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.

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.

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.

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.

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.

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.

Association of high-sensitivity C-reactive protein and diabetic nephropathy in patients with type 2 diabetes: a Mendelian randomization study.

INTRODUCTION: Observational studies support the relationship between C-reactive protein (CRP) level and diabetic nephropathy (DN) in patients with diabetes. The research question regarding whether the relationship between serum high-sensitivity C-reactive protein (hsCRP) level and DN is causal lacks experimental evidence. Therefore, this study aimed to evaluate the causality between hsCRP and DN based on Mendelian randomization (MR) analysis. RESEARCH DESIGN AND METHODS: A total of 2332 participants with type 2 diabetes from the Taiwan Biobank database was analyzed. Genetic risk scores (GRSs), which comprise four validated CRP loci as two instrumental variables, were calculated as unweighted and weighted scores to evaluate the causal relationship of hsCRP with DN risk. The two-stage regression model was used to estimate OR and 95% CI. RESULTS: The analyses of the observational study showed that the hsCRP level was significantly associated with DN after multivariate adjustment (adjusted OR 1.15; 95% CI 1.01 to 1.32). Unweighted/weighted GRSs for log-transformed hsCRP satisfied MR assumptions 1 and 3, respectively; that is, a significant association with hsCRP was observed but that with DN was absent (adjusted OR 1.00, 95% CI 0.92 to 1.09; 1.00, 0.72 to 1.39, respectively). The MR analyses demonstrated that a 1-unit increase in the log-transformed genetically predicted hsCRP by unweighted and weighted GRSs was associated with DN, demonstrating ORs of 1.80 (95% CI 1.51 to 2.14) and 1.67 (95% CI 1.40 to 1.98), respectively. CONCLUSIONS: The current study provided experimental evidence that hsCRP level was causally related to DN. These findings suggest that the elevated hsCRP may be a causal risk factor for DN in patients with type 2 diabetes.

Obesity marker trajectories and cognitive impairment in older adults: a 10-year follow-up in Taichung community health study for elders.

BACKGROUND: Obesity and cognitive impairment prevalence increases as age increases. Recent growing evidence finds links between obesity and cognitive impairment in older adults. However, the association between the two is controversial. This study aims to identify obesity marker trajectory patterns, and to assess whether these patterns are associated with cognitive impairment and cognitive decline during a 10-year follow-up period among community-dwelling older adults. METHODS: A total of 626 older adults aged 65 and older were involved in the study, with at least two repeated measurements at baseline, one-year or 10-year follow-up. Cognitive function was measured through the Mini Mental State Examination. Obesity markers included body mass index, waist circumference, waist-to-hip (WHR), fat mass (FM), and abdominal fat (AF) measured by dual-energy X-ray absorptiometry. Multivariate logistic regression analyses were performed to estimate the adjusted odds ratios (ORs) and 95% confidence intervals (CIs) of cognitive impairment and cognitive decline for obesity marker trajectory patterns. RESULTS: After a 10-year follow-up, 168 older adults with incident cognitive impairment and 156 with rapid cognitive decline were defined as the top 25th percentile of cognitive decline. Four distinct trajectory groups of obesity markers were identified. In multivariate logistic regression analyses, a low likelihood of cognitive impairment was observed in the consistently high-level group from FM trajectory (ORs = 0.41, 95% CI = 0.20-0.85); the high-level U-shaped group from WHR trajectory (0.43, 0.22-0.84); and the median-level flat inverse U-shaped, consistently high-level, and low-level flat U-shaped groups from AF trajectory (0.44, 0.26-0.77; 0.33, 0.18-0.61; 0.39, 0.18-0.82). In addition, a low likelihood of rapid decline was found in the low-level, slightly increasing trend group from WHR trajectory (0.43, 0.22-0.85). CONCLUSION: FM and AF trajectories with consistent high levels and WHR trajectory with high level with U-shaped group are associated with low risks of incident cognitive impairment in older adults. Similarly, WHR trajectory with a low but slowly increasing trend is associated with a decreased risk of cognitive decline.

Joint effect of blood pressure and glycemic variation on the risk of cardiovascular morbidity and mortality in persons with type 2 diabetes.

OBJECTIVE: Few studies have explored the association of visit-to-visit variation in blood pressure (BP) and glycemic factors with cardiovascular disease (CVD) morbidity and mortality. This study aimed to examine the independent and joint effect of visit-to-visit BP and glycemic variation on CVD morbidity and mortality in persons with T2DM. METHODS: The present study consisted of two retrospective cohort studies. The Taiwan Diabetes Study was based on a database of the National Diabetes Care Management Program (DCMP) and linked with cardiovascular morbidity incidence. The Taichung Diabetes Study was based on the DCMP database of a medical center, which can be linked with the National Death Registry dataset. The outcomes were analyzed by using Cox's proportional hazard models. RESULTS: A total of 13,280 and 10,894 persons with T2DM in Taiwan and Taichung Diabetes Study, respectively, were included. SBP-CV, FPG-CV, and HbA1c-CV were significant predictors of stroke, CVD event or death, all-cause mortality, and expanded CVD mortality, whereas DBP-CV was a significant predictor of all-cause mortality and expanded and non-expanded CVD mortality. The joint effect of SBP, FPG, and HbA1c predicted the incidence of stroke and CVD event or death with increased risks of 16 %-35 %. In addition, the joint effect of SBP, DBP, FPG, and HbA1c was associated with all-cause and expanded CVD mortality with increased risks of 29 %-81 %. CONCLUSIONS: The joint effect of BP and glucose variation improved the prediction of cardiovascular morbidity and mortality. Moreover, simultaneous measurement of visit-to-visit BP and glycemic variation may stratify persons with cardiovascular risks and may be regarded as important therapeutic goals in the care of T2DM.

Independent and joint associations of skeletal muscle mass and physical performance with all-cause mortality among older adults: a 12-year prospective cohort study.

BACKGROUND: Decreased skeletal muscle mass and low physical performance are independently associated with increased mortality in elderly individuals. However, little is known about the effects of skeletal muscle mass combined with physical performance on the prediction of mortality risk among community-dwelling older adults. This study aimed to determine the combined effects of skeletal muscle mass and physical performance on total mortality. METHODS: A community-based prospective cohort study was conducted among 641 participants aged 65 and older in 2009. The height-adjusted skeletal muscle index (hSMI) and the weight-adjusted SMI (wSMI) were determined by dual-energy X-ray absorptiometry examination. Physical performance tests measured at baseline included gait speed (GS), timed up-and-go (TUG) test, timed chair stand (TCS), weight-adjusted leg press (WaLP), and handgrip strength (HS). Cox proportional hazards regression models were applied to determine the adjusted hazard ratios (HRs) of mortality with 95% confidence intervals (95% CIs) for baseline skeletal muscle mass, physical performance, and traditional risk factors. RESULTS: During the follow-up of 12 years, 198 (30.89%) participants died. Low hSMI, low GS, high TUG, high TCS, low WaLP, and low HS were associated with high risks of mortality after the adjustment for confounders. The results of receiver operating characteristic (ROC) curve analyses revealed the values of ROC for models with additional consideration for TUG or all indicators significantly improved the discriminatory ability of mortality compared with the model with traditional factors (all P < 0.05). Elders with low hSMI and low GS (HRs = 4.33, 95% CI: 2.76-6.78), high TUG (4.11, 2.60-6.48), high TCS (2.97, 1.92-4.59), low WaLP (3.19, 2.13-4.79), and low HS (4.08, 2.70-6.17) were associated with high risks of mortality compared with those with high hSMI and their corresponding counterparts. CONCLUSION: The hSMI and physical performance are significantly associated with increased risks of all-cause mortality. The combined use of hSMI and physical performance can provide improved risk stratification, which may be appropriately used as a screening tool targeting high-risk elders for the effective prevention of sarcopenia-related mortality.

Prediction of all-cause and cardiovascular mortality using ankle-brachial index and brachial-ankle pulse wave velocity in patients with type 2 diabetes.

Ankle-brachial index (ABI) and brachial-ankle pulse wave velocity (baPWV) are used as non-invasive indicators for detecting atherosclerosis and arterial stiffness, two well-known predictors of mortality in patients with type 2 diabetes mellitus (T2DM). ABI and baPWV have independent associations with mortality; however, their joint and interactive effects on mortality have not been assessed in patients with T2DM. This work aims to evaluate the independent, joint, and interactive associations of ABI and baPWV with all-cause and expanded cardiovascular disease (CVD) mortality in patients with T2DM. This observational study included 2160 patients with T2DM enlisted in the Diabetes Care Management Program database of China Medical University Hospital from 2001 to 2016 and then followed their death status until August 2021. Cox proportional hazard models were used to evaluate the independent, joint, and interactive effects of ABI and baPWV on the risk of all-cause and expanded CVD mortality. A total of 474 patient deaths occurred after a mean follow-up of 8.4 years, and 268 of which were attributed to cardiovascular events. Abnormal ABI (≤ 0.9) and highest baPWV quartile were independently associated with increased risks of all-cause [ABI: hazard ratio (HR) 1.67, 95% confidence interval (CI) 1.30-2.11; baPWV: 1.63, 1.16-2.27] and expanded CVD mortality (ABI: 2.21, 1.62-3.02; baPWV: 1.75, 1.09-2.83). The combination of abnormal ABI (≤ 0.9) and highest baPWV quartile was associated with a significantly higher risk of all-cause (4.51, 2.50-8.11) and expanded CVD mortality (9.74, 4.21-22.51) compared with that of the combination of normal ABI and lowest baPWV quartile. Significant interactions were observed between ABI and baPWV in relation to all-cause and expand CVD mortality (both p for interaction < 0.001). Through their independent, joint, and interactive effects, ABI and baPWV are significant parameters that can improve the prediction of all-cause and expanded CVD mortality in patients with T2DM and help identify high-risk patients who may benefit from diabetes care.

Sleep duration predicts subsequent long-term mortality in patients with type 2 diabetes: a large single-center cohort study.

BACKGROUND: Sleep duration is associated with mortality. However, prior studies exploring whether sleep duration predicts subsequent long-term mortality in patients with diabetes are limited. This study aims to examine whether metabolic factors affect the associations between baseline sleep duration and subsequent risks of all-cause, expanded, and non-expanded cardiovascular disease (CVD) mortalities among patients with type 2 diabetes (T2D). METHODS: A total of 12,526 T2D patients aged 30 years and older, with a follow-up period ≥ 3 years, were identified from the Diabetes Case Management Program of a medical center in Taiwan. Sleep duration was measured using computerized questionnaires by case managers, and the time frame for this question was 1 month prior to the interview date. Sleep duration in relation to subsequent mortality from all causes, expanded CVD, and non-expanded CVD was examined using Cox proportional hazard models. RESULTS: Within 10 years of follow-up, 2918 deaths (1328 CVD deaths and 1590 non-CVD deaths) were recorded. A J-shaped association was observed for all-cause, expanded CVD, and non-expanded CVD mortalities, and the lowest risks were observed for patients with 5-7 h of sleep. The significant joint effects included sleep duration of more or less than 7 h with age ≥ 65 years [adjusted HRs: 4.00 (3.49-4.60)], diabetes duration ≥ 5 years [1.60 (1.40-1.84)], age at diabetes diagnosis ≤ 45 years [1.69 (1.38-2.07)], insulin use [1.76 (1.54-2.03)], systolic blood pressure/diastolic blood pressure > 130/85 mmHg [1.24 (1.07-1.43)], triglyceride ≥ 150 mg/dL [1.38 (1.22-1.56)], HbA1c ≥ 7% [1.31 (1.13-1.52)], and body mass index < 27 kg/m2 [1.31 (1.17-1.45)] for all-cause mortality. CONCLUSION: A J-shaped association was observed between sleep duration and all-cause and expanded CVD mortality, and a sleep duration of 5-7 h had the lowest mortality risk. Sleep duration also showed significant synergistic interactions with diabetes duration but shared an antagonistic interaction with age and obesity.

Effect of blood pressure trajectory and variability on new-onset chronic kidney disease in patients with type 2 diabetes.

This study aimed to evaluate the effects of BP trajectory and variability on chronic kidney disease (CKD) incidence in patients with type 2 diabetes. This retrospective longitudinal study included 4,560 participants with type 2 diabetes, aged ≥30 years, free of CKD, with ≥3 years of follow-up, and who attended the Diabetes Care Management Program in 2001-2013. The follow-up period ended in 2016. The adverse outcome was a new-onset CKD event, which was determined using eGFR and albuminuria. Cox proportional hazards models were used to assess the associations. At the end of the follow-up, 1255 participants had developed CKD, with a mean follow-up of 4.3 ± 3.2 years. Three trajectory subgroups of BP, i.e., Cluster 1: "moderate-stable" for SBP and "moderate-downward" for DBP, Cluster 2: "low-upward-downward" for both SBP and DBP, and Cluster 3: "high-downward-upward" for both SBP and DBP, were generated. The BP variability was grouped into three classes on the basis of tertiles. For the BP trajectory, patients in Cluster 3 of DBP had a higher CKD risk than those in Cluster 1 (HR = 1.24, 95% CI = 1.03-1.50). For the BP variability, patients in Tertile 3 had a significantly higher CKD risk than those in Tertile 1 (SBP: 1.28, 1.11-1.47; DBP: 1.17, 1.02-1.34). Persons with type 2 diabetes who achieved a small reduction in DBP after participating in the education program but rebounded and those who had the highest variation in both SBP and DBP faced the highest increase in CKD risk.

Development and validation of a risk prediction model for chronic kidney disease among individuals with type 2 diabetes.

Many studies had established the chronic kidney disease (CKD) prediction models, but most of them were conducted on the general population and not on patients with type 2 diabetes, especially in Asian populations. This study aimed to develop a risk prediction model for CKD in patients with type 2 diabetes from the Diabetes Care Management Program (DCMP) in Taiwan. This research was a retrospective cohort study. We used the DCMP database to set up a cohort of 4,601 patients with type 2 diabetes without CKD aged 40-92 years enrolled in the DCMP program of a Taichung medical center in 2002-2016. All patients were followed up until incidences of CKD, death, and loss to follow-up or 2016. The dataset for participants of national DCMP in 2002-2004 was used as external validation. The incident CKD cases were defined as having one of the following three conditions: ACR data greater than or equal to 300 (mg/g); both eGFR data less than 60 (ml/min/1.73 m2) and ACR data greater than or equal to 30 (mg/g); and eGFR data less than 45 (ml/min/1.73 m2). The study subjects were randomly allocated to derivation and validation sets at a 2:1 ratio. Cox proportional hazards regression model was used to identify the risk factors of CKD in the derivation set. Time-varying area under receiver operating characteristics curve (AUC) was used to evaluate the performance of the risk model. After an average of 3.8 years of follow-up period, 3,067 study subjects were included in the derivation set, and 786 (25.63%) were newly diagnosed CKD cases. A total of 1,534 participants were designated to the validation set, and 378 (24.64%) were newly diagnosed CKD cases. The final CKD risk factors consisted of age, duration of diabetes, insulin use, estimated glomerular filtration rate, albumin-to-creatinine ratio, high-density lipoprotein cholesterol, triglyceride, diabetes retinopathy, variation in HbA1c, variation in FPG, and hypertension drug use. The AUC values of 1-, 3-, and 5-year CKD risks were 0.74, 0.76, and 0.77 in the validation set, respectively, and were 0.76, 0.77, and 0.76 in the sample for external validation, respectively. The value of Harrell's c-statistics was 0.76 (0.74, 0.78). The proposed model is the first CKD risk prediction model for type 2 diabetes patients in Taiwan. The 1-, 3-, and 5-year CKD risk prediction models showed good prediction accuracy. The model can be used as a guide for clinicians to develop medical plans for future CKD preventive intervention in Chinese patients with type 2 diabetes.

Effect of blood lipid variability on mortality in patients with type 2 diabetes: a large single-center cohort study.

BACKGROUND: Dyslipidemia is a major cardiovascular risk factor and common in diabetes patients. Most guidelines focus on optimal lipid levels, while variation of lipid profiles is far less discussed. This study aims to investigate the association of visit-to-visit variability in blood lipids with all-cause, cardiovascular, and non-cardiovascular mortality in patients with type 2 diabetes. METHODS: We identified 10,583 type 2 diabetes patients aged ≥ 30 years with follow-up ≥ 3 years and who participated in the Diabetes Care Management Program at a medical center in Taiwan. Variability in lipid profiles within 3 years after entry was calculated using coefficient of variation. Cox proportional hazard models were used to evaluate lipid variability in relation to subsequent mortality. RESULTS: Over a mean follow-up of 6.4 years, 1838 all-cause deaths (809 cardiovascular deaths) were observed. For each 10% increase in variability in high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and total cholesterol, the hazard ratios (95% confidence intervals) of all-cause mortality were 1.30 (1.22-1.37), 1.05 (1.01-1.09), and 1.10 (1.03-1.16), respectively; those of cardiovascular mortality were 1.27 (1.16-1.39), 1.08 (1.02-1.15), and 1.16 (1.07-1.27), respectively. Each 10% increase in high-density lipoprotein cholesterol variability conveyed 31% greater risk of non-cardiovascular mortality. High variability in total cholesterol and low-density lipoprotein cholesterol increased all-cause mortality in subgroups of nonsmoking, regular exercising, non-dyslipidemia, and more severe status of diabetes at baseline. CONCLUSIONS: Blood lipid variability except for triglyceride variability was associated with all-cause and cardiovascular mortality in patients with type 2 diabetes.

Derivation and validation of a clinical prediction model for risks of venous thromboembolism in diabetic and general populations.

ABSTRACT: Most studies on the prediction of venous thromboembolism (VTE) focused on hospitalized, surgery, and cancer patients or women receiving hormonal contraceptives or menopausal hormone therapy. No study considered diabetic and general populations to establish a VTE prediction model, especially in Asia. We developed a predictive model for VTE among type 2 diabetic patients and the general population.This study considered 2 nationwide retrospective cohort studies consisting of 52,427 diabetic participants and 508,664 participants from the general population aged 30 to 85 years during 2001 to 2004 in Taiwan. All participants were followed up until VTE event, death, or December 2011. The outcome event was VTE, including deep venous thrombosis and pulmonary embolism. Candidate predictors consisted of socio-demographic factors, diabetes-related factors and biomarkers, comorbidities, and medicine use. Our study followed the procedures proposed by the Framingham Heart Study to develop prediction models by using a Cox regression model. The predictive accuracy and performance characteristics were assessed using the area under curve of receiver operating characteristics curve and calibration of a risk score were performed by Hosmer-Lemeshow goodness-of-fit test.The common factors for persons with type 2 diabetes and general population included age, hospitalization status 1 year before the baseline, hypertension, chronic kidney disease, chronic obstructive pulmonary disease, and anti-diabetes medications; the specific factors for persons with type 2 diabetes consisted of body mass index, glycosylated hemoglobin A1C, and creatinine; and the factors for general population included gender, peripheral vascular disease, cancer, hypertension medication, cardiovascular medication, and non-steroidal anti-inflammatory drug. The area under curve of 3-, 5-, and 8-year VTE prediction models were 0.74, 0.71, and 0.69 in the diabetic population and 0.77, 0.76, and 0.75 in the general population, respectively.The new clinical prediction models can help identify a high risk of VTE and provide medical intervention in diabetic and general populations.

Three-year trajectories of metabolic risk factors predict subsequent long-term mortality in patients with type 2 diabetes.

AIM: This study aims to evaluate the associations between 3-year trajectories of metabolic risk factors and subsequent mortality in patients with type 2 diabetes. METHODS: A total of 6400 persons aged ≥ 30 years with type 2 diabetes and ≥ 3 years of follow-up period were included. The cluster analysis determined the patterns of 3-year trajectories, and Cox proportional hazards models evaluated the associations between patterns and mortality. RESULTS: Three trajectory subgroups of metabolic risk factors, namely, cluster 1, normal; cluster 2, high-stable or reducing with high level at baseline; and cluster 3, fluctuation: elevated and decreasing, were generated. The clusters 2 and 3 of body mass index (BMI), fasting plasma glucose (FPG), HbA1c, and triglyceride (TG) trajectories were associated with increased risks of all-cause mortality compared with cluster 1 (hazard ratio = 1.27, 95% confidence interval = 1.06-1.51 and 1.45, 1.19-1.78 for BMI; 1.41, 1.22-1.62 and 1.81, 1.38-2.38 for FPG; 1.42, 1.23-1.64 and 1.47, 1.23-1.75 for HbA1c; 1.34, 1.10-1.63 and 2.40, 1.30-4.37 for TG, respectively). For the systolic blood pressure trajectory, only cluster 3 was associated with an increased mortality risk relative to cluster 1 (1.76, 1.13-2.77). CONCLUSIONS: Long-term metabolic risk factor trajectories may be associated with subsequent mortality.

Renal markers and risks of all cause and cardiovascular mortality from the Taichung community based cohort study.

This study aimed to explore the associations between renal-related and arterial stiffness biomarkers with all-cause and expanded cardiovascular disease (CVD) mortality in a general Taiwanese population. This prospective community-based cohort study included 4883 subjects aged ≥ 20 years who were followed up until December 31, 2016. Renal-related biomarkers consisted of blood urea nitrogen (BUN), estimated glomerular filtration rate (eGFR), and urine albumin-to-creatinine ratio (UACR). Arterial stiffness biomarker consisted of brachial-ankle pulse wave velocity (baPWV). The death status of the subjects was ascertained by matching information from death records with the identification number and date of birth of the subjects. Cox proportional hazard models with restricted cubic splines estimated the hazard ratios and 95% confidence intervals for all-cause mortality and expanded CVD mortality. During a mean 8.3 years of follow up, 456 deaths were recorded, 146 of which were due to expanded CVD mortality. The multivariable-adjusted hazard ratios of all-cause mortality was 1.53 (95% CI 1.21-1.94) for BUN (≥ 20 mg/dL vs. < 20 mg/dL), 1.57 (1.15-2.14) for eGFR (< 90 mL/min/1.73 m2 vs. ≥ 90 mL/min/1.73 m2), 1.55 (1.25-1.92) for UACR (≥ 30 mg/g vs. < 30 mg/g), and 1.75 (1.14-2.67) for baPWV (≥ 1400 cm/s vs. < 1400 cm/s). The expanded CVD mortality was 1.89 (95% CI 1.30-2.73) for BUN (≥ 20 mg/dL vs. < 20 mg/dL), 2.28 (1.13-4.57) for eGFR (< 90 mL/min/1.73 m2 vs. ≥ 90 mL/min/1.73 m2), 2.13 (1.52-2.99) for UACR (≥ 25 mg/g vs. < 25 mg/g), and 15.73 (2.14-115.61) for baPWV (≥ 1400 cm/s vs. < 1400 cm/s). High levels of BUN, UACR, and baPWV and low levels of eGFR showed high risks with all-cause and expanded CVD mortality. Our study provides insights into screening tests to target populations at high risk of premature death due to CVD.

A risk scoring system to predict the risk of new-onset hypertension among patients with type 2 diabetes.

Hypertension (HTN), which frequently co-exists with diabetes mellitus, is the leading major cause of cardiovascular disease and death globally. This study aimed to develop and validate a risk scoring system considering the effects of glycemic and blood pressure (BP) variabilities to predict HTN incidence in patients with type 2 diabetes. This research is a retrospective cohort study that included 3416 patients with type 2 diabetes without HTN and who were enrolled in a managed care program in 2001-2015. The patients were followed up until April 2016, new-onset HTN event, or death. HTN was defined as diastolic BP (DBP) ≥ 90 mm Hg, systolic BP (SBP) ≥ 140 mm Hg, or the initiation of antihypertensive medication. Cox proportional hazard regression model was used to develop the risk scoring system for HTN. Of the patients, 1738 experienced new-onset HTN during an average follow-up period of 3.40 years. Age, sex, physical activity, body mass index, type of DM treatment, family history of HTN, baseline SBP and DBP, variabilities of fasting plasma glucose, SBP, and DBP and macroalbuminuria were significant variables for the prediction of new-onset HTN. Using these predictors, the prediction models for 1-, 3-, and 5-year periods demonstrated good discrimination, with AUC values of 0.70-0.76. Our HTN scoring system for patients with type 2 DM, which involves innovative predictors of glycemic and BP variabilities, has good classification accuracy and identifies risk factors available in clinical settings for prevention of the progression to new-onset HTN.

Independent associations of urinary albumin-to-creatinine ratio and serum cystatin C with carotid intima-media thickness in community-living Taiwanese adults.

BACKGROUND: Renal function is a key factor of cardiovascular disease. Carotid intima-media thickness (IMT) has been widely used as a marker of early subclinical atherosclerosis. The determinants of cystatin C, a novel marker of renal function, have not been extensively studied in the Asian population. This study aimed to assess the determinants of cystatin C and explore whether carotid thickening was associated with urinary albumin-creatinine ratio and cystatin C in community-living Taiwanese adults. METHODS: A cross-sectional study was conducted on participants from Taichung City, Taiwan. All the participants underwent carotid ultrasonography. Carotid IMT-mean and IMT-maximum were derived. Kidney biomarkers were measured on the basis of urinary albumin-to-creatinine ratio (ACR) and cystatin C. Multiple linear regression analysis was used. RESULTS: A total of 1032 individuals were recruited, and 469 (45.44%) of them were men. An increased cystatin C level was significantly associated with older age, male gender, lack of physical activity, low HDL cholesterol, abdominal obesity, high hs-CRP, and high ACR. The multivariate-adjusted mean carotid IMT-mean and IMT-maximum values significantly increased by 80.49 and 195.23 µm for every one unit of increase in cystatin C level and by 0.07 and 0.14 µm for every one unit of increase in ACR, respectively (all p < 0.001 except ACR on IMT-maximum with p < 0.01). Lack of physical activity, low HDL, abdominal obesity, high hs-CRP, and high ACR were the determinants of cystatin C. CONCLUSION: Cystatin C and ACR were strongly and linearly associated with carotid thickening, a marker of subclinical atherosclerosis.