Influence of glucometric 'dynamical' variables on duodenal-jejunal bypass liner (DJBL) anthropometric and metabolic outcomes.

BACKGROUND: The endoscopically implanted duodenal-jejunal bypass liner (DJBL) is an attractive alternative to bariatric surgery for obese diabetic patients. This article aims to study dynamical aspects of the glycaemic profile that may influence DJBL effects. METHODS: Thirty patients underwent DJBL implantation and were followed for 10 months. Continuous glucose monitoring (CGM) was performed before implantation and at month 10. Dynamical variables from CGM were measured: coefficient of variation of glycaemia, mean amplitude of glycaemic excursions (MAGE), detrended fluctuation analysis (DFA), % of time with glycaemia under 6.1 mmol/L (TU6.1), area over 7.8 mmol/L (AO7.8) and time in range. We analysed the correlation between changes in both anthropometric (body mass index, BMI and waist circumference) and metabolic (fasting blood glucose, FBG and HbA1c) variables and dynamical CGM-derived metrics and searched for variables in the basal CGM that could predict successful outcomes. RESULTS: There was a poor correlation between anthropometric and metabolic outcomes. There was a strong correlation between anthropometric changes and changes in glycaemic tonic control (∆BMI-∆TU6.1: rho = - 0.67, P < .01) and between metabolic outcomes and glycaemic phasic control (∆FBG-∆AO7.8: r = .60, P < .01). Basal AO7.8 was a powerful predictor of successful metabolic outcome (0.85 in patients with AO7.8 above the median vs 0.31 in patients with AO7.8 below the median: Chi-squared = 5.67, P = .02). CONCLUSIONS: In our population, anthropometric outcomes of DJBL correlate with improvement in tonic control of glycaemia, while metabolic outcomes correlate preferentially with improvement in phasic control. Assessment of basal phasic control may help in candidate profiling for DJBL implantation.

New insights from continuous glucose monitoring into the route to diabetes.

AIM: Type 2 diabetes mellitus (T2DM) is preceded by a period of impaired glucoregulation. We investigated if continuous glucose monitoring system (CGMS) (1) could improve our capacity to predict the development of T2DM in subjects at risk. (2) Find out if impaired fasting glucose/impaired glucose tolerance differentiation through CGMS would also elucidate differences in clinical phenotypes. MATERIAL AND METHODS: Observational study of 209 hypertensive patients, aged 18 to 85 years who wore at entry a CGMS. Two CGMS metrics, percent of time under the 100 mg/dL glycaemic threshold (TU100) (impaired fasting glucose surrogate phenotype) and area above the 140 mg/dL glycemic threshold (AO140) (impaired glucose tolerance surrogate phenotype) were measured. The median follow-up was 32 months (6-72 mo), and there were 17 new cases of T2DM. RESULTS: In a multivariate Cox proportional hazard survival analysis including the conventional prediabetes-defining criteria and the 2 CGMS-derived variables, only TU100 and HbA1c were significant and independent variables in predicting T2DM development. An increase in 0.1 in TU100 resulted in a 0.69 (95% CI, 0.54-0.88; P < .01) odds ratio of developing T2DM. With cut-off points of 0.5 for TU100 and 5.7% for HbA1c , the test "TU < 0.5 and HbA1c  > 5.7%" had a sensitivity of 0.81 (SD, 0.10), a specificity of 0.83 (SD, 0.03), and a likelihood ratio of 4.82 (SD, 1.03) for T2DM development. CONCLUSIONS: Continuous glucose monitoring system allows for a better T2DM risk-development categorization than fasting glucose and HbA1c in a high-risk population. Continuous glucose monitoring system-derived phenotyping reveals clinical differences, not disclosed by conventional fasting plasma glucose/HbA1c categorization. These differences may correlate with distinct pathophysiological mechanisms.

Glucose time series complexity as a predictor of type 2 diabetes.

BACKGROUND: Complexity analysis of glucose profile may provide valuable information about the gluco-regulatory system. We hypothesized that a complexity metric (detrended fluctuation analysis, DFA) may have a prognostic value for the development of type 2 diabetes in patients at risk. METHODS: A total of 206 patients with any of the following risk factors (1) essential hypertension, (2) obesity or (3) a first-degree relative with a diagnosis of diabetes were included in a survival analysis study for a diagnosis of new onset type 2 diabetes. At inclusion, a glucometry by means of a Continuous Glucose Monitoring System was performed, and DFA was calculated for a 24-h glucose time series. Patients were then followed up every 6 months, controlling for the development of diabetes. RESULTS: In a median follow-up of 18 months, there were 18 new cases of diabetes (58.5 cases/1000 patient-years). DFA was a significant predictor for the development of diabetes, with ten events in the highest quartile versus one in the lowest (log-rank test chi2 = 9, df = 1, p = 0.003), even after adjusting for other relevant clinical and biochemical variables. In a Cox model, the risk of diabetes development increased 2.8 times for every 0.1 DFA units. In a multivariate analysis, only fasting glucose, HbA1c and DFA emerged as significant factors. CONCLUSIONS: Detrended fluctuation analysis significantly performed as a harbinger of type 2 diabetes development in a high-risk population. Complexity analysis may help in targeting patients who could be candidates for intensified treatment. Copyright © 2016 The Authors. Diabetes/Metabolism Research and Reviews Published by John Wiley & Sons Ltd.

Differences in complexity of glycemic profile in survivors and nonsurvivors in an intensive care unit: a pilot study.

OBJECTIVE: To investigate glycemic dynamics and its relation with mortality in critically ill patients. We searched for differences in complexity of the glycemic profile between survivors and nonsurvivors in patients admitted to a multidisciplinary intensive care unit. DESIGN: Prospective, observational study, convenience sample. SETTINGS: Multidisciplinary intensive care unit of a teaching hospital in Madrid, Spain. PATIENTS: A convenience sample of 42 patients, aged 29 to 86 yrs, admitted to an intensive care unit with an Acute Physiology and Chronic Health Evaluation II score of >or=14 and with an anticipated intensive care unit stay of >72 hrs. INTERVENTIONS: A continuous glucose monitoring system was used to measure subcutaneous interstitial fluid glucose levels every 5 mins for 48 hrs during the first days of intensive care unit stay. A 24-hr period (n = 288 measurements) was used as time series for complexity analysis of the glycemic profile. MEASUREMENTS: Complexity of the glycemic profile was evaluated by means of detrended fluctuation analysis. Other conventional measurements of variability (range, sd, and Mean Amplitude of Glycemic Excursions) were also calculated. MAIN RESULTS: Ten patients died during their intensive care unit stay. Glycemic profile was significantly more complex (lower detrended fluctuation analysis) in survivors (mean detrended fluctuation analysis, 1.49; 95% confidence interval, 1.44-1.53) than in nonsurvivors (1.60; 95% confidence interval, 1.52-1.68). This difference persisted after accounting for the presence of diabetes. In a logistic regression model, the odds ratio for death was 2.18 for every 0.1 change in detrended fluctuation analysis.Age, gender, Simplified Acute Physiologic Score 3 or Acute Physiologic and Chronic Health Evaluation II scores failed to explain differences in survivorship. Conventional variability measurements did not differ between survivors and nonsurvivors. CONCLUSIONS: Complexity of the glycemic profile of critically ill patients varies significantly between survivors and nonsurvivors. Loss of complexity in glycemia time series, evaluated by detrended fluctuation analysis, is associated with higher mortality.

Detrended Fluctuation Analysis in the prediction of type 2 diabetes mellitus in patients at risk: Model optimization and comparison with other metrics.

Complexity analysis of glucose time series with Detrended Fluctuation Analysis (DFA) has been proved to be useful for the prediction of type 2 diabetes mellitus (T2DM) development. We propose a modified DFA algorithm, review some of its characteristics and compare it with other metrics derived from continuous glucose monitorization in this setting. Several issues of the DFA algorithm were evaluated: (1) Time windowing: the best predictive value was obtained including all time-windows from 15 minutes to 24 hours. (2) Influence of circadian rhythms: for 48-hour glucometries, DFA alpha scaling exponent was calculated on 24-hour sliding segments (1-hour gap, 23-hour overlap), with a median coefficient of variation of 3.2%, which suggests that analysing time series of at least 24-hour length avoids the influence of circadian rhythms. (3) Influence of pretreatment of the time series through integration: DFA without integration was more sensitive to the introduction of white noise and it showed significant predictive power to forecast the development of T2DM, while the pretreated time series did not. (4) Robustness of an interpolation algorithm for missing values: The modified DFA algorithm evaluates the percentage of missing values in a time series. Establishing a 2% error threshold, we estimated the number and length of missing segments that could be admitted to consider a time series as suitable for DFA analysis. For comparison with other metrics, a Principal Component Analysis was performed and the results neatly tease out four different components. The first vector carries information concerned with variability, the second represents mainly DFA alpha exponent, while the third and fourth vectors carry essentially information related to the two "pre-diabetic behaviours" (impaired fasting glucose and impaired glucose tolerance). The scaling exponent obtained with the modified DFA algorithm proposed has significant predictive power for the development of T2DM in a high-risk population compared with other variability metrics or with the standard DFA algorithm.

Delay in the Detrended Fluctuation Analysis Crossover Point as a Risk Factor for Type 2 Diabetes Mellitus.

Detrended Fluctuation Analysis (DFA) measures the complexity of a glucose time series obtained by means of a Continuous Glucose Monitoring System (CGMS) and has proven to be a sensitive marker of glucoregulatory dysfunction. Furthermore, some authors have observed a crossover point in the DFA, signalling a change of dynamics, arguably dependent on the beta-insular function. We investigate whether the characteristics of this crossover point have any influence on the risk of developing type 2 diabetes mellitus (T2DM). To this end we recruited 206 patients at increased risk of T2DM (because of obesity, essential hypertension, or a first-degree relative with T2DM). A CGMS time series was obtained, from which the DFA and the crossover point were calculated. Patients were then followed up every 6 months for a mean of 17.5 months, controlling for the appearance of T2DM diagnostic criteria. The time to crossover point was a significant predictor risk of developing T2DM, even after adjusting for other variables. The angle of the crossover was not predictive by itself but became significantly protective when the model also considered the crossover point. In summary, both a delay and a blunting of the crossover point predict the development of T2DM.

A randomized trial of citalopram versus placebo in outpatients with asthma and major depressive disorder: a proof of concept study.

BACKGROUND: The prevalence of asthma has increased in recent years and depression is common in this population. Minimal data are available on the treatment of depressed asthma patients. METHODS: Ninety adults with asthma and current major depressive disorder were randomized to receive citalopram or placebo for 12 weeks. At each visit, the Hamilton Rating Scale for Depression (HRSD), Inventory of Depressive Symptomatology - Self-Report, Asthma Control Questionnaire, and Asthma Quality of Life Questionnaire were administered, and oral corticosteroid use assessed. RESULTS: In the evaluable sample (n = 82), the primary outcome, a random regression analysis of HRSD scores, revealed no significant between-group differences. Bonferroni corrected secondary outcomes revealed HRSD scores decreased significantly in both groups with a significantly greater decrease in the citalopram group at week 6. Changes in asthma symptoms were similar between groups. The groups had similar rates of oral corticosteroid use at baseline, but the citalopram group had less corticosteroid use during the study. Changes in asthma symptom severity correlated with changes in depressive symptom severity. CONCLUSIONS: A reduction in depressive symptoms was associated with improvement in asthma. Corticosteroid use, an important measure of severe asthma exacerbations, was lower in the citalopram group. Larger clinical trials in this population are warranted.

Glucose series complexity at the threshold of diabetes.

BACKGROUND: One of the earliest signs of dysfunction in a complex system is the simplification of its output. A well-accepted method to measure this phenomenon is detrended fluctuation analysis (DFA). Herein, we evaluated the usefulness of DFA at the threshold of type 2 diabetes mellitus (T2DM). METHODS: We report on the clinical and glucometric characteristics of a sample of 103 patients at increased risk of developing T2DM. All patients had HbA1c levels 5%-6.4% and met at least one of the following criteria: body mass index (BMI) > 30 kg/m2, essential hypertension or a first-degree relative with T2DM. For each patient, a 24-h glucose time series was obtained, and the clinical and glucometric variables were compared. RESULTS: There was a significant correlation between the number of National Cholesterol Education Program--Adult Treatment Panel (ATP III) metabolic syndrome (MS)-defining criteria and DFA (ρ = 0.231, P = 0.019), and DFA differed significantly between patients meeting or not the ATP III definition of MS (1.443 vs. 1.399, respectively; P = 0.018). The DFA was not correlated with HbA1c. Depending on how it was calculated, the area under the log(Fn)∼log(n) curve correlated with HbA1c levels or the number of MS criteria. Conventional variability metrics (mean amplitude of glycemic excursions) did not differ between patients complying or not with the definition of MS. CONCLUSIONS: Complexity analysis is capable of detecting differences in variables related to the risk of developing T2DM and could be a useful tool to study the initial phases of glucoregulatory dysfunction leading to T2DM.

Glucose series complexity in hypertensive patients.

Nonlinear methods have been applied to the analysis of biological signals. Complexity analysis of glucose time series may be a useful tool for the study of the initial phases of glucoregulatory dysfunction. This observational, cross-sectional study was performed in patients with essential hypertension. Glucose complexity was measured with detrended fluctuation analysis (DFA), and glucose variability was measured by the mean amplitudes of glycemic excursion (MAGE). We included 91 patients with a mean age of 59 ± 10 years. We found significant correlations for the number of metabolic syndrome (MS)-defining criteria with DFA (r = 0.233, P = .026) and MAGE (r = 0.396, P < .0001). DFA differed significantly between patients who complied with MS and those who did not (1.44 vs. 1.39, P = .018). The MAGE (f = 5.3, P = .006), diastolic blood pressures (f = 4.1, P = .018), and homeostasis model assessment indices (f = 4.2, P = .018) differed between the DFA tertiles. Multivariate analysis revealed that the only independent determinants of the DFA values were MAGE (ß coefficient = 0.002, 95% confidence interval: 0.001-0.004, P = .001) and abdominal circumference (ß coefficient = 0.002, 95% confidence interval: 0.000015-0.004, P = .048). In our population, DFA was associated with MS and a number of MS criteria. Complexity analysis seemed to be capable of detecting differences in variables that are arguably related to the risk of the development of type 2 diabetes.

Cystatin C as a predictor of mortality and cardiovascular events in a population with chronic kidney disease.

Background. We examine whether cystatin C, a surrogate marker of renal function, could identify patients with chronic kidney disease (CKD) with an increased risk of renal disease progression, death, or cardiovascular events. Methods. Data were obtained for 180 patients, with a diagnosis of chronic renal failure based on serum creatinine estimated glomerular filtration rate (eGFRcreat) <90 mL/min/1.73 m(2). This population was grouped in tertiles according to cystatin C and creatinine values at baseline. Cardiovascular events and overall mortality were estimated for each tertile. Predictors of overall mortality and for the development of renal disease progression were analyzed. Results. The median age was 75 years (interquartile range 69-82) and the median eGFRcreat 38 mL/min m(2) (interquartile range 33-49). Overall mortality was lower on the first and on the second tertiles of cystatin C than on the third one (HR = 0.060; 95% CI: 0.008-0.447 and HR = 0.094; 95% CI: 0.022-0.406, resp.). Deaths related to the creatinine tertiles followed the same pattern, but differences were not as large. Cardiovascular mortality was lower on the second than on the third cystatin C tertile (HR = 0.198; 95% CI: 0.040-0.987), but it did not show differences on the first and the second creatinine tertiles compared with the third one (HR = 0.126; 95% CI: 0.013-1.265 and HR = 0.403; 95% CI: 0.093-1.740). The only independent predictors of mortality during followup were baseline cystatin C (OR = 0.100; 95% CI: 0.021-0.463) and baseline uric acid (OR = 1.377; 95% CI: 1.070-1.773). Conclusion. Cystatin C may be an alternative to creatinine for detecting a high risk of death and cardiovascular events in a population with CKD.

Association between urinary albumin excretion and both central and peripheral blood pressure in subjects with insulin resistance.

BACKGROUND: Central blood pressure (cBP) predicts cardiovascular events. Regarding subclinical organ damage, the relationship between urinary albumin excretion (UAE) and cBP is rather unknown. OBJECTIVE: We aimed to determine whether cBP is related to UAE, and if this relationship is stronger than that observed with peripheral blood pressure (pBP). METHODS: Three hundred and twenty-four hypertensives (61% men, aged 65 ±â€Š10 years) with insulin-resistance (77% diabetics; 23% nondiabetics with metabolic syndrome) were studied. Office pBP and cBP (radial applanation tonometry) were determined. UAE (albumin/creatinine) was averaged from three first-morning-void urine samples. Differences between patients with/without microalbuminuria, and the relationship between UAE and both pBP and cBP were analyzed. The strength of such relationship (cBP vs. pBP) was compared using a noninferiority test. RESULTS: Microalbuminuria was detected in 25% of all patients. After age-adjustment and sex-adjustment, both central and peripheral SBP and pulse pressure (PP) (mmHg) were higher in microalbuminurics than in normoalbuminurics [central SBP (cSBP): 130 ±â€Š20 vs. 124 ±â€Š19; peripheral (pSBP): 147 ±â€Š22 vs. 139 ±â€Š20; central pulse pressure (cPP): 52 ±â€Š15 vs. 47 ±â€Š14; peripheral pulse pressure (pPP): 67 ±â€Š16 vs. 62 ±â€Š16, P < 0.05 for all]. Partial correlation coefficients (age-adjusted and sex-adjusted) between blood pressure (BP) and UAE were 0.175 for cSBP, 0.143 for pSBP, 0.124 for cPP (P < 0.05 for all), and 0.092 for pPP (P = 0.117). Neither cBP nor pBP were superior to each other in their association with UAE or with microalbuminuria. Comparisons between cBP and pBP by means of noninferiority tests revealed no differences in the magnitude of correlation coefficients (P = 0.265 for SBP; P = 0.212 for PP), or differences in means between patients with/without microalbuminuria (P = 0.327 for SBP; P = 0.054 for PP). CONCLUSION: Although cBP is related with UAE, this relationship is not superior to that of office peripheral BP.

Cystatin C is associated with the metabolic syndrome and other cardiovascular risk factors in a hypertensive population.

Serum cystatin C has been associated with cardiovascular disease. We investigated whether cystatin C concentration is associated with the metabolic syndrome and with other cardiovascular risk factors in a hypertensive population. In this cross-sectional study, we prospectively included 611 essential hypertensive patients during a 12-month period. Cystatin C concentration was measured by nephelometry. The metabolic syndrome was present in 46% of the patients. Cystatin C was significantly higher in patients with the metabolic syndrome (0.94 +/- 0.27 mg/L) than in those without (0.87 +/- 0.23 mg/L) (P < .0001). Pearson partial correlation analysis showed a significant correlation between cystatin C and body mass index (r = 0.240; P = .001); waist circumference (r = 0.173; P = .012); microalbuminuria (r = 0.273; P < .0001); triglycerides (r = 0.138; P = .047); C-reactive protein (r = 0.190; P = .006); uric acid (r = 0.284; P < .0001); age (r = 0.409; P < .0001); and glomerular filtration rate (GFR) (r = -0.638; P < .0001). Multivariate analysis showed that GFR (B = -0.0061; 95% confidence interval [CI], -0.0073 to -0.0049; P < .0001), age (B = 0.0023; 95% CI, 0.0005-0.0041; P = .009), microalbuminuria (B = 0.0005; 95% CI, 0.0002-0.0007; P < .0001), uric acid (B = 0.0252; 95% CI, 0.0085-0.0418; P = .003), body mass index (B = 0.0051, 95% CI, 0.0012-0.0089; P = .011), and C-reactive protein (B = 0.0048; 95% CI, 0.0015-0.0082; P = .005) were independent determinants of cystatin C concentration. Measuring cystatin C concentration in hypertensive patients may be useful for evaluating their cardiovascular risk profile.

The route to diabetes: Loss of complexity in the glycemic profile from health through the metabolic syndrome to type 2 diabetes.

AIMS: In many physiologic systems, the evolution from health to disease correlates with a loss of complexity in the system's output. We analyze the difference in complexity of the glycemic profile in healthy volunteers (H), patients with the metabolic syndrome (MS), and patients with type 2 diabetes mellitus (DM). METHODS: We measured interstitial fluid glucose every 5 minutes for 3 days in 10 H, 10 MS, and 10 DM. Complexity of the glycemic profile was evaluated by means of detrended fluctuation analysis (DFA). Mean amplitude of glycemic excursions (MAGE) was also calculated. RESULTS: GLUCOSE PROFILE WAS MORE COMPLEX (LOWER DFA) IN HEALTHY SUBJECTS THAN IN PATIENTS WITH MS OR DM (MEAN DFA [SD]: H: 1.25 (0.10), MS: 1.39 (0.07), DM: 1.42 (0.10). ANOVA: F(2,27) = 9.94, p = 0.001). DM had also a less complex profile than MS, but this difference was not statistically significant. There was an inverse relation between complexity (lower DFA) and the number of MS defining criteria (rho = 0.55, p = 0.002) and between complexity and MAGE (r = 0.68, p < 0.0001). CONCLUSIONS: There is a progressive loss of complexity in the glycemic profile from health, through the metabolic syndrome to type 2 diabetes mellitus. This loss of complexity precedes hyperglycemia and correlates with other markers of disease progression. Complexity analysis may be a useful tool to track the evolution from health to type 2 diabetes. Furthermore, it may provide a way to measure glycemic control in real-life situations and has some distinct advantages over other conventional variability metrics.

Development of chronic kidney disease and cardiovascular prognosis in essential hypertensive patients.

The existence of a significant percentage of treated hypertensive patients presenting a diminished renal function has been recently described. Mild renal function abnormalities are recognized as powerful predictors of cardiovascular morbidity and mortality. However, longitudinal data demonstrating this association are lacking. The objectives of this study have been analysis of the evolution of GFR, assessed as creatinine clearance (CrCl), during long-term follow-up of hypertensive patients and evaluation of the impact of the development of chronic kidney disease (CKD) on cardiovascular prognosis. A historical cohort of 281 patients attending our Hypertension Unit was selected according to the following criteria: essential hypertension, more than 5 yr of follow-up, and normal GFR at baseline (CrCl > 90 ml/min per 1.73 m(2)). Patients had an average follow-up of 13.2 +/- 4.8 yr. Forty-one patients (14.6%) developed CKD (CrCl < 60 ml/min per 1.73 m(2)) attributed to hypertensive nephrosclerosis. Initial serum creatinine, age, systolic BP at baseline, and average total cholesterol during follow-up were independent predictors of CKD development. Forty-nine (17.4%) of 281 patients presented a cardiovascular event during follow-up: 17 patients (40.6%) who developed CKD and 32 patients (13.3%) with preserved renal function (log rank test P < 0.001). After adjustment in a Cox multivariate analysis, age, development of CKD during follow-up, and male gender were independent predictors of the appearance of cardiovascular events. In essential hypertensive patients with normal renal function at baseline, the development of CKD during the follow-up is strongly and independently related with poor cardiovascular prognosis.

Hypertensive renal damage in metabolic syndrome is associated with glucose metabolism disturbances.

Recent evidence highlights the relationship between metabolic syndrome (MS) and increased risk of cardiovascular (CV) diseases. Mild renal function abnormalities are associated with an enhanced CV risk, considered to be due to the presence of associated risk factors. Hence, MS and renal abnormalities could be linked and contribute to augment CV risk. For estimating the prevalence of diminished creatinine clearance (CC; <60 ml/min per 1.73 m(2)) in hypertensive patients with or without MS and for investigating the factors accompanying this abnormality, 1625 hypertensive patients, aged 18 yr or older, were included. The presence of MS was defined according to the Adult Treatment Panel III criteria. The overall prevalence of MS was 49.4% (n = 802). No significant difference was found for CC between those with and without MS, albeit the presence of MS was accompanied by greater urinary albumin excretion (P = 0.01). The prevalence of a diminished CC was also similar in the two groups. MS-positive patients presented a progressive decay in CC when classified as normoglycemic (n = 319), impaired fasting glucose (n = 237), and diabetic patients (n = 246; 85.9 +/- 30.2, 81.8 +/- 26.8, and 75.2 +/- 25.7 ml/min per 1.73 m(2), respectively; P = 0.0007 linearity test) and the opposite for microalbuminuria (29.5 +/- 45.5, 45.0 +/- 96.6, and 74.1 +/- 146.3 mg/24 h, respectively; P = 0.001 linearity test). In multiple regression analysis, factors related to the finding of a diminished CC in MS and non-MS patients were similar. Hypertensive patients at a relatively young age present with an elevated prevalence of minor abnormalities of renal function that is mostly related to the presence of metabolic alteration of glucose together with age and BP.