversial. Thus, we aimed to evaluate the effect of aspirin on primary prevention in the real world. METHODS: Among the 4,266,268 participants without a history of CVD or previous prescription of aspirin and other antiplatelet agents who were screened between 2002 and 2008, 268,963 persons who were prescribed low-dose aspirin (≤100 mg/day) over 90 days in 2002-2008 and 1,075,852 persons who did not receive aspirin were selected after propensity score matching. A Cox proportional-hazards model was used to evaluate the effect of low-dose aspirin on the development of CVD and bleeding episodes. RESULTS: Aspirin showed a protective effect on total CVD events (hazard ratio (HR); 0.737, 95% confidence interval; 0.729-0.745). The protective effect of aspirin on total CVD events was significant in men, women and even in young participants (<65 years). Aspirin had a protective effect in participants with diabetes or hypertension against all subcategories of CVD. The HR of bleeding risk was 1.4-1.5 in aspirin group. CONCLUSIONS: Low-dose aspirin generally showed a protective effect against CVD regardless of age, sex, and underlying comorbidities in the real world. Though, the effect of aspirin was evident at a young age, the risk of bleeding was also high (1.4-1.5 times), and thus, careful prescription is required.

Separation and Identification of an Antimicrobial Substance from Schisandra chinensis Extract against Streptococcus mutans KCCM 40105 Strain.

This study aimed to isolate and identify antibacterial compounds from Schisandra chinensis (S. chinensis) that are effective against the Streptococcus mutans KCCM 40105 strain. First, S. chinensis was extracted using varying concentrations of ethanol, and the resulting antibacterial activity was evaluated. The 30% ethanol extract of S. chinensis showed high activity. The fractionation and antibacterial activity of a 30% ethanol extract from S. chinensis were examined using five different solvents. Upon investigation of the antibacterial activity of the solvent fraction, the water and butanol fractions showed high activity, and no significant difference was found. Therefore, the butanol fraction was chosen for material exploration using silica gel column chromatography. A total of 24 fractions were obtained from the butanol portion using silica gel chromatography. The fraction with the highest antibacterial activity was Fr 7. From Fr 7, thirty-three sub-fractions were isolated, and sub-fraction 17 showed the highest level of antibacterial activity. A total of five peaks were obtained through the pure separation of sub-fraction 17 using HPLC. Peak 2 was identified as a substance exhibiting a high level of antibacterial activity. Based on the results of UV spectrometry, 13C-NMR, 1H-NMR, LC-MS, and HPLC analyses, the compound corresponding to peak number 2 was identified as tartaric acid.

Association between Sight-Threatening Eye Diseases and Death by Suicide in South Korea: A Nationwide Population-based Cohort Study.

PURPOSE: Although associations between visual impairment (VI) and suicide are posited, specific risks across the sight-threatening eye disease (STED) spectrum remain to be assessed. We determined whether individuals with STED die more often by suicide than do other people and assessed the temporal associations. DESIGN: A nationwide, population-based cohort study. PARTICIPANTS: All persons aged 40 years or older in South Korea from 2010 to 2020. METHODS: Persons diagnosed with STEDs (i.e., glaucoma, exudative age-related macular degeneration [AMD], or diabetic retinopathy [DR]) were identified in the Korean National Health Insurance (NHI) service database. Both NHI health checkup records and the National Disability Registration were used for coexisting severe VI. Death by suicide was defined as diagnostic codes as recorded in the Korea National Statistical Office. Incidence rate ratios (IRRs) were estimated by quasi-Poisson regressions and adjusted for sociodemographics, comorbidity, psychiatric diagnoses, and VI. The temporal relationship between time since first STED diagnosis and suicide risk was determined by identifying patients with STED newly diagnosed during the period from 2010 to 2011. MAIN OUTCOME MEASURES: The IRR of death by suicide in people with STED relative to those without. RESULTS: Of the 2.8 million people (45% male) observed for 24 300 969 person-years, 13 205 died by suicide. Among them, 34% (n = 4514) had a STED diagnosis, for a suicide rate of 69 per 100 000 person-years (95% confidence interval [CI], 67-72), relative to 51 per 100 000 person-years (95% CI, 50-52) for non-STED individuals. People with STED had an adjusted IRR of 1.33 (95% CI, 1.26-1.41) relative to those without. The largest excess adjusted IRR of suicide mortality was that for DR (1.40, 95% CI, 1.29-1.52). For exudative AMD, the adjusted IRR was 1.20 (95% CI, 1.04-1.39), whereas for glaucoma, the corresponding value was 1.09 (95% CI, 1.02-1.17). With coexisting severe VI, the IRR for any STED was 1.49 (95% CI, 1.29-1.73). The highest suicide hazard ratio was between 3 and 6 months postdiagnosis (5.33; 95% CI, 4.59-6.20). CONCLUSIONS: In South Korea between 2010 and 2020, a higher suicide rate was evident among those with diagnosed STED than for persons not so diagnosed. FINANCIAL DISCLOSURE(S): The author(s) have no proprietary or commercial interest in any materials discussed in this article.