Comparative Effectiveness of Team-Based Care With and Without a Clinical Decision Support System for Diabetes Management : A Cluster Randomized Trial.

BACKGROUND: Uncontrolled hyperglycemia, hypercholesterolemia, and hypertension are common in persons with diabetes. OBJECTIVE: To compare the effectiveness of team-based care with and without a clinical decision support system (CDSS) in controlling glycemia, lipids, and blood pressure (BP) among patients with type 2 diabetes. DESIGN: Cluster randomized trial. (ClinicalTrials.gov: NCT02835287). SETTING: 38 community health centers in Xiamen, China. PATIENTS: 11 132 persons aged 50 years or older with uncontrolled diabetes and comorbid conditions, 5475 receiving team-based care with a CDSS and 5657 receiving team-based care alone. INTERVENTION: Team-based care was delivered by primary care physicians, health coaches, and diabetes specialists in all centers. In addition, a computerized CDSS, which generated individualized treatment recommendations based on clinical guidelines, was implemented in 19 centers delivering team-based care with a CDSS. MEASUREMENTS: Coprimary outcomes were mean reductions in hemoglobin A1c (HbA1c) level, low-density lipoprotein cholesterol (LDL-C) level, and systolic BP over 18 months and the proportion of participants with all 3 risk factors controlled at 18 months. RESULTS: During the 18-month intervention, HbA1c levels, LDL-C levels, and systolic BP significantly decreased by -0.9 percentage point (95% CI, -0.9 to -0.8 percentage point), -0.49 mmol/L (CI, -0.53 to -0.45 mmol/L) (-19.0 mg/dL [CI, -20.4 to -17.5 mg/dL]), and -9.1 mm Hg (CI, -9.9 to -8.3 mm Hg), respectively, in team-based care with a CDSS and by -0.6 percentage point (CI, -0.7 to -0.5 percentage point), -0.32 mmol/L (CI, -0.35 to -0.29 mmol/L) (-12.5 mg/dL [CI, -13.6 to -11.3 mg/dL]), and -7.5 mm Hg (CI, -8.4 to -6.6 mm Hg), respectively, in team-based care alone. Net differences were -0.2 percentage point (CI, -0.3 to -0.1 percentage point) for HbA1c level, -0.17 mmol/L (CI, -0.21 to -0.12 mmol/L) (-6.5 mg/dL [CI, -8.3 to -4.6 mg/dL]) for LDL-C level, and -1.5 mm Hg (CI, -2.8 to -0.3 mm Hg) for systolic BP. The proportion of patients with controlled HbA1c, LDL-C, and systolic BP was 16.9% (CI, 15.7% to 18.2%) in team-based care with a CDSS and 13.0% (CI, 11.7% to 14.3%) in team-based care alone. LIMITATION: There was no usual care control, and clinical outcome assessors were unblinded; the analysis did not account for multiple comparisons. CONCLUSION: Compared with team-based care alone, team-based care with a CDSS significantly reduced cardiovascular risk factors in patients with diabetes, but the effect was modest. PRIMARY FUNDING SOURCE: Xiamen Municipal Health Commission.

Staying up late increases cardiovascular disease risk in women with polycystic ovary syndrome.

STUDY QUESTION: What is the association between late bedtime, night sleep duration, and lifetime cardiovascular disease (CVD) risk in women with polycystic ovary syndrome (PCOS)? SUMMARY ANSWER: Both late bedtime (≥1:00) and short sleep duration (<7 h/night) were independently associated with a high-lifetime CVD risk among women with PCOS. WHAT IS KNOWN ALREADY: Previous studies indicated that sleep disturbances, including altered sleep duration and staying up late (SUL), occurred more frequently among women with PCOS compared to women without PCOS. Studies have shown that both PCOS and sleep disturbances are associated with deterioration in cardiometabolic health in the longer term. However, there are limited data regarding the possible association between sleep disturbances and CVD risk among reproductive-aged women with PCOS. STUDY DESIGN, SIZE, DURATION: From the original 393 women identified at our center, a total of 213 women with PCOS aged 18-40 years were enrolled in a cross-sectional study between March 2020 and July 2022. PARTICIPANTS/MATERIALS, SETTING, METHODS: Bedtime and night sleep duration were obtained from a standardized self-administered questionnaire. The prediction for atherosclerotic CVD risk in the China risk model was applied to estimate the lifetime CVD risk in the PCOS population. Restricted cubic spline regression was applied to explore the non-linear association between sleep duration and lifetime CVD risk in a series of models. Multivariable logistic regression analyses were performed to determine the association between bedtime, night sleep duration, and lifetime CVD risk. MAIN RESULTS AND THE ROLE OF CHANCE: In our study, we found that the proportion of SUL was 94.25% and the mean (±SD) of night sleep duration was 7.5 ± 1.1 h in women with PCOS. Restricted cubic spline regression analysis showed a U-shaped relation between sleep duration and lifetime CVD risk. After adjusting for occasional drinking, fasting insulin, triglyceride, low-density lipoprotein cholesterol, and testosterone in multivariable logistic analyses, compared with going to bed at 23-24 o'clock, those who went to bed after 1 o'clock were independently associated with high-lifetime CVD risk [odds ratio (OR) = 3.87, 95% CI: 1.56-9.62]; compared with optimal sleep duration (7-8 h/night), short sleep (<7 h/night) was also independently associated with high-lifetime CVD risk (OR = 2.46, 95% CI: 1.01-5.97). LIMITATIONS, REASONS FOR CAUTION: Inferring causality is limited owing to the cross-sectional design. All sleep variables data were obtained from a standardized self-administered questionnaire rather than measurements using objective approaches. Even after adjusting for potential confounders, we still cannot completely rule out the possibility of residual confounding from unmeasured factors such as socioeconomic status. Future studies with larger sample sizes are needed to further explore the relation between long sleep duration and lifetime CVD risk. Although these findings are not generalizable to non-SUL PCOS populations, they could be used for guiding multidimensional treatment. Lastly, there is no non-PCOS group in the current cross-sectional study, which limits the interpretation of the findings from the PCOS group. WIDER IMPLICATIONS OF THE FINDINGS: This is the first study to report that both late bedtime (≥1:00) and short sleep duration (<7 h/night) were independently associated with a high-lifetime CVD risk among reproductive-aged women with PCOS, in a sample of Chinese adults. Predicting cardiovascular risk and examining the association between sleep disturbances and predicted CVD risk among women with PCOS help to highlight the need for early interventions on sleep to improve their cardiovascular outcomes. STUDY FUNDING/COMPETING INTEREST(S): This study was funded by the Natural Science Foundation of Fujian Province (No. 2020J011242), the Fujian provincial health technology project (No. 2022CXB016), the Joint Research Projects of Health and Education Commission of Fujian Province (No. 2019-WJ-39), and the Medical and Health project of Xiamen Science & Technology Bureau (No. 3502Z20214ZD1001). The authors declare that they have no conflict of interest. TRIAL REGISTRATION NUMBER: N/A.

Comparative effectiveness of team-based care with a clinical decision support system versus team-based care alone on cardiovascular risk reduction among patients with diabetes: Rationale and design of the D4C trial.

BACKGROUND: Diabetes has become a major public health challenge worldwide, especially in low- and middle-income countries (LMICs). Uncontrolled hyperglycemia, hypertension, and dyslipidemia major risk factors for all-cause mortality and cardiovascular disease (CVD) are common in patients with diabetes in China. We propose to compare the effectiveness of team-based care plus a clinical decision support system (CDSS) with team-based care alone on glycemic, blood pressure (BP), and lipid control, and clinical CVD reduction among patients with type-2 diabetes and at high risk for CVD. METHODS: The Diabetes Complication Control in Community Clinics (D4C) study is a cluster-randomized trial conducted among 38 community health centers in Xiamen City, China. Nineteen clinics have been randomly assigned to team-based care plus CDSS and 19 to team-based care alone. Team-based care includes primary care providers, health coaches, and diabetes specialists working collaboratively with patients to achieve shared treatment goals for CVD risk factor reduction. The CDSS integrates guideline-based treatment algorithms for glycemic, BP, and lipid control, along with a patient's medical history and insurance policy, to recommend treatment and follow-up plans. In phase 1, the co-primary outcomes are mean reduction in glycated hemoglobin (HbA1c), systolic BP (SBP), and low-density lipoprotein (LDL)-cholesterol over 18 months, and the proportion of patients with controlled HbA1c, SBP, and LDL-cholesterol at 18 months' between the 2 comparison groups. In phase 2, the primary outcome is the difference in major CVD incidence (non-fatal stroke, non-fatal myocardial infarction, hospitalized heart failure, and CVD mortality) between the 2 comparison groups. Mean reduction in HbA1c, SBP, and LDL-cholesterol levels will be simultaneously modeled for a single overall treatment effect. CONCLUSION: The D4C trial will generate evidence on whether a CDSS will further reduce the CVD burden among patients with diabetes beyond team-based care at community clinics. If proven effective, this implementation strategy could be scaled up within primary care settings in China and other LMICs to reduce CVD incidence and mortality among patients with diabetes.

Fat-free mass index is a feasible predictor of insulin resistance in women with polycystic ovary syndrome: Evidence from a cross-sectional study.

BACKGROUND: Insulin resistance (IR) and adipose tissue amplify the metabolic and reproductive outcomes in women with polycystic ovary syndrome (PCOS). It has been widely discussed that body composition influences metabolic health. Still, limited studies were focused on the role of the fat-free mass index (FFMI) in assessing IR in PCOS women. AIMS: We aimed to explore the associations between FFMI/fat mass index (FMI) and IR in women with PCOS and assess the role of FFMI in predicting IR in women with PCOS. METHODS: In the current cross-sectional study, women with PCOS aged between 18 and 40 years were enrolled from October 2018 to July 2022. Baseline demographic information was obtained using standardized self-administered questionnaires. Anthropometric, biochemical, and hormonal information was measured and recorded by investigators. Pearson's correlation and multivariable logistical regression were used to analyze the associations of FFMI/FMI and IR. In addition, receiver operating characteristic (ROC) curves were implied to measure the predictive role of FFMI/FMI for IR in women with PCOS. RESULTS: A total of 371 women with PCOS, reproductive age (27.58 ± 4.89) were enrolled. PCOS women with IR have higher levels of triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), homeostatic model assessment of insulin resistance (HOMA-IR), FMI, and FFMI than that without IR. FMI (r = 0.492, p < 0.001) and FFMI (r = 0.527, p < 0.001) were positively associated with IR. After adjusting for potential confounders, FMI and FFMI were significantly associated with IR in PCOS women, and the OR was 1.385 (95%CI: 1.212-1.583) and 2.306 (95%CI: 1.675-3.174), respectively. Additionally, the FFMI (0.847, 95%CI: 0.784-0.888) has a larger area of ROC (AUC) than the FMI (0.836, 95%CI: 0.799-0.896), while there is no difference in predicting IR (95%CI: -0.18-0.41, p = 0.456). CONCLUSION: These results indicated that FFMI and FMI could significantly increase the risk of IR, both of which could be feasible predictors of IR in PCOS women.

Anti-Müllerian hormone was independently associated with central obesity but not with general obesity in women with PCOS.

Objective: Anti-Müllerian hormone (AMH) is recognized as the most important biomarker for ovarian reserve. In this cross-sectional study, we aimed to explore the potential association of AMH with central obesity or general obesity in women with polycystic ovary syndrome (PCOS). Methods: In this cross-sectional study, 179 patients with PCOS were enrolled and underwent anthropometric measurements (BMI and waist circumference (WC)) and serum AMH level detection. Pearson's correlation and multivariable logistic regression analyses were performed to determine the associations of AMH with central obesity and general obesity. Results: Subjects with increasing BMI showed significantly lower values of AMH (median (interquartile range (IQR)) 8.95 (6.03-13.60) ng/mL in normal weight group, 6.57 (4.18-8.77) ng/mL in overweight group, and 6.03 (4.34-9.44) ng/mL in obesity group, P = 0.001), but higher levels of systolic blood pressure, fasting insulin, total cholesterol, triglycerides, LDL-c, obesity indices (WC, hip circumferences, waist-to-hip ratio, waist-to-height ratio (WHtR), and Chinese visceral adiposity index (CVAI)). Compared with the group of PCOS women without central obesity, the group with central obesity had significantly lower value of AMH (median (IQR) 8.56 (5.29-12.96) ng/mL vs 6.22 (4.33-8.82) ng/mL; P = 0.003). Pearson's correlation analysis showed that AMH was significantly and negatively correlated with BMI (r = -0.280; P < 0.001), WC (r = -0.263; P < 0.001), WHtR (r = -0.273; P < 0.001), and CVAI (r = -0.211; P = 0.006). Multivariate logistic regression analysis with adjustment for potential confounding factors showed that AMH was independently and negatively associated with central obesity but was not significantly associated with general obesity. Conclusions: AMH was independently and negatively associated with central obesity. Closely monitoring the WC and AMH should be addressed in terms of assessing ovarian reserve in women with PCOS.

Correlation Between Daily Energy Intake from Fat with Insulin Resistance in Patients with Polycystic Ovary Syndrome.

OBJECTIVE: The aim of the present study was to investigate the possible correlation between the percentage of daily energy intake from fat (PEF) with insulin resistance (IR) in women with polycystic ovary syndrome (PCOS). METHODS: In this cross-sectional study, a total of 186 females with PCOS were screened. Daily dietary intake data were collected by a trained nutritionist using the 24-h dietary recall method over three consecutive days. A total of 111 subjects who had complete data were divided into two groups based on the percentage of daily energy intake from fat (PEF): the normal PEF (NPEF) group (PEF < 30%) and the high PEF (HPEF) group (PEF ≥ 30%). Pearson's correlation analysis and stepwise multivariate linear regression analysis were used to analyze the correlation of PEF with homeostasis model assessment of insulin resistance (HOMA-IR). RESULTS: The total prevalence rate of overweight/obesity was 80.2%. There were significant differences in waist circumference (WC), body mass index (BMI), fasting insulin, and HOMA-IR (P < 0.001) among the normal weight, the overweight, and the obese groups, but no significant differences were observed in total energy and dietary macronutrients intake in the three groups. The daily intake of fat and protein, fasting insulin, and HOMA-IR in the NPEF group were significantly higher than those in the HPEF group. Pearson's correlation analysis showed PEF in PCOS women was negatively correlated with BMI (r= -0.189, p=0.047) and HOMA-IR (log-transformed) (r= -0.217, p=0.022). Further, stepwise multivariate linear regression analysis showed PEF was negatively correlated with HOMA-IR (p<0.05). CONCLUSION: The percentage of daily energy intake from fat is negatively correlated with IR in women with PCOS.

Efficacy of Vildagliptin Added to Continuous Subcutaneous Insulin Infusion (CSII) in Hospitalized Patients with Type 2 Diabetes.

INTRODUCTION: The aim of this study was to compare the efficacy of vildagliptin as add-on therapy to short-term continuous subcutaneous insulin infusion (CSII) with CSII monotherapy in hospitalized patients with type 2 diabetes mellitus (T2DM). METHODS: A total of 200 hospitalized patients with inadequately controlled T2DM were randomized into groups, with one group receiving CSII monotherapy (CSII group, n =100) and the other group receiving CSII plus vildagliptin as add-on (CSII + Vig group, n = 100). Of these, 191 completed the 7-day trial (CSII group, n = 99; CSII + Vig group, n = 92) and included in the analysis. The glycemic control and variability of the patients were measured using all-day capillary blood glucose (BG) monitoring. Weight and fasting C-peptide levels were evaluated before and after the interventions. RESULTS: Mean BG concentrations during the whole treatment period were lower and the time to reach target BG was reduced in the CSII + Vig group compared with the CSII group (9.89 ± 3.37 vs. 9.46 ± 3.23 mmol/L, P < 0.01; 129 ± 4 vs. 94 ± 5 h, P < 0.01, respectively). Similarly, the indicators of glycemic variability, namely the standard deviation of BG and the largest amplitude of glycemic excursion, were significantly decreased in the CSII + Vig group compared with the CSII group (2.68 ± 1.05 vs. 2.39 ± 1.00 mmol/L, P < 0.01; 7.19 ± 2.86 vs. 6.23 ± 2.73 mmol/L, P < 0.01, respectively). CONCLUSIONS: Short-term CSII with vildagliptin as add-on therapy may be an optimized treatment for hospitalized patients with T2DM compared with short-term CSII monotherapy.

Assessment of the optimal cutoff value of fasting plasma glucose to establish diagnosis of gestational diabetes mellitus in Chinese women.

Our aim is to assess the optimal cutoff value of fasting plasma glucose (FPG) in Chinese women at 24-28 weeks' gestation by performing oral glucose tolerance test (OGTT) to improve diagnostic rate of gestational diabetes mellitus (GDM). Data were derived from the Medical Birth Registry of Xiamen. A FPG cutoff value of 5.1 mmol/L confirmed the diagnosis of GDM in 4,794 (6.10%) pregnant women. However, a FPG cutoff value of 4.5 mmol/L should rule out the diagnosis of GDM in 35,932 (45.73%) pregnant women. If we use this cutoff value, the diagnosis of GDM to about 27.3% of pregnant women will be missed. Additionally, a 75-g OGTT was performed in pregnant women with FPG values between 4.5 and 5.1 mmol/L, avoiding the performance of formal 75-g OGTT in about 50.37% pregnant women. Meanwhile, according to maternal age and pre-pregnancy BMI categories, with FPG values between 4.5 mmol/L and 5.1 mmol/L, which had high sensitivity, to improve the diagnostic rate of GDM in all groups. Further researches are needed to present stronger evidences for the screening value of FPG in establishing the diagnosis of GDM in pregnant women.