Mediation analysis of brain magnetic resonance imaging variables with all-cause and cardiovascular disease-specific mortalities in persons with type 2 diabetes.

AIM: Glucose variation (GV) has emerged as a predictor of morbidity and mortality in persons with diabetes. However, no study has examined whether brain magnetic resonance imaging (MRI) variables mediated the association between mortality and GV. MATERIALS AND METHODS: This study was a retrospective cohort comprising 3,961 individuals with type 2 diabetes (T2D), whose electronic medical records were retrieved from a medical center between January 2001 and October 2021. GV was quantified using coefficient of variation of fasting plasma glucose (FPG-CV) and glycated hemoglobin (HbA1c). The MRI variables included the presence or absence of cerebrovascular abnormality and white matter hyperintensity (WMH). All deaths and deaths resulting from expanded cardiovascular disease (CVD) were identified through annual record linkage with National Death Datasets. Cox proportional hazards models were applied to evaluate associations of MRI variable or GV with mortality. Mediation analyses were performed to assess the relative contributions of MRI variables for GV on mortality. RESULTS: Among 3,961 patients, 2,114 patients (53.4%) had cerebrovascular abnormality and 1,888 patients (47.7%) had WMH. The results showed cerebrovascular abnormality and WMHs were significantly associated with all-cause and expanded CVD mortality after considering GV. The largest mediated effects of GV on all-cause and expanded CVD mortality were observed by cerebrovascular abnormality (5.26% and 8.49%, respectively). CONCLUSIONS: Our study suggests cerebrovascular abnormality and WMHs are important predictors of mortality in patients with T2D after considering GV. In addition, MRI variables of cerebrovascular abnormality expressed weak but significant mediation effect on the associations between GV and mortality.

Independent and joint effects of self-reported physical activity and sedentary behaviors on mortality in community-dwelling older persons: a prospective cohort study.

BACKGROUND: This study aims to assess the joint and independent effects of self-reported physical activity and sedentary behavior on mortality in older persons. METHODS: A prospective community-based cohort study was conducted to examine physical activity (PA) level and sitting time (ST) in relation to mortality among 1,786 older persons aged 65 years and above. PA was assessed by a checklist of 26 self-reported items about PA and hours per week, and the metabolic equivalent hours/week was derived, and ST was measured by a self-reported item asking the average number of hours spent sitting per day. The participants were divided into four combination groups of PA and ST based on WHO guideline and values found in literature: high PA/short ST group, high PA/long ST group, low PA/long ST group, and low PA/short ST group. Data on death ascertainment were obtained through linkage with the national death datasets and expanded cardiovascular disease (CVD) included cardiovascular disease, diabetes, and chronic kidney disease. RESULTS: After follow-up for a median 11.1 years, 599 mortality cases were recorded, giving a crude all-cause mortality of 32.5/1,000 person-years, CVD mortality of 8.6/1,000 person-years, expanded CVD mortality of 11.9/1,000 person-years, and nonexpanded CVD mortality of 20.8/1,000 person-years. For all-cause, and expanded CVD, the hazards ratios (HRs) for the low PA/long ST group remained significant compared with that for the high PA/short ST group after all covariates were considered [HRs for all-cause mortality: 1.4 [95% confidence interval (CI) 1.1, 1.8]; and expanded CVD mortality: 1.7 (95% CI 1.1, 2.4). CONCLUSIONS: The independent effect of PA and the joint effects of PA and ST are associated with all-cause and expanded CVD death risks. Expanded CVD mortality may be minimized by engaging in PA and reducing sedentary behaviors.

Heritability of carotid intima-media thickness and inflammatory factors of atherosclerosis in a Chinese population.

Carotid intima-media thickness (cIMT), a marker of subclinical atherosclerosis, has been found to be associated with incident stroke. High-sensitivity C-reactive protein (CRP) and fibrinogen have been demonstrated to be associated with atherosclerosis. Previous studies on heritability estimates of IMT, CRP, and fibrinogen among Chinese populations are limited. This study aims to estimate the heritability of these risk factors in residents who participated in the Taichung Community Health Study (TCHS) and their family members. A total of 2671 study subjects from 805 families were enrolled in the study, selected from a random sample of TCHS participants and their family members. CRP, and fibrinogen were obtained from each participant, and a questionnaire interview was conducted. cIMT was measured by high-resolution B-mode ultrasound and expressed as the mean of the maximum. Heritability estimates and the familial correlation of cIMT, CRP, and fibrinogen among family pairs were determined with SAGE software. With multivariate adjustments, significant heritability was found for cIMT (h2 = 0.26, P < 0.001), CRP (h2 = 0.34, P < 0.001), and fibrinogen (h2 = 0.48, P < 0.001). The intrafamilial correlation coefficients for the three indexes in the parent-offspring pairs were significant (P < 0.001) and ranged from 0.17 to 0.41. The full sibship correlations were also significant (P < 0.001) for the three indexes and ranged from 0.19 to 0.47. This study indicates that a moderate proportion of the variability in CRP, fibrinogen, and cIMT can be attributed to genetic factors in Chinese populations. The findings suggest that CRP is associated with cIMT, whereas no significant association exists between fibrinogen and cIMT.

Effect modification of glycemic control on association of lung function with all-cause and cardiovascular mortality in persons with type 2 diabetes - A retrospective cohort study.

BACKGROUND: Poor glucose control might deteriorate the impaired pulmonary function, which can ultimately lead to mortality. However, few studies have examined the effect modification of glucose control on the association between pulmonary function and mortality. This study aimed to examine the association of pulmonary function with mortality and determine the effect modification of glycemic level on the association of pulmonary function with mortality in persons with type 2 diabetes (T2DM). METHODS: A retrospective cohort study included 3846 persons with T2DM with pulmonary function testing in Taiwan during 2002-2020. Expiratory volume in 1 s (FEV1) was measured as pulmonary function. Cox proportional hazards models were used and the effect modification of pulmonary function parameters and glucose control was assessed by their product terms. RESULTS: There were 733 deaths during an average follow-up of 7.83 years. Significant associations of FEV1 and mortality were found (hazards ratio [HR] for FEV1 Z-scores of <0 to -1, <-1 to -2 and <-2: 1.47 [1.20, 1.80], 2.48 [1.95, 3.14] and 3.07 [1.74, 5.44] compared with participants with Z-score ≥0, respectively. All p for trend<0.001). Significant effect modifications were found and the association between FEV1 and mortality was stronger in persons with good glycemic control compared with poor glycemic control (FEV1-FPG effect modification, P = 0.01; FEV1-HbA1c effect modification, P = 0.03). CONCLUSION: Pulmonary function, measured by FEV1, is significantly associated with mortality in persons with T2DM. Significant effect modification of glucose control on the association between pulmonary function parameters and mortality was found.

Addressing causal relationship between drinking behavior and metabolic syndrome: one-sample Mendelian randomization analysis.

AIMS: Alcohol drinking is associated with central obesity, hypertension, and hyperlipidemia, which further causes metabolic syndrome (MetS). However, prior epidemiological studies on such associations lack experimental evidence for a causal relationship. This study aims to explore the causal relationship between drinking behavior and MetS in Taiwan population by using Mendelian randomization (MR) analysis. METHODS: A cross-sectional study was conducted using the Taiwan Biobank database, which comprised 50 640 Han Chinese who were 30-70 years old without cancer from 2008 to 2020. In MR analysis, we constructed weighted and unweighted genetic risk scores by calculating SNP alleles significantly associated with alcohol drinking. We calculated odds ratios and 95% confidence interval (CI) by using a two-stage regression model. RESULTS: A total of 50 640 participants were included with a mean age of 49.5 years (SD: 1.67 years), 36.6% were men. The adjusted odds ratio (aOR) of MetS per 5% increase in the likelihood of genetic predisposition to drink based on weighted genetic risk score with adjustment was 1.11 (95% CI: 1.10, 1.12, P < .001). Analysis was also conducted by grouping the likelihood of genetic predisposition to drink based on quartiles with multivariate adjustment. Using Q1 as the reference group, the aORs of MetS for Q2, Q3, and Q4 were 1.19 (1.12, 1.27, p < .001), 1.31 (1.23, 1.40, p < .001), and 1.87 (1.75, 2.00, p < .001), respectively, for the weighted genetic risk score. CONCLUSIONS: This study shows a modest relationship between drinking behavior and MetS by using MR analysis.

Development of a risk prediction model for radiation dermatitis following proton radiotherapy in head and neck cancer using ensemble machine learning.

PURPOSE: This study aims to develop an ensemble machine learning-based (EML-based) risk prediction model for radiation dermatitis (RD) in patients with head and neck cancer undergoing proton radiotherapy, with the goal of achieving superior predictive performance compared to traditional models. MATERIALS AND METHODS: Data from 57 head and neck cancer patients treated with intensity-modulated proton therapy at Kaohsiung Chang Gung Memorial Hospital were analyzed. The study incorporated 11 clinical and 9 dosimetric parameters. Pearson's correlation was used to eliminate highly correlated variables, followed by feature selection via LASSO to focus on potential RD predictors. Model training involved traditional logistic regression (LR) and advanced ensemble methods such as Random Forest and XGBoost, which were optimized through hyperparameter tuning. RESULTS: Feature selection identified six key predictors, including smoking history and specific dosimetric parameters. Ensemble machine learning models, particularly XGBoost, demonstrated superior performance, achieving the highest AUC of 0.890. Feature importance was assessed using SHAP (SHapley Additive exPlanations) values, which underscored the relevance of various clinical and dosimetric factors in predicting RD. CONCLUSION: The study confirms that EML methods, especially XGBoost with its boosting algorithm, provide superior predictive accuracy, enhanced feature selection, and improved data handling compared to traditional LR. While LR offers greater interpretability, the precision and broader applicability of EML make it more suitable for complex medical prediction tasks, such as predicting radiation dermatitis. Given these advantages, EML is highly recommended for further research and application in clinical settings.

Association of echocardiographic parameters with all-cause and cardiovascular mortality in patients with type 2 diabetes.

BACKGROUND: This study aimed to evaluate associations between echocardiography markers and mortality in patients with type 2 diabetes mellitus (T2DM). METHODS: Diabetes Care Management Program database of a medical center was used, including 5612 patients with T2DM aged 30 years and older and who underwent echocardiography assessment between 2001 and 2021. Cox proportional hazard regression models were used to evaluate associations of echocardiography abnormalities with all-cause and expanded cardiovascular disease (CVD) mortality. RESULTS: During a mean follow-up of 5.8 years, 1273 patients died. Hazard ratios (95% confidence intervals) of all-cause mortality for each standard deviation increase were presented for the cardiac systolic function indicator of left ventricular ejection fraction (0.77, 0.73-0.81), cardiac structural parameters of left ventricular mass index (1.25, 1.19-1.31) and left atrial volume index (1.31, 1.25-1.37), and cardiac diastolic function of E/A ratio (1.10, 1.07-1.13), E/e' ratio (1.37, 1.30-1.45), and TR velocity (1.25, 1.18-1.32); meanwhile, the values of expanded CVD mortality included left ventricular ejection fraction (0.67, 0.62-0.72), left ventricular mass index (1.35, 1.25-1.45), left atrial volume index (1.40, 1.31-1.50), E/A ratio (1.12, 1.08-1.16), E/e' ratio (1.57, 1.46-1.69), and TR velocity (1.29, 1.19-1.39), respectively. CONCLUSIONS: Cardiac systolic function indicator of left ventricular ejection fraction, cardiac structural parameters of left ventricular mass index and left atrial volume index, and cardiac diastolic function indicators of E/A ratio, E/e' ratio, and TR velocity are associated with all-cause and expanded CVD mortality in patients with T2DM.

Comparison of Mini Nutritional Assessment Tool and Geriatric Nutrition Risk Index in Predicting 12-Y Mortality Among Community-Dwelling Older Persons.

BACKGROUND: Malnutrition is a common and dangerous condition in older adults, which has been associated with increased risk of mortality. OBJECTIVES: This study aimed to evaluate and compare the abilities of Mini Nutritional Assessment short form (MNA-SF), MNA full form (MNA-FF), and geriatric nutritional risk index (GNRI) to predict all-cause and expanded cardiovascular disease (CVD)-related mortality in community-dwelling older adults. METHODS: This research was an observational cohort study conducted in a community setting, with a 12-y follow-up involving 1001 community-living older adults aged 65 y or older who were enrolled in 2009 and followed up until 2021. Nutritional status assessment was carried out in 2009 using MNA-SF, MNA-FF, and GNRI. Multivariate Cox proportional hazards regression was applied to determine adjusted hazard ratios of mortality with 95% CIs. RESULTS: A total of 368 deaths (36.76%) and 122 expanded CVD-related deaths (12.19%) were observed after a median follow-up of 12 y. Compared with normal nutritional status, poor nutritional status assessed by the MNA-SF, MNA-FF, and GNRI was found to be associated with an increased all-cause mortality in older persons. MNA-SF and MNA-FF, but not GNRI, were associated with expanded CVD-related mortality. The MNA-FF showed better discriminatory accuracy for all-cause (C-statistics: 0.77; 95% CI: 0.63, 0.79) and expanded CVD-related mortality (C-statistics: 0.79; 95% CI: 0.70, 0.83) than MNA-SF (C-statistics: 0.76; 95% CI: 0.73-0.79; and C-statistics: 0.76; 95% CI: 0.72-0.81, respectively) and GNRI (C-statistics: 0.75; 95% CI: 0.73-0.79; and C-statistics: 0.76; 95% CI: 0.72-0.80, respectively). CONCLUSIONS: Our findings indicate that MNA-SF, MNA-FF, and GNRI were all independent predictors of all-cause mortality. In particular, the MNA-FF may be the best nutritional assessment tool for predicting all-cause and CVD-related mortality among older persons residing in community, compared with MNA-SF and GNRI.

Ohwia caudata aqueous extract attenuates senescence in aging adipose-derived mesenchymal stem cells.

Stem cells exhibit pluripotency and self-renewal abilities. Adipose-derived mesenchymal stem cells can potentially be used to reconstruct various tissues. They possess significant versatility and alleviate various aging-related diseases. Unfortunately, aging leads to senescence, apoptosis, and a decline in regenerative capacity in adipose-derived mesenchymal stem cells. These changes necessitate a strategy to mitigate the effects of aging on stem cells. Ohwia caudata (O. caudata) has therapeutic effects against several illnesses. However, studies on whether O. caudata has therapeutic effects against aging are lacking. In this study, we aimed to identify potential therapeutic anti-aging effects in the crude aqueous extract of O. caudata on adipose-derived mesenchymal stem cells. Using 0.1 µM doxorubicin, we induced aging in human adipose-derived mesenchymal stem cells (hADMSCs) and evaluated whether various concentrations of O. caudata aqueous extract exhibit anti-aging effects on them. The O. caudata extract exhibited significant antioxidant effects on hADMSCs without any toxicity. Furthermore, after treatment with the O. caudata aqueous extract, the levels of mitochondrial superoxide, DNA double-strand breaks, and telomere shortening were reduced in the hADMSCs subjected to doxorubicin-induced aging. The extract also suppressed doxorubicin-induced aging by upregulating klotho and downregulating p21 in hADMSCs. These findings indicated that the O. caudata extract exhibited anti-aging properties that modulated hADMSC homeostasis. Therefore, it could be a potential candidate for restoring the self-renewal ability and multipotency of aging hADMSCs.

Association of carotid atherosclerosis markers with all-cause and cardiovascular disease-specific mortality in persons with type 2 diabetes: a causal mediation analysis with glucose variation.

AIMS: Glucose variation (GV) is independently associated with mortality in patients with diabetes. However, no study has examined the effects of carotid atherosclerosis markers on mortality after considering GV. Our purpose is to investigate the independent effects of carotid atherosclerosis markers in persons with type 2 diabetes (T2DM) after considering GV and the mediation effects of carotid atherosclerosis markers on associations between GV with cardiovascular disease (CVD) mortality. MATERIALS AND METHODS: This study is a retrospective cohort study including 3628 persons with T2DM who were admitted to a medical center between January 01, 2001 and October 31, 2021. GV was defined as a coefficient of variation (CV) of repeated measurements within a year before the index date (date of first IMT assessment). Carotid atherosclerosis markers included intima-media thickness (IMT), plaque, and stenosis. The outcomes consisted of all-cause and expanded cardiovascular disease (CVD) mortality. Cox proportional hazards models were applied. RESULTS: Among the participants, 286 (7.9%) had IMT ≥ 2 mm, 2834 (78.1%) had carotid plaque, and 464 (12.8%) had carotid stenosis ≥ 50%. When GV was considered, IMT, carotid plaque, and carotid stenosis were significant factors for all-cause mortality (except IMT considering HbA1c-CV) and expanded CVD mortality. IMT was a significant mediator in the associations of fasting plasma glucose (FPG)-CV with all-cause and expanded CVD mortality (2 and 3.19%, respectively), and carotid stenosis was a significant mediator in the association between FPG-CV and expanded CVD mortality (3.83%). CONCLUSIONS: Our statistical evaluations show suggests that carotid atherosclerosis markers are important predictors of CVD mortality in persons with T2DM if GV is considered. In addition, IMT and carotid stenosis were significant mediators in the association between GV and mortality.

Mitochondrial DNA haplogroup D and brain microstructure regulate cognitive function among community-dwelling older adults.

INTRODUCTION: Maintaining physical and cognitive function among older adults is important. These functional states are affected by mitochondria through various mechanisms, such as cellular energy production and oxidative stress control. Owing to its involvement in the relations among the brain, cognition, and physical function, mitochondrial function may be affected by mitochondrial DNA (mtDNA) haplogroups. This study explored the effect of mtDNA haplogroups and brain microstructure on physical and cognitive functions among community-dwelling older adults. METHODS: This study was a community-based cross-sectional research. A total of 128 subjects aged 65 years and older without dementia completed several assessments, including mtDNA sequencing, physical and cognitive function tests, and magnetic resonance imaging (MRI) scans. Cognitive function and impairment were assessed by the MMSE and AD8 questionnaires. mtDNA haplogroups were classified by HaploGrep 2 software, and white matter microstructural integrity was scanned by 3T MRI. RESULTS: The mean age of the subjects was 77.3 years. After the adjustment for covariates, the mtDNA haplogroup D carriers showed significantly lower mini-mental state examination (MMSE) scores than other carriers (p = 0.047). Further considering the brain microstructure, the mtDNA haplogroup D (p = 0.002) and white matter volumes in the left precuneus corrected for total intracranial volumes (p = 0.014) were found to be independently influencing factors of the MMSE scores. CONCLUSIONS: The mtDNA haplogroup D and white matter microstructure regulated the cognitive function among community-dwelling older adults. The findings provide new insights into the research gap. Scientists must further venture into this field.

Association of time-varying sleep duration and cognitive function with mortality in the elderly: a 12-year community-based cohort study.

BACKGROUND: Sleeping problems and cognitive impairment are common in elders. Baseline sleep duration and cognitive status are predictors of mortality. But few studies have explored whether longitudinal changes in sleep duration and cognitive function are related to mortality in older adults. The present study investigated the time-varying relationships of sleep duration and cognitive function with subsequent mortality among community-dwelling elders by using 12 years of repeated-measure data. METHODS: Taichung Community Health Study for Elders (TCHS-E) is a retrospective, population-based cohort that started in 2009 (wave 1) with a total of 912 elders aged 65 years or above. Follow up was conducted in 2010 (wave 2), 2018 (wave 3), and 2020 (wave 4). Sleep duration and Mini-Mental State Examination (MMSE) forms were executed at baseline and three visits during follow-up. Time-varying Cox proportional hazards regression estimated adjusted hazard ratios (HRs) of mortality with 95% confidence intervals (CIs). RESULTS: During about 12 years (9,396 person-years) follow-up, 329 deaths from all causes were documented, including 102 deaths due to expanded cardiovascular disease (CVD). In the multivariable-adjusted, time-varying Cox proportional hazard model, the adjusted HR values of all-cause mortality were 1.47 (1.02-2.12) for sleep duration > 9 h/day (vs. 7 h/day) and 1.81 (1.26-2.59) for MMSE < 27 (vs. 30). The adjusted HR values of the expanded CVD mortality were 2.91 (1.24-6.83) for MMSE of 29; 2.69 (1.20-6.05) for MMSE of 27-28; and 4.32 (95% CI: 1.92-9.74) for MMSE < 27. The dose-dependent relationship was significant (p < 0.001). The combinations of sleep duration longer than 9 h/day and MMSE < 27 were linked with the highest risks for expanded CVD and all-cause mortality. CONCLUSIONS: Long sleep duration and low cognitive function were jointly and independently linked with higher risk of mortality in elders residing in community.

A non-invasive mouse model that recapitulates disuse-induced muscle atrophy in immobilized patients.

Disuse muscle atrophy occurs consequent to prolonged limb immobility or bed rest, which represents an unmet medical need. As existing animal models of limb immobilization often cause skin erosion, edema, and other untoward effects, we here report an alternative method via thermoplastic immobilization of hindlimbs in mice. While significant decreases in the weight and fiber size were noted after 7 days of immobilization, no apparent skin erosion or edema was found. To shed light onto the molecular mechanism underlying this muscle wasting, we performed the next-generation sequencing analysis of gastrocnemius muscles from immobilized versus non-mobilized legs. Among a total of 55,487 genes analyzed, 787 genes were differentially expressed (> fourfold; 454 and 333 genes up- and down-regulated, respectively), which included genes associated with muscle tissue development, muscle system process, protein digestion and absorption, and inflammation-related signaling. From a clinical perspective, this model may help understand the molecular/cellular mechanism that drives muscle disuse and identify therapeutic strategies for this debilitating disease.

Using machine learning algorithm to analyse the hypothyroidism complications caused by radiotherapy in patients with head and neck cancer.

Machine learning algorithms were used to analyze the odds and predictors of complications of thyroid damage after radiation therapy in patients with head and neck cancer. This study used decision tree (DT), random forest (RF), and support vector machine (SVM) algorithms to evaluate predictors for the data of 137 head and neck cancer patients. Candidate factors included gender, age, thyroid volume, minimum dose, average dose, maximum dose, number of treatments, and relative volume of the organ receiving X dose (X: 10, 20, 30, 40, 50, 60 Gy). The algorithm was optimized according to these factors and tenfold cross-validation to analyze the state of thyroid damage and select the predictors of thyroid dysfunction. The importance of the predictors identified by the three machine learning algorithms was ranked: the top five predictors were age, thyroid volume, average dose, V50 and V60. Of these, age and volume were negatively correlated with thyroid damage, indicating that the greater the age and thyroid volume, the lower the risk of thyroid damage; the average dose, V50 and V60 were positively correlated with thyroid damage, indicating that the larger the average dose, V50 and V60, the higher the risk of thyroid damage. The RF algorithm was most accurate in predicting the probability of thyroid damage among the three algorithms optimized using the above factors. The Area under the receiver operating characteristic curve (AUC) was 0.827 and the accuracy (ACC) was 0.824. This study found that five predictors (age, thyroid volume, mean dose, V50 and V60) are important factors affecting the chance that patients with head and neck cancer who received radiation therapy will develop hypothyroidism. Using these factors as the prediction basis of the algorithm and using RF to predict the occurrence of hypothyroidism had the highest ACC, which was 82.4%. This algorithm is quite helpful in predicting the probability of radiotherapy complications. It also provides references for assisting medical decision-making in the future.

Application of artificial intelligence in endoscopic image analysis for the diagnosis of a gastric cancer pathogen-Helicobacter pylori infection.

Helicobacter pylori (H. pylori) infection is the principal cause of chronic gastritis, gastric ulcers, duodenal ulcers, and gastric cancer. In clinical practice, diagnosis of H. pylori infection by a gastroenterologists' impression of endoscopic images is inaccurate and cannot be used for the management of gastrointestinal diseases. The aim of this study was to develop an artificial intelligence classification system for the diagnosis of H. pylori infection by pre-processing endoscopic images and machine learning methods. Endoscopic images of the gastric body and antrum from 302 patients receiving endoscopy with confirmation of H. pylori status by a rapid urease test at An Nan Hospital were obtained for the derivation and validation of an artificial intelligence classification system. The H. pylori status was interpreted as positive or negative by Convolutional Neural Network (CNN) and Concurrent Spatial and Channel Squeeze and Excitation (scSE) network, combined with different classification models for deep learning of gastric images. The comprehensive assessment for H. pylori status by scSE-CatBoost classification models for both body and antrum images from same patients achieved an accuracy of 0.90, sensitivity of 1.00, specificity of 0.81, positive predictive value of 0.82, negative predicted value of 1.00, and area under the curve of 0.88. The data suggest that an artificial intelligence classification model using scSE-CatBoost deep learning for gastric endoscopic images can distinguish H. pylori status with good performance and is useful for the survey or diagnosis of H. pylori infection in clinical practice.

Association of body indices and risk of mortality in patients with type 2 diabetes.

INTRODUCTION: A body shape index (ABSI) is independently associated with mortality in general population, but studies on the predictability of ABSI in the risk of mortality in patients with type 2 diabetes (T2D) are limited. We aimed to examine the independent and joint association of ABSI, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), and body roundness index (BRI) with mortality in patients with T2D. RESEARCH DESIGN AND METHODS: The study included 11 872 patients (46.5% women) aged 30 years and older and who took part in diabetes care management program of a medical center in Taiwan. Body indices were evaluated by anthropometric measurements at baseline between 2001 and 2016, and their death status was followed up through 2021. Multivariate Cox regression models were used to assess the effect of body indices on mortality. RESULTS: During a mean follow-up of 10.2 years, 560 cardiovascular disease (CVD) deaths and 3043 deaths were recorded. For ABSI, WC, WHR, WHtR and BRI, all-cause mortality rates were statistically significantly greater in Q4 versus Q2. For BMI and WHtR, all-cause mortality rates were also statistically significantly greater in Q1 versus Q2. The combination of BMI and ABSI exhibited a superiority in identifying risks of all-cause mortality and CVD mortality (HRs: 1.45 and 1.37, both p<0.01). CONCLUSIONS: Combined use of ABSI and BMI can contribute to the significant explanation of the variation in death risk in comparison with the independent use of BMI or other indices.

Three-year trajectories of sleep duration and mortality in patients with type 2 diabetes-a hospital-based retrospective cohort study.

OBJECTIVES: Most studies have shown that a single item of self-reported sleep duration is related to mortality risk. However, the long-term effect of sleep duration on mortality remains unclear in patients with diabetes. This study aimed to examine the associations of 3-year trajectory patterns of sleep duration with all-cause and expanded cardiovascular disease mortality in patients with type 2 diabetes. METHODS: Patients with type 2 diabetes and self-reported sleep duration during a 3-year interval were included. Expanded cardiovascular disease was defined as death due to cardiovascular disease, diabetes, and kidney diseases. Cox's proportional hazards models were employed to examine the associations between sleep duration patterns and mortality after controlling for sociodemographic factors, lifestyle behaviors, diabetes-related variables, diabetic complications, and medication use. RESULTS: A total of 7591 patients were included for analysis, and 995 deaths (13.11%) and 424 expanded cardiovascular disease deaths (5.59%) were observed during a mean follow-up of 8.51 years. Five trajectory patterns of sleep duration were identified: cluster 1: "constant 7- to 8-hour group" (50.03%); cluster 2: "constant low group" (19.68%); cluster 3: "high with decreasing trend group" (3.08%); cluster 4: "low with fluctuation group" (1.28%); and cluster 5: "constant high group" (25.93%). Compared with cluster 1, clusters 3 and 4 were associated with increased risks of all-cause mortality (1.41, 1.08-1.84; 1.44, 1.01-2.05), and cluster 5 was associated with high risks of all-cause and expanded cardiovascular disease mortality (1.26, 1.08-1.46; 1.42, 1.12-1.79). CONCLUSIONS: Sleep duration trajectories with constant high or unstable patterns may be associated with higher mortality.

Sentiment analysis of Indonesian datasets based on a hybrid deep-learning strategy.

Various attempts have been conducted to improve the performance of text-based sentiment analysis. These significant attempts have focused on text representation and model classifiers. This paper introduced a hybrid model based on the text representation and the classifier models, to address sentiment classification with various topics. The combination of BERT and a distilled version of BERT (DistilBERT) was selected in the representative vectors of the input sentences, while the combination of long short-term memory and temporal convolutional networks was taken to enhance the proposed model in understanding the semantics and context of each word. The experiment results showed that the proposed model outperformed various counterpart schemes in considered metrics. The reliability of the proposed model was confirmed in a mixed dataset containing nine topics.

Trends in energy and macronutrient intake among Taiwanese older adults in 1999-2000, 2005-2008 and 2013-2016 periods.

BACKGROUND: This study aimed to explore trends, in 3 periods, in the intake of energy and macronutrients among Taiwanese older adults. METHODS: Study subjects were those aged ≥65 years in the Nutrition and Health Survey in Taiwan 1999-2000 as well as the surveys in 2005-2008 and 2013-2016. Twenty-four-hour dietary recall data were obtained. This study used the 3 nutrition survey datasets for 1999-2000, 2005-2008, and 2013-2016, including data on the questionnaire, physical examination, and dietary intakes. Each nutrition survey involved the face-to-face household interview, and individual's dietary intake of carbohydrate, fat, and protein (% of energy) was estimated. Subsequently, intake statuses of the three macronutrients were classified into below, meeting, and above intake categories. RESULTS: In the 2013-2016 survey, approximately 40% of the older adults had a low intake of energy. The prevalence of older adults with a meeting intake of carbohydrate, fat, and protein have increased from the 1999-2000 to 2013-2016 periods. The prevalence of people having a low intake of carbohydrate declined from the 1999-2000 period to the 2013-2016 period. The prevalence of high fat intake in 2013-2016 was approximately 5% higher than that in 1999-2000. In the 2013-2016 period, the prevalence of low intake of carbohydrate, fat, and protein were 25.9, 24.5, and 4.9%, respectively; moreover, the prevalence of high intake of the aforementioned macronutrients were 38.7, 36.2, and 17.6%, respectively. CONCLUSIONS: Our study provides important evidence on the dietary patterns, as well as their changes over time among Taiwanese older adults. Such information would be useful for health policy makers about the burden of unbalanced diet and for nutrition educators on planning nutrition promotion interventions about well-balanced dietary for the older persons.

Plasma riboflavin fluorescence as a diagnostic marker of mesenteric ischemia-reperfusion injury in rats.

Due to the delayed and vague symptoms, it is difficult to early diagnose mesenteric ischemia injuries in the dynamics of acute illness, leading to a 60-80 % mortality rate. Here, we found plasma fluorescence spectra can rapidly assess the severity of mesenteric ischemia injury in animal models. Ischemia-reperfusion damage of the intestine leads to multiple times increase in NADH, flavins, and porphyrin auto-fluorescence of blood. The fluorescence intensity ratio between blue-fluorophores and flavins can reflect the occurrence of shock. Using liquid chromatography and mass spectroscopy, we confirm that riboflavin is primarily responsible for the increased flavin fluorescence. Since humans absorb riboflavin from the intestine, its increase in plasma may indicate intestinal mucosa injury. Our work suggests a self-calibrated and reagent-free approach to identifying the emergence of fatal mesenteric ischemia in emergency departments or intensive care units.