Borja Vargas

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 (β coefficient = 0.002, 95% confidence interval: 0.001-0.004, P = .001) and abdominal circumference (β 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.

Glucose time series complexity as a predictor of type 2 diabetes

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.

Glucose series complexity at the threshold of diabetes.

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).

Glucose series complexity at the threshold of diabetes 糖尿病阈值的血糖序列的复杂性

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).

Patterns with Equal Values in Permutation Entropy: Do They Really Matter for Biosignal Classification?

Two main weaknesses have been identified for permutation entropy (PE): the neglect of subsequence pattern differences in terms of amplitude and the possible ambiguities introduced by equal values in the subsequences. A number of variations or customizations to the original PE method to address these issues have been proposed in the scientific literature recently. Specifically for ties, methods have tried to remove the ambiguity by assigning different weighted or computed orders to equal values. Although these methods are able to circumvent such ambiguity, they can substantially increase the algorithm costs, and a general characterization of their practical effectiveness is still lacking. This paper analyses the performance of PE using several biomedical datasets (electroencephalogram, heartbeat interval, body temperature, and glucose records) in order to quantify the influence of ties on its signal class segmentation capability. This capability is assessed in terms of statistical significance of the PE differences between classes and classification sensitivity and specificity. Being obvious that ties modify the PE results, we hypothesize that equal values are intrinsic to the acquisition process, and therefore, they impact all the classes more or less equally. The experimental results confirm ties are often not the limiting factor for PE, even they can be beneficial as a sort of stochastic resonance, and it can be far more effective to focus on the embedding dimension instead.

NONALCOHOLIC STEATOHEPATITIS IN A HYPERTENSIVE POPULATION

Objective: Nonalcoholic steatohepatitis (NASH) is strongly associated with overweight or obesity, the Metabolic Syndrome (MS) and type 2 diabetes mellitus (DM2). Our objective was to analyse their relationship with essential hypertension, a condition frequently linked to these pathologies. Design and method: Prospective, cross-sectional study conducted in a Hypertension Unit. We defined NASH as the presence of ultrasound hepatic steatosis with the increase in AST > 1.5 times high-reference laboratory values, in the absence of other causes of hepatopathy and with an alcohol intake less of 30 g/day (males) and 15 g/day (females). Results: We included a total of 2251 patients (51.3% males), with an average age of 56 years and a BMI of 30. 57% had MS and 11.5% DM2. 91 patients (4%) presented NASH criteria (4.9% males and 3.1% females, p = 0.032). Patients with NASH had higher abdominal circumference (106 vs. 100 cm, p < 0.0001), uric acid (6.4 vs. 5.8 mg/dl, p = 0.002), triglycerides (162 vs. 128 mg/dl, p = 0.005), basal glycaemia (116 vs. 107 mg/ dl, p = 0.026), HbA1c (6.5% vs. 6.1%, p = 0.015), basal insulin (18.4 vs. 13 mUI/ml, p = 0.025), DBP (83 vs. 80 mmHg, p = 0.036), ferritin (365 vs. 157 mg/dl, p < 0.0001), prevalence of MS (78% vs. 56%, p < 0.0001) and DM2 (20% vs.11%, p = 0.017). NASH also correlated with the number of MS factors (r = 0.045, p = 0.035). In the multivariate analysis, the variables independently associated with NASH were the abdominal circumference (Exp.(B) = 1034, 95%CI: 1001–1.068, p = 0.042), uric acid (Exp.(B) = 1.263, 95%CI: 1.005–1.588, p = 0.045), ferritin (Exp.(B) = 1.003, 95%CI: 1.002–1.005, p < 0.0001), the presence of MS (Exp.(B) = 4.358, 95%CI: 1.001–19.529, p = 0.005) and DM2 (Exp.(B) = 2.399, 95%CI: 1.040–5.537, p = 0.04). Triglycerides, basal glycaemia, HbA1c, basal insulin and DBP resulted excluded in the final model (model R2: 0.49). Conclusions: In our patients NASH was independently associated with the presence of DM2 and MS and with several of the defining or related components of MS. Thus NASH can represent the hepatic correlation of MS in essential hypertension.

INSULINE RESISTANCE AND CHRONIC RENAL DISEASE IN A HYPERTENSIVE POPULATION

Objective: Both insulin resistance (IR) and metabolic syndrome (MS) has been related with the presence or the development of chronic renal disease (CRD). Our aim was to analyse this association in a hypertensive population. Design and method: Prospective, observational study conducted in a Hypertension Unit. We defined MS by ATP-III criteria, IR as the presence of a HOMA-index > 75% percentile (4.4) and the presence of CRD as an eGFR (EPI-creatinine equation) < 60 ml/min /1.73m2 and /or the presence of albuminuria (<30 mg/gr. creatinine, average of two consecutive days samples). Results: We include 773 patients (50.8% males) with a mean age of 54 years. 54.7% had MS. 64% of the patients with MS presented IR and just 8.5% had IR without MS. 21% had CRD: 11.9% with albuminuria, 9.1% with eGFR < 60 ml/min./1.73 m2 and 2.5% with both criteria. In univariate analisys the presence of CRD was associated with MS (28% vs. 18%, p = 0.05) and with IR (29% vs. 22%, p = 0.05). In multivariate analisys (logistic regression), including in a first model the MS and IR and adjusted by sex and age, the MS but no IR was associated with the presence of CRD (OR = 1.63, p = 0.014). In a second model, including as variables all the defining MS-criteria and adjusted as well by sex and age, the presence of CRD was independently associated with the abdominal circumference (OR = 1.020, p = 0.023), HDL-cholesterol (OR = 0.980, p = 0.016) and SBP (OR = 1.012, p = 0.039). In this last model just the HOMA-index was independently associated with a eGFR < 60 ml/min/1.73 m2 (OR = 1.064, p = 0.042) whereas the presence de albuminuria was associated with the abdominal circumference (OR = 1.022, p = 0.028), HDL-cholesterol (OR = 0.976, p = 0.022) and SBP (OR = 1.020, p = 0.002). Conclusions: In our hypertensive patients the simultaneous presence of MS an IR was frequent, resulting scanty the presence of IR without MS. An decreased eGFR was independently associated with HOMA-index and the presence of albuminuria with several components of MS. So, HOMA-index measurement can be an useful tool in the evaluation of renal prognosis of these patients.

New insights from continuous glucose monitoring into the route to diabetes

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.

Classification of glucose records from patients at diabetes risk using a combined permutation entropy algorithm

BACKGROUND AND OBJECTIVES The adoption in clinical practice of electronic portable blood or interstitial glucose monitors has enabled the collection, storage, and sharing of massive amounts of glucose level readings. This availability of data opened the door to the application of a multitude of mathematical methods to extract clinical information not discernible with conventional visual inspection. The objective of this study is to assess the capability of Permutation Entropy (PE) to find differences between glucose records of healthy and potentially diabetic subjects. METHODS PE is a mathematical method based on the relative frequency analysis of ordinal patterns in time series that has gained a lot of attention in the last years due to its simplicity, robustness, and performance. We study in this paper the applicability of this method to glucose records of subjects at risk of diabetes in order to assess the predictability value of this metric in this context. RESULTS PE, along with some of its derivatives, was able to find significant differences between diabetic and non-diabetic patients from records acquired up to 3 years before the diagnosis. The quantitative results for PE were 3.5878 ± 0.3916 for the nondiabetic class, and 3.1564 ± 0.4166 for the diabetic class. With a classification accuracy higher than 70%, and by means of a Cox regression model, PE demonstrated that it is a very promising candidate as a risk stratification tool for continuous glucose monitoring. CONCLUSION PE can be considered as a prospective tool for the early diagnosis of the glucoregulatory system.

Development of a Novel Scheme for Long-Term Body Temperature Monitoring: A Review of Benefits and Applications

Body temperature is a health or disease marker that has been in clinical use for centuries. The threshold currently applied to define fever, with small variations, is 38 °C. However, current approaches do not provide a full picture of the thermoregulation process and its correlation with disease. This paper describes a new non-invasive body temperature device that improves the understanding of the pathophysiology of diseases by integrating a variety of temperature data from different body locations. This device enables to gain a deeper insight into fever, endogenous rhythms, subject activity and ambient temperature to provide anticipatory and more efficient treatments. Its clinical use would be a big step in the overcoming of the anachronistic febrile/afebrile dichotomy and walking towards a system medicine approach to certain diseases. This device has already been used in some clinical applications successfully. Other possible applications based on the device features and clinical requirements are also described in this paper.