Hypertension is a chronic disease that requires long‐term follow‐up in many patients, however, optimal visit intervals are not well‐established. This study aimed to evaluate the incidences of major ...cardiovascular events (MACEs) according to visit intervals. We analyzed data from 9894 hypertensive patients in the Korean Hypertension Cohort, which enrolled and followed up 11,043 patients for over 10 years. Participants were classified into five groups based on their median visit intervals (MVIs) during the 4‐year period and MACEs were compared among the groups. The patients were divided into clinically relevant MVIs of one (1013; 10%), two (1299; 13%), three (2732; 28%), four (2355; 24%), and six months (2515; 25%). The median follow‐up period was 5 years (range: 1745 ± 293 days). The longer visit interval groups did not have an increased cumulative incidence of MACE (12.9%, 11.8%, 6.7%, 5.9%, and 4%, respectively). In the Cox proportional hazards model, those in the longer MVI group had a smaller hazard ratio (HR) for MACEs or all‐cause death: 1.77 (95% confidence interval CI, 1.45–2.17), 1.7 (95% CI: 1.41–2.05), 0.90 (95% CI: 0.74–1.09) and 0.64 (95% CI: 0.52–0.79), respectively (Reference MVI group of 75–104 days). In conclusion, a follow‐up visits with a longer interval of 3–6 months was not associated with an increased risk of MACE or all‐cause death in hypertensive patients. Therefore, once medication adjustment is stabilized, a longer interval of 3–6 months is reasonable, reducing medical expenses without increasing the risk of cardiovascular outcomes.
The objective of this study was to examine FoxO expression and FoxO function in meniscus. In menisci from human knee joints with osteoarthritis (OA), FoxO1 and 3 expression were significantly reduced ...compared with normal menisci from young and old normal donors. The expression of FoxO1 and 3 was also significantly reduced in mouse menisci during aging and OA induced by surgical meniscus destabilization or mechanical overuse. Deletion of FoxO1 and combined FoxO1, 3, and 4 deletions induced abnormal postnatal meniscus development in mice and these mutant mice spontaneously displayed meniscus pathology at 6 mo. Mice with Col2Cre-mediated deletion of FoxO3 or FoxO4 had normal meniscus development but had more severe aging-related damage. In mature AcanCreERT2 mice, the deletion of FoxO1, 3, and 4 aggravated meniscus lesions in all experimental OA models. FoxO deletion suppressed autophagy and antioxidant defense genes and altered several meniscus-specific genes. Expression of these genes was modulated by adenoviral FoxO1 in cultured human meniscus cells. These results suggest that FoxO1 plays a key role in meniscus development and maturation, and both FoxO1 and 3 support homeostasis and protect against meniscus damage in response to mechanical overuse and during aging and OA.
Moutan Cortex, the root bark of Paeonia suffruticosa ANDREWS in Ranunculaceae, has widely demonstrated analgesic, anti-spasmodic, and anti-inflammatory effects in various cancer and immune cell ...lines. Oxidative stress is associated with development of several diseases, including liver disease. We prepared the water extract of Moutan Cortex (MCE) to investigate the cytoprotective activities and its mechanism. MCE protected hepatocytes from arachidonic acid (AA)+iron induced oxidative stress, as indicated by reactive oxygen species (ROS) production and cell viability analysis. MCE also suppressed mitochondrial dysfunction in AA+iron-treated human hepatocyte-derived hepatocellular carcinoma cell line, HepG2 cells. In addition, MCE treatment induces AMP-activated protein kinase (AMPK) and liver kinase B1 phosphorylation, which play a role in inhibition of oxidative stress induced cell death. Moreover, one of the MCE compounds, chlorogenic acid, exerted protective effects against oxidative stress and apoptosis. Taken together, MCE protected hepatocytes against AA+iron-induced oxidative stress through AMPK activation, and may be a candidate for the treatment of liver disease.
Background
We aimed to assess the clinical characteristics of sarcopenia by the original and revised European Working Group on Sarcopenia in Older People (EWGSOP 1 and 2), and to propose a new ...sarcopenia phenotype score (SPS) to improve relevance of clinical outcomes.
Methods
Analyses were performed in 1408 older adults of the Aging Study of PyeongChang Rural Area, a community‐based cohort in Korea. For sarcopenia definitions, we used EWGSOP 1, EWGSOP 2, and SPS, a new index counting number of abnormal domains among components of grip strength, gait speed, or muscle mass. Frailty status by the frailty index and the Cardiovascular Health Study frailty score was compared with sarcopenia measures. Prediction ability for composite outcome combining death and institutionalization due to functional decline was assessed among sarcopenia measures.
Results
Generally, sarcopenia spectrum by both EWGSOP 1 and 2 was associated with worse functional status in parameters of geriatric assessments. However, population who were considered as sarcopenic by EWGSOP 1, but not by EWGSOP 2, showed increased risk of composite outcome and worse frailty status, compared with people who were classified as not sarcopenic by both EWGSOP 1 and 2. With SPS, dose–response relationship was observed with both frailty status and outcome prediction. Prediction for composite outcome was better in SPS than in EWGSOP 2 classification.
Conclusions
A new SPS might be used to classify sarcopenic burden in older adults to resolve possible inconsistencies in phenotype correlation and outcome prediction of EWGSOP 2 criteria.
Marine resources are valuable assets to be protected from illegal, unreported, and unregulated (IUU) fishing and overfishing. IUU and overfishing detections require the identification of fishing ...gears for the fishing ships in operation. This paper is concerned with automatically identifying fishing gears from AIS (automatic identification system)-based trajectory data of fishing ships. It proposes a deep learning-based fishing gear-type identification method in which the six fishing gear type groups are identified from AIS-based ship movement data and environmental data. The proposed method conducts preprocessing to handle different lengths of messaging intervals, missing messages, and contaminated messages for the trajectory data. For capturing complicated dynamic patterns in trajectories of fishing gear types, a sliding window-based data slicing method is used to generate the training data set. The proposed method uses a CNN (convolutional neural network)-based deep neural network model which consists of the feature extraction module and the prediction module. The feature extraction module contains two CNN submodules followed by a fully connected network. The prediction module is a fully connected network which suggests a putative fishing gear type for the features extracted by the feature extraction module from input trajectory data. The proposed CNN-based model has been trained and tested with a real trajectory data set of 1380 fishing ships collected over a year. A new performance index, DPI (total performance of the day-wise performance index) is proposed to compare the performance of gear type identification techniques. To compare the performance of the proposed model, SVM (support vector machine)-based models have been also developed. In the experiments, the trained CNN-based model showed 0.963 DPI, while the SVM models showed 0.814 DPI on average for the 24-h window. The high value of the DPI index indicates that the trained model is good at identifying the types of fishing gears.
Older adults are at an increased risk of postoperative morbidity. Numerous risk stratification tools exist, but effort and manpower are required. This study aimed to develop a predictive model of ...postoperative adverse outcomes in older patients following general surgery with an open-source, patient-level prediction from the Observational Health Data Sciences and Informatics for internal and external validation. We used the Observational Medical Outcomes Partnership common data model and machine learning algorithms. The primary outcome was a composite of 90-day postoperative all-cause mortality and emergency department visits. Secondary outcomes were postoperative delirium, prolonged postoperative stay (≥75th percentile), and prolonged hospital stay (≥21 days). An 80% versus 20% split of the data from the Seoul National University Bundang Hospital (SNUBH) and Seoul National University Hospital (SNUH) common data model was used for model training and testing versus external validation. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) with a 95% CI. Data from 27,197 (SNUBH) and 32,857 (SNUH) patients were analyzed. Compared to the random forest, Adaboost, and decision tree models, the least absolute shrinkage and selection operator logistic regression model showed good internal discriminative accuracy (internal AUC 0.723, 95% CI 0.701-0.744) and transportability (external AUC 0.703, 95% CI 0.692-0.714) for the primary outcome. The model also possessed good internal and external AUCs for postoperative delirium (internal AUC 0.754, 95% CI 0.713-0.794; external AUC 0.750, 95% CI 0.727-0.772), prolonged postoperative stay (internal AUC 0.813, 95% CI 0.800-0.825; external AUC 0.747, 95% CI 0.741-0.753), and prolonged hospital stay (internal AUC 0.770, 95% CI 0.749-0.792; external AUC 0.707, 95% CI 0.696-0.718). Compared with age or the Charlson comorbidity index, the model showed better prediction performance. The derived model shall assist clinicians and patients in understanding the individualized risks and benefits of surgery.
•Lead (Pb) is a highly toxic metal in aquatic animals, especially in fish.•The Pb exposure induces a significant bioaccumulation in specific tissues in fish.•Oxidative stress, neurotoxicity, and ...immune alterations are caused by the Pb exposure.
Lead (Pb) is a highly toxic metal in aquatic environments. Fish are at the top of the food chain in most aquatic environments, and are the most susceptible to the toxic effects of Pb exposure. In addition, fish are one of the most abundant vertebrates, and they can directly affect humans through food intake; therefore, fish can be used to assess the extent of environmental pollution in an aquatic environment. Pb-induced toxicity in fish exposed to toxicants is primarily induced by bioaccumulation in specific tissues, and the accumulation mechanisms vary depending on water habitat (freshwater or seawater) and pathway (waterborne or dietary exposure). Pb accumulation in fish tissues causes oxidative stress due to excessive ROS production. Oxidative stress by Pb exposure induces synaptic damage and neurotransmitter malfunction in fish as neurotoxicity. Moreover, Pb exposure influences immune responses in fish as an immune-toxicant. Therefore, the purpose of this review was to examine the various toxic effects of Pb exposure, including bioaccumulation, oxidative stress, neurotoxicity, and immune responses, and to identify indicators to evaluate the extent of Pb toxicity by based on the level of Pb exposure.
Hypertension is the leading cause of death in human being, which shows high prevalence and associated complications that increase the mortality and morbidity. Controlling blood pressure (BP) is very ...important because it is well known that lowering high BP effectively improves patients' prognosis. This review aims to provide a focused update of the 2018 Korean Hypertension Society Guidelines for the management of hypertension. The importance of ambulatory BP and home BP monitoring was further emphasized not only for the diagnosis but also for treatment target. By adopting corresponding BPs, the updated guideline recommended out-of-office BP targets for both standard and intensive treatment. Based on the consensus on corresponding BPs and Systolic Blood Pressure Intervention Trial (SPRINT) revisit, the updated guidelines recommended target BP in high-risk patients below 130/80 mmHg and it applies to hypertensive patients with three or more additional cardiovascular risk factors, one or more risk factors with diabetes, or hypertensive patients with subclinical organ damages, coronary or vascular diseases, heart failure, chronic kidney disease with proteinuria, and cerebral lacunar infarction. Cerebral infarction and chronic kidney disease are also high-risk factors for cardiovascular disease. However, due to lack of evidence, the target BP was generally determined at < 140/90 mmHg in patients with those conditions as well as in the elderly. Updated contents regarding the management of hypertension in special situations are also discussed.
The standardized techniques of blood pressure (BP) measurement in the clinic are emphasized and it is recommended to replace the mercury sphygmomanometer by a non-mercury sphygmomanometer. ...Out-of-office BP measurement using home BP monitoring (HBPM) or ambulatory BP monitoring (ABPM) and even automated office BP (AOBP) are recommended to correctly measure the patient's genuine BP. Hypertension (HTN) treatment should be individualized based on cardiovascular (CV) risk and the level of BP. Based on the recent clinical study data proving benefits of intensive BP lowering in the high risk patients, the revised guideline recommends the more intensive BP lowering in high risk patients including the elderly population. Lifestyle modifications, mostly low salt diet and weight reduction, are strongly recommended in the population with elevated BP and prehypertension and all hypertensive patients. In patients with BP higher than 160/100 mmHg or more than 20/10 mmHg above the target BP, two drugs can be prescribed in combination to maximize the antihypertensive effect and to achieve rapid BP control. Especially, single pill combination drugs have multiple benefits, including maximizing reduction of BP, minimizing adverse effects, increasing adherence, and preventing cardiovascular disease (CVD) and target organ damage.
Falls impact over 25% of older adults annually, making fall prevention a critical public health focus. We aimed to develop and validate a machine learning-based prediction model for serious ...fall-related injuries (FRIs) among community-dwelling older adults, incorporating various medication factors.
Utilizing annual national patient sample data, we segmented outpatient older adults without FRIs in the preceding three months into development and validation cohorts based on data from 2018 and 2019, respectively. The outcome of interest was serious FRIs, which we defined operationally as incidents necessitating an emergency department visit or hospital admission, identified by the diagnostic codes of injuries that are likely associated with falls. We developed four machine-learning models (light gradient boosting machine, Catboost, eXtreme Gradient Boosting, and Random forest), along with a logistic regression model as a reference.
In both cohorts, FRIs leading to hospitalization/emergency department visits occurred in approximately 2% of patients. After selecting features from initial set of 187, we retained 26, with 15 of them being medication-related. Catboost emerged as the top model, with area under the receiver operating characteristic of 0.700, along with sensitivity and specificity rates around 65%. The high-risk group showed more than threefold greater risk of FRIs than the low-risk group, and model interpretations aligned with clinical intuition.
We developed and validated an explainable machine-learning model for predicting serious FRIs in community-dwelling older adults. With prospective validation, this model could facilitate targeted fall prevention strategies in primary care or community-pharmacy settings.
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