12 research outputs found
Insulin resistance and arterial stiffness: impact of gestational diabetes on pulse wave velocity
Background: Gestational diabetes is an intolerance of glucose with the first appearance during the pregnancy. This hyperglycaemia status, because of the pre-existing insulin-resistance, constitute a favourable land of arterial stiffness. The aim of this study is to determine the impact of non obese gestational diabetes on arterial stiffness by measuring the pulse wave velocity (PWV).Methods: We recruited 60 pregnant women aged from 20 to 35 years old. They were between twentieth four and thirtieth five weeks of gestational age. Subjects were divided into two groups: the first group (G1), considered as control group, included 25 normoglycemic pregnant subjects without any history of illness or risk factors of gestational diabetes; the second group (G2) included 35 women with Gestational Diabetes Mellitus (GDM). All pregnant women had not history of smoking, were not taking decoction or medicine, which could disturb pregnancy evolution. Anthropo-physiological and biochemical parameters studied, were: age, body mass index (BMI), blood pressure (BP), triglyceride, cholesterol and HOMA-IR index. The PWV between finger and toe (PWVft) was measured by pOpmètre®.Results: The two groups are matched by age (G1:28±4ans; G2:29±3ans) and BMI (G1:25.6±1.27; G2:26.9±1.3). Blood pressure (BP) values are in normal interval (systolic BP: [110-132mmHg]; diastolic BP: [63-87mmHg]; mean BP: [79-103mmHg]). Total cholesterol (G1:0.95±0.08;G2:2.4±0.7; p˂0.0001), HDL cholesterol (G1:0.44±0.02; G2:0.76±0.2; p˂0.0001, LDL cholesterol (G1:0.40±0.05; G2:1.3±0.5; p˂0.0001), triglyceride (G1:0.57±0.45; G2:1.6±0.4;p˂0.0001), HOMA.IR (G1:1.31±1.05; G2:7.4±1.07; p˂0.01), PWVft (G1:5.99±1.23; G2:10.3±1.9; p˂0.0001) are significantly higher in diabetic group. PWVft is positively correlate to HOMA-IR index, total cholesterol, LDL cholesterol and triglycerides (r=0.3348, p=0.032; r=0.5275, p˂0.0001; r=0.4855,p˂0.0001; r=0.5581, p˂0.0001respectively).Conclusions: Gestational diabetes might induce an increase of pulse wave velocity expressing increment of arterial stiffness. This last constitute an early underlying cardiovascular risk.
High blood viscosity is associated with high pulse wave velocity in African sickle cell trait carriers
Background: Sickle cell trait (SCT) is the benign condition of sickle cell disease. Often asymptomatic, the SCT carriers have hemorheological disturbances such as blood hyper-viscosity compared to healthy subjects. These disturbances could lead to structural and functional changes in large vessels. The aim of the study was to evaluate the association between blood viscosity (ηb) and pulse wave velocity (PWV) in SCT carriers.Methods: Thirteen SCT with high blood viscosity (SCT_hηb) aged 34±12 years (4 men) were compared to 13 SCT with low blood viscosity (SCT_lηb) aged 32±9 years (5 men) recruited from the National Blood Transfusion Center (CNTS) in Dakar (Senegal). Pulse wave velocity finger-toe (PWVft) was assessed using pOpmètre® (Axelife SAS-France). Cardiovascular risk (CVR) was assessed according to the Framingham Laurier score.Results: SCT_hηb had higher PWVft (m/s) than SCT_lηb respectively 8.98±1.98 and 7.11±1.18 (p = 0.004). CVR score (%) was higher in SCT_hηb than SCT_lηb, but this difference was not statistically significant (5.96±7.45 vs 2.09±2.15; p=0.31). Multivariate linear regression showed a positive correlation between PWVft and ηb and CVR score (r2=0.74, F=21.19, p˂0.001).Conclusions: Present results indicate that the SCT_hηb carriers have arteries stiffer than SCT_lηb and ηb and CVR could remain independent determinants of arterial stiffness in SCT carriers
Evaluation of the pulse wave velocity in African rheumatoid arthritis subjects
Background: Rheumatoid arthritis is a systemic disease with often fatal vascular events. In addition to traditional cardiovascular risk factors, disease-specific elements contribute to this cardiovascular mortality. The aim of this study was to assess arterial stiffness in rheumatoid arthritis and to determine the factors involved.Methods: We have recruited the black African patients followed in rheumatology and had rheumatoid arthritis diagnosis. Only patients between 18 and 60 years and meeting the American College of Rheumatology criteria were included. All controls were healthy. We evaluated the propagation velocity of the pulse wave finger-toe (PWVft) measured by the pOpmètre®.Results: Present study shows that the PWVft was significantly elevated in over half of patients (55.10%). Besides, the mean patients PWVft was significantly higher than that of the control (respectively 9.40±0.51 and 7.22±0.33 p=0.001). In the patients, no factor was significantly involved in the arterial stiffness, but cons in the control group, the PWVft was significantly correlated with age (p=0.023 and r=0.55).Conclusions: Rheumatoid arthritis patients had higher PWVft compared to controls. Due to the importance of its cardiovascular morbidity and mortality, arthritis requires a regular monitoring element as arterial stiffness, which is currently a major vascular parameter monitoring
On the potential of AI based health assessment from photopletysmographic signals
International audienceOn the potential of AI based health assessment from photopletysmographic signal
Diabetes Detection and Management through Photoplethysmographic and Electrocardiographic Signals Analysis: A Systematic Review
International audienc
Type 2 diabetes detection with light CNN from single raw PPG wave
International audiencePhotoplethysmography (PPG) is a non-invasive and cost-efficient optical technique used to assess blood volume variations in the microcirculation. PPG technology is widely used in a variety of wearable sensors to investigate the cardiovascular system. Recent studies have demonstrated the utility of PPG analysis for carrying out large-scale screening to prevent and detect diabetes. However, most of these studies require feature extraction and/or several pre-processing steps. Over the past few years, the advent of deep learning has significantly impacted the analysis of biomedical signals. Despite their success in other fields, however, very few studies have focused on the application of deep learning to raw PPG signals for detecting diabetes. Existing studies have proposed large models trained on large amounts of data. In this paper, we present a Light CNN-based model for screening the presence of type 2 diabetes using a single raw pulse extracted from photoplethysmographic signals. In addition to the baseline architecture, we evaluate different model architectures that take as input age and biological sex or PPG handcrafted features. Furthermore, we apply transfer learning to all the tested architectures to evaluate the effectiveness of harnessing pre-trained models in detecting diabetes. We tested a model pre-trained on a general PPG shape dataset and another model pre-trained on a dataset containing hypertension PPG signals. Our model scored an AUC of 75.5 when trained with raw PPG waves, age, and biological sex without applying transfer learning, which is competitive with current state of the art
An extended one-dimensional arterial network model dor the simulation of pressure and flow in upper and lower limb extremities
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Clustered photoplethysmogram pulse wave shapes and their associations with clinical data.
Peer reviewed: TruePhotopletysmography (PPG) is a non-invasive and well known technology that enables the recording of the digital volume pulse (DVP). Although PPG is largely employed in research, several aspects remain unknown. One of these is represented by the lack of information about how many waveform classes best express the variability in shape. In the literature, it is common to classify DVPs into four classes based on the dicrotic notch position. However, when working with real data, labelling waveforms with one of these four classes is no longer straightforward and may be challenging. The correct identification of the DVP shape could enhance the precision and the reliability of the extracted bio markers. In this work we proposed unsupervised machine learning and deep learning approaches to overcome the data labelling limitations. Concretely we performed a K-medoids based clustering that takes as input 1) DVP handcrafted features, 2) similarity matrix computed with the Derivative Dynamic Time Warping and 3) DVP features extracted from a CNN AutoEncoder. All the cited methods have been tested first by imposing four medoids representative of the Dawber classes, and after by automatically searching four clusters. We then searched the optimal number of clusters for each method using silhouette score, the prediction strength and inertia. To validate the proposed approaches we analyse the dissimilarities in the clinical data related to obtained clusters
High blood viscosity is associated with high pulse wave velocity in African sickle cell trait carriers
Background: Sickle cell trait (SCT) is the benign condition of sickle cell disease. Often asymptomatic, the SCT carriers have hemorheological disturbances such as blood hyper-viscosity compared to healthy subjects. These disturbances could lead to structural and functional changes in large vessels. The aim of the study was to evaluate the association between blood viscosity (ηb) and pulse wave velocity (PWV) in SCT carriers.Methods: Thirteen SCT with high blood viscosity (SCT_hηb) aged 34±12 years (4 men) were compared to 13 SCT with low blood viscosity (SCT_lηb) aged 32±9 years (5 men) recruited from the National Blood Transfusion Center (CNTS) in Dakar (Senegal). Pulse wave velocity finger-toe (PWVft) was assessed using pOpmètre® (Axelife SAS-France). Cardiovascular risk (CVR) was assessed according to the Framingham Laurier score.Results: SCT_hηb had higher PWVft (m/s) than SCT_lηb respectively 8.98±1.98 and 7.11±1.18 (p = 0.004). CVR score (%) was higher in SCT_hηb than SCT_lηb, but this difference was not statistically significant (5.96±7.45 vs 2.09±2.15; p=0.31). Multivariate linear regression showed a positive correlation between PWVft and ηb and CVR score (r2=0.74, F=21.19, p˂0.001).Conclusions: Present results indicate that the SCT_hηb carriers have arteries stiffer than SCT_lηb and ηb and CVR could remain independent determinants of arterial stiffness in SCT carriers
Pulse wave velocity is lower in trained than in untrained sickle cell trait carriers
International audienceSickle cell trait (SCT) is a benign condition of sickle cell disease. Nevertheless, previous reports showed that SCT carriers have increased blood viscosity and decreased vascular reactivity compared to non-SCT carrier. The benefit of regular exercise on vascular function has been well documented in the general population but no study focused on the SCT population