143 pubblicazioni classificate nel seguente modo:

Fifty Years of Biomedical Engineering: From Origin to Smart Technologies
The First Outstanding 50 Years of "Università Politecnica delle Marche"
Autore/i: Burattini, Laura; Di Nardo, Francesco; Morettini, Micaela; Verdini, Federica; Fioretti, Sandro
Classificazione: 2 Contributo in Volume
Abstract: In Italy, the Bioengineering Community was founded in 1980. The kick-off meeting was held in Montesicuro, a little village near Ancona and organized by Prof. Tommaso Leo from the then-named “Università degli Studi di Ancona” (now Università Politecnica delle Marche, UNIVPM) in cooperation with the nascent National Group of Bioengineering. This chapter aims to produce a brief review of the main results in Biomedical Engineering by UNIVPM during the first 50 years useful to understand the present and to track future contributions for the next 50 years. It is also an occasion to recall the pioneering work on the Bioengineering of the Neuromuscular, Cardiovascular and Metabolic systems performed by our leading colleagues Tommaso Leo, Paolo Mancini and Roberto Burattini, as well as to describe significant research achievements obtained by professors, researchers, post-doc fellows and PhD students who worked and/or are currently working at the UNVPM. Though mainly focusing on research findings in the above cited physiological systems, it is also worth mentioning in this chapter that UNIVPM has also an educational mission, provided by the two Biomedical Engineering courses currently active at the Engineering Faculty: the three-year Bachelor and the two-year Master (in English) courses.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/278101

Digital cardiotocography: What is the optimal sampling frequency?
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
Autore/i: Romagnoli, Sofia; Sbrollini, Agnese; Burattini, Luca; Marcantoni, Ilaria; Morettini, Micaela; Burattini, Laura
Classificazione: 1 Contributo su Rivista
Abstract: Cardiotocography (CTG) is the most popular prenatal diagnostic test for establishing fetal health and consists in simultaneous recording of fetal heart rate (FHR, bpm) and maternal uterine contraction (UC, mmHg) traces. Typically, FHR and UC traces are visually analyzed and interpreted by clinicians. Recently, software applications like CTG Analyzer have been developed to support visual CTG interpretation by making it more objective and independent from clinician’s experience. Automatic CTG analysis requires CTG-traces digitalization and thus assessment of a correct sampling frequency (SF). Thus, this paper aims to investigate dependency of automatic CTG analysis on SF in order to identify optimal SF (OSF) for FHR and UC traces that minimizes computational efforts without jeopardizing CTG interpretation. To this aim, the “CTU-CHB intra-partum CTG database” was considered and visually annotated by an expert gynecologist. FHR and UC traces, originally sampled at 4 Hz, were down sampled at 2 Hz, 1 Hz, 0.4 Hz and 0.2 Hz, and automatically analyzed using CTG Analyzer. Eventually, results obtained through automatic analysis were compared to visual annotations, which were taken as reference. A cumulative statistical index (CSI), ranging from 0.00% to 100.00%, was defined as a linear combination of positive-predictive value, sensitivity, false-positive rate and false-negative rate. OSF was defined as the one that maximizes CSI. If CSI was showing the same value for more than one SF, the lowest SF was selected as the optimal since minimizing computational efforts. Results indicate that OSF for FHR is 2 Hz (CSI ≥ 85.41%), whereas OSF for UC is 0.2 Hz (CSI = 75.21%).
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/264306

Surface electromyography low-frequency content: Assessment in isometric conditions after electrocardiogram cancellation by the Segmented-Beat Modulation Method
INFORMATICS IN MEDICINE UNLOCKED
Autore/i: Sbrollini, Agnese; Strazza, Annachiara; Candelaresi, Silvia; Marcantoni, Ilaria; Morettini, Micaela; Fioretti, Sandro; Di Nardo, Francesco; Burattini, Laura
Classificazione: 1 Contributo su Rivista
Abstract: Background: Surface electromyography (SEMG) is widely used in clinics for assessing muscle functionality. All procedures proposed for noise reduction alter SEMG spectrum, especially in the low-frequency band (below 30 Hz). Indeed, low-frequency band is generally addressed to motion artifacts and electrocardiogram (ECG) interference without any further investigation on the possibility of SEMG having significant spectral content. The aim of the present study was evaluating SEMG frequency content to understand if low-frequency spectral content is negligible or, on the contrary, represents a significant SEMG portion potentially providing relevant clinical information. Method: Isometric recordings of five muscles (sternocleidomastoideus, erectores spinae at L4, rectus abdominis, rectus femoris and tibialis anterior) were acquired in 10 young healthy voluntary subjects. These recordings were not affected by motion artifacts by construction and were pre-processed by the Segmented-Beat Modulation Method for ECG deletion before performing spectral analysis. Results: Results indicated that SEMG frequency content is muscle and subject dependent. Overall, the 50th[25th;75th] percentiles spectrum median frequency and spectral power below 30 Hz were 74[54; 87] Hz and 18[10; 31] % of total (0–450 Hz) spectral power. Conclusions: Low-frequency spectral content represents a significant SEMG portion and should not be neglected.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/262204

GPU-Based Segmented-Beat Modulation Method for Denoising Athlete Electrocardiograms During Training
Computing in Cardiology
Autore/i: Nasim, Amnah; DELLA SANTA, Edoardo; Tanchi, Damiano; Sbrollini, Agnese; Marcantoni, Ilaria; Morettini, Micaela; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Sport-related sudden cardiac death (SRSCD), defined as “death occurring during sport or within one hour of cessation of training”, is the leading cause of death in athletes. SRSCD occurs in the presence of underlying cardiovascular diseases, some of which may be identified by processing electrocardiographic recordings acquired during training (TECGs). A fast and accurate processing of TECGs during or immediately after training is challenging since TECGs are typically highly corrupted by noise and interferences, which may jeopardize their interpretation and identification of abnormal morphologies. The present study evaluated the ability of GPU-based Segmented-Beat Modulation Method (GPUSBMM) to provide a noise-free estimation of TECGs, and to improve the algorithm by GPU acceleration to make it compatible with modern hardware. In this research, 19 6- to-10 min TECGs (sampling frequency: 256 Hz), acquired from 8 subjects while performing 4 different exercise tasks (walk, run, low-resistance bike and high-resistance bike), were analyzed. Results indicate that GPU-SBMM application yielded a significant increase of SNR(dB) (from 1±5 dB to 19±5 dB; p<10-12 ), also when stratifying by exercise tasks. Additionally, a considerable average speedup of 7.67x is achieved using NVIDIA GeForce 740M GPU processor.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/264729

Automatic Identification of Atrial Fibrillation by Spectral Analysis of Fibrillatory Waves
Computing in Cardiology
Autore/i: Sbrollini, Agnese; Cicchetti, Krizia; DE MARTINIS, Alessia; Marcantoni, Ilaria; Morettini, Micaela; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: A heart affected by atrial fibrillation (AF) presents atrial cells that depolarize in many sites, generating a chaotic electrical activity. On the electrocardiogram (ECG), this activity reflects in the appearance of fibrillatory (F) waves, consisting of low-amplitude oscillations at 4-10 Hz. Aim of the present study is to propose an automatic AF identification method based on F-wave frequency analysis in 10 s ECGs. To this aim, 10 s ECG from 90 healthy subjects (HSs) and 50 AF patients (AFPs) were considered. ECGs were processed by the segmented beat modulation method to reduce components in the F-wave band. Then, the power spectral density (PSD) was computed and the F-wave frequency ratio (FWFR), defined as the ratio between the spectral area in the F-wave frequency band and the total spectral area, was computed. FWFR ability to discriminate AFPs from HSs was evaluated by analyzing the area under the curve (AUC) of the receiver operating characteristic, and by computation of sensitivity, specificity and accuracy. FWFR values were higher in AFPs than in HSs (P<10-11). AUC was at least 85%, whereas sensitivity, specificity and accuracy were at least 84%, 69% and 81%, respectively. In conclusion, F-wave frequency evaluation by FWFR represents a promising clinical tool to automatically identify AF.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/264734

TWA Simulator: a Graphical User Interface for T-wave Alternans
Computing in Cardiology
Autore/i: Morettini, Micaela; Marchesini, Lorenzo; Pettinari, LUCA ALBERTO; Tigrini, Andrea; Marcantoni, Ilaria; Sbrollini, Agnese; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: T-wave alternans (TWA) is an every-other-beat fluctuation of the T-wave amplitude, often at microvolt (invisible) levels. It is recognized as an important risk index of severe ventricular arrhythmias, leading sometimes to sudden cardiac arrest. Many algorithms for automatic detection and quantification of TWA have been proposed; when applied to the same electrocardiogram (ECG), they may provide a different TWA quantification, making interpretation of differences difficult. Aim of this work is to propose TWA Simulator as a useful tool to validate and compare TWA identification methods. TWA Simulator is a user-friendly MATLAB graphical user interface (GUI) able to generate, model, visualize and store simulated ECG (SECG) affected by TWA of known morphology and amplitude. SECG is constructed by a Nfold repetition of a template, constituted by a real and clean ECG beat. Both number of beats and RR inter-beat variability can be set by the user. Both direct and inverted TWA can be simulated. Direct TWA is simulated by adding a waveform (among four possibility) to every other T wave; inverted TWA is simulated by changing T-wave polarity in every-other SECG beat. Availability of TWA Simulator would allow efficient validation and comparison of automatic TWA identification methods by helping interpretation of results
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/264735

Automatic Identification and Classification of Fetal Heart-Rate Decelerations from Cardiotocographic Recordings
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Autore/i: Sbrollini, Agnese; Carnicelli, Amalia; Massacci, Alessandra; Tomaiuolo, Leonardo; Zara, Tommaso; Marcantoni, Ilaria; Burattini, Luca; Morettini, Micaela; Fioretti, Sandro; Burattini, Laura
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Cardiotocography (CTG) consists in the simultaneous recording of two distinct traces, the fetal heart rate (FHR; bpm) and the maternal uterine contractions (UCs; mmHg). CTG analysis consists in the evaluation of specific features of traces, among which fetal decelerations (DECs) are considered the 'center-stage' since possibly related to fetal distress. DECs are classified based on their duration and occurrence in relation to UCs as prolonged, early, late and variable; each class associates to a specific status of the fetus health. Typically, CTG traces are visually interpreted; however, computerized CTG analysis may overcome subjectivity in CTG interpretation. Thus, this study proposes a new automatic algorithm for computerized identification and classification of DECs. The algorithm was tested on the 552 CTG recordings constituting the 'CTU-CHB intra-partum CTG database' of Physionet. Of these, 470 (85.15%) were found suitable for automatic DECs identification and classification. Overall, 5888 DECs were identified, of which 3255 (55.28%) were classified while the other 2633 (44.72%) remained unclassified due to very strict preliminary classification criteria (now required for avoiding misclassifications). Among the classified DECs, 468 (14.38%) were classified as prolonged, 1498 (46.02%) as early, 32 (0.98%) as late, 1257 (38.62%) as variable. Thus, among the classified DECs, the most common are the early and the variable ones (overall 84.64%), the occurrence of which ranged from 0 to 14 DECs per recording. These findings are in agreement with what reported in literature. In conclusion, the proposed algorithm for automatic DECs identification and classification represents a useful tool for computerized CTG analysis.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/262590

PCG-Delineator: an Efficient Algorithm for Automatic Heart Sounds Detection in Fetal Phonocardiography
Computing in Cardiology
Autore/i: Strazza, Annachiara; Sbrollini, Agnese; di Battista, Valeria; Ricci, Rita; Trillini, Letizia; Marcantoni, Ilaria; Morettini, Micaela; Fioretti, Sandro; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Fetal phonocardiography (FPCG) is a non-invasive electronic recording of the acoustic cardiac signals. Unfortunately, FPCG is hidden by high-amplitude noise which makes detection of FPCG waveforms challenging. Aim of the study is to propose PCG-Delineator as an algorithm for automatic detection of the first and second heart sound (S1 and S2, respectively) from FPCG. To this aim, 37 simulated FPCG tracings (Physionet) are filtered by a wavelet-based procedure (4th order Coiflets mother wavelet with 7 decomposition levels) to erase noise. Successively, S1 and S2 are detected. S1 detection procedure is threshold-based (threshold=30% of the filtered FPCG signal maximum amplitude), under the condition that 40ms separate two consecutive S1 sounds. S2 detection procedure is also threshold-based, but under the conditions that S2 has to fall 100ms after preceding S1 and 200ms before successive S1, and that S2 has to have an amplitude lower than 80% that of preceding S1. Sensitivity (SE) and positive predictive values (PPV) were computed. Results indicate that PCG-Delineator was able to reduce noise (our SNR: from -1.1÷7.4dB to 12.9÷17.9dB; P<10-14) and to accurately detect both S1 (SE: 88%; PPV: 91%) and S2 (SE: 77%; PPV:99%). In conclusion, PCG-Delineator is an efficient algorithm for automatic heart sounds detection in FPCG.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/264730

Personalizing physical exercise in a computational model of fuel homeostasis
PLOS COMPUTATIONAL BIOLOGY
Autore/i: Palumbo, M. C.; Morettini, M.; Tieri, P.; Diele, F.; Sacchetti, M.; Castiglione, F.
Classificazione: 1 Contributo su Rivista
Abstract: The beneficial effects of physical activity for the prevention and management of several chronic diseases are widely recognized. Mathematical modeling of the effects of physical exercise in body metabolism and in particular its influence on the control of glucose homeostasis is of primary importance in the development of eHealth monitoring devices for a personalized medicine. Nonetheless, to date only a few mathematical models have been aiming at this specific purpose. We have developed a whole-body computational model of the effects on metabolic homeostasis of a bout of physical exercise. Built upon an existing model, it allows to detail better both subjects’ characteristics and physical exercise, thus determining to a greater extent the dynamics of the hormones and the metabolites considered.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/277113

Assessment of glucose effectiveness from short IVGTT in individuals with different degrees of glucose tolerance
ACTA DIABETOLOGICA
Autore/i: Morettini, Micaela;   ·, Francesco  Di  Nardo; Burattini, Laura; Fioretti, Sandro; Christian  Göbl,   ·; Alexandra  Kautzky‑Willer,   ·; Giovanni  Pacini,   ·; Andrea  Tura,   ·
Classificazione: 1 Contributo su Rivista
Abstract: Aims Minimal model analysis of intravenous glucose tolerance test (IVGTT) data represents the reference method to assess insulin sensitivity (SI) and glucose effectiveness (SG) that quantify the insulin-dependent and insulin-independent processes of glucose disappearance, respectively. However, test duration (3 h) and need for modeling expertise limit the applicability of this method. Aim of this study was providing a simple predictor of SG applicable to short test (1 h), as previously done with SI. Methods Three groups of subjects reflecting different glucose tolerance degrees underwent a 3 h IVGTT: subjects with normal glucose tolerance (NGT, n = 164), with defective glucose regulation (DGR, n = 191), and with type 2 diabetes (T2D, n = 39). Minimal model analysis provided reference SG and its components at zero (GEZI) and basal (BIE) insulin. The simple predictor CSG (calculated SG) was described by the formula CSG = α0 + α1 × KG/Gpeak, being KG the glucose disappearance rate (between 10 and 50 min) and Gpeak the maximum of the glucose curve during the test; α0 and α1 coefficients were provided by linear regression analysis. Results CSG and SG showed a markedly significant relationship in the whole dataset (r = 0.72, p < 0.0001) and in the single groups (r = 0.70 in NGT, r = 0.71 in DGR and r = 0.70 in T2D, p < 0.0001 for all); α1 × KG/Gpeak was significantly related to GEZI (r ≥ 0.60). Conclusions The interest for insulin-independent glucose disappearance is increasing, due to the recent availability of SGLT2 pharmacological agents, lowering glycemic levels without requiring insulin action. This study proposes a reliable predictor of SG based on IVGTT lasting 1 h only, and not requiring mathematical modeling skills.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/260624

Electrocardiogram Derived Respiratory Signal through the Segmented-Beat Modulation Method
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Autore/i: Pambianco, Benedetta; Sbrollini, Agnese; Marcantoni, Ilaria; Morettini, Micaela; Fioretti, Sandro; Burattini, Laura
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Respiration rate and variability are indicators of health-condition changes. In chronic disease management, it is becoming increasingly desirable to use wearable devices in order to minimize invasiveness and maximize comfort. However, not all wearable devices integrate sensors for direct acquisition of respiratory (DAR) signal. In these cases, the breathing extraction can be done through indirect methods, typically from the electrocardiogram (ECG). The aim of the present study is to propose a single-ECG-lead procedure based on the Segmented-Beat Modulation Method (SBMM) as a suitable tool for ECG-derived respiratory (EDR) signal estimation and respiration frequency (RF) identification. Clinical data consisted of combined measurements of two-lead (I and II) ECG and DAR signals from 20 healthy subjects ('CEBS' database by Physionet). Each respiration-affected ECG lead was submitted to a specifically designed SBMMbased procedure for EDR estimation by ECG subtraction. RF from EDR and DAR were identified as the frequency at which the Fourier spectrum has a maximum in the 0.07-1.00 Hz frequency range. Results indicated that mean RF values over the population from EDR signals (0.27 ± 0.09 Hz and 0.27 ± 0.09 Hz from leads I and II, respectively) were not significantly different from that from DAR (0.28 ± 0.09 Hz). Moreover, differences in RF identification (0.01 ± 0.03 Hz and 0.00 ± 0.02 Hz from leads I and II, respectively) were, on average not significantly different from 0. Thus, SBMM-based procedure is robust and accurate for EDR estimation and RF identification.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/262588

Automatic T-Wave Alternans Identification in Indirect and Direct Fetal Electrocardiography
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Autore/i: Marcantoni, Ilaria; Sbrollini, Agnese; Burattini, Luca; Morettini, Micaela; Fioretti, Sandro; Burattini, Laura
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Fetal T-wave alternans (TWA) is a still littleknown marker for severe fetus-heart instabilities and may be related to some currently unjustified fetal deaths. Automatically detecting TWA on direct fetal electrocardiograms (DFECG) means possibility of providing fetuses the right treatment during delivery. Instead, automatically identifying TWA on indirect fetal electrocardiograms (IFECG) means possibility of providing fetuses the right treatment even during pregnancy, when taking actions for outcome improvement is still possible. Moreover, TWA identification from IFECG is noninvasive, and thus safe for both fetuses and mothers. The aim of this work was testing the heart-rate adaptive match filter (HRAMF) for automatic TWA identification in IFECG and comparing HRAMF performance in IFECG against DFECG. To this aim, simultaneously recorded DFECG and IFECG tracings from 5 healthy fetuses were used ('Abdominal and Direct Fetal Electrocardiogram Database' from Physionet). TWA measurements (frequency, mean amplitude, maximum amplitude, and amplitude standard deviation) in IFECG (1.09±0.04 Hz, 11±5 μV, 21±12 μV and 7±3 μV) were of the same order of magnitude of those in DFECG (1.07±0.02 Hz, 9±2 μV, 30±11 μV and 6±2 μV). Moreover, a direct correlation (ñ) was found between maximum TWA and fetal heart rate (IFECG: ρ=0.999; P=0.022; DEFEG: ρ=0.642; P=0.243). Thus, HRAMF was able to detect TWA from IFECG as well as from DFECG.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/262587

eCTG: an automatic procedure to extract digital cardiotocographic signals from digital images
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
Autore/i: Sbrollini, Agnese; Agostinelli, Angela; Marcantoni, Ilaria; Morettini, Micaela; Burattini, Luca; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Classificazione: 1 Contributo su Rivista
Abstract: Background and objective: Cardiotocography (CTG), consisting in the simultaneous recording of fetal heart rate (FHR) and maternal uterine contractions (UC), is a popular clinical test to assess fetal health status. Typically, CTG machines provide paper reports that are visually interpreted by clinicians. Consequently, visual CTG interpretation depends on clinician's experience and has a poor reproducibility. The lack of databases containing digital CTG signals has limited number and importance of retrospective studies finalized to set up procedures for automatic CTG analysis that could contrast visual CTG interpretation subjectivity. In order to help overcoming this problem, this study proposes an electronic procedure, termed eCTG, to extract digital CTG signals from digital CTG images, possibly obtainable by scanning paper CTG reports. Methods: eCTG was specifically designed to extract digital CTG signals from digital CTG images. It includes four main steps: pre-processing, Otsu's global thresholding, signal extraction and signal calibration. Its validation was performed by means of the “CTU-UHB Intrapartum Cardiotocography Database” by Physionet, that contains digital signals of 552 CTG recordings. Using MATLAB, each signal was plotted and saved as a digital image that was then submitted to eCTG. Digital CTG signals extracted by eCTG were eventually compared to corresponding signals directly available in the database. Comparison occurred in terms of signal similarity (evaluated by the correlation coefficient ρ and the mean signal error MSE) and clinical features (including FHR baseline and variability; number, amplitude and duration of tachycardia, bradycardia, acceleration and deceleration episodes; number of early, variable, late and prolonged decelerations; and UC number, amplitude, duration and period). Results: The value of ρ between eCTG and reference signals was 0.85 (P < 10−560) for FHR and 0.97 (P < 10−560) for UC. On average, MSE value was 0.00 for both FHR and UC. No CTG feature was found significantly different when measured in eCTG vs. reference signals. Conclusions: eCTG procedure is a promising useful tool to accurately extract digital FHR and UC signals from digital CTG images.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/255236

T-Wave Alternans in Partial Epileptic Patients
Computing in Cardiology
Autore/i: Marcantoni, Ilaria; Cerquetti, Valeria; Cotechini, Valentina; Lattanzi, Maeva; Sbrollini, Agnese; Morettini, Micaela; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Epilepsy is a chronic neurological disorder, hallmark of which is unpredictable epileptic seizures (ES). The leading cause of death in people with uncontrolled ES is the sudden unexpected death in epilepsy (SUDEP), which is believed to share genes with sudden cardiac death (SCD). Being T-wave alternans (TWA) an ECG index of SCD, aim of this work was to evaluate TWA occurrence in proximity of ES. Electrocardiograms (ECG) from five partial epileptic patients constituting the “Post-Ictal Heart Rate Oscillations in Partial Epilepsy” Database by Physionet were analysed for automatic TWA identification by the heart-rate adaptive match filter (HRAMF). ES onsets and offsets were annotated. ECG segments starting 10min before ES and ending 10min after ES were extracted and further processed to characterize trends of median heart rate, median TWA (mTWA) and maximum TWA (MTWA) in ES proximity. Levels of mTWA were significantly higher than what previously observed in a female healthy population in all ES (46[25;59]µV), pre-ES (31[25;62]µV) and post-ES (30[26;63]µV) conditions. Both mTWA and MTWA tended to increase during ES. Thus, in proximity of ES, our epileptic patients are at increased risk of SCD, possibly associated with SUDEP. Other studies defining TWA role as a biomarker for SUDEP are needed.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/264731

Simple assessment of insulin sensitivity in the zucker rat
IFMBE Proceedings
Autore/i: Morettini, Micaela; Faelli, E.; Perasso, L.; Fioretti, Sandro; Burattini, Laura; Ruggeri, P.; DI NARDO, Francesco
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The model-based assessment of insulin sensitivity in Zucker rat from Intravenous Glucose Tolerance Test (IVGTT) data is a common procedure. The minimal model methodology provides a very reliable assessment but requires specific competence for running the model. The aim of this study was presenting calculated SI (CSI), as a surrogate index for the simple assessment of insulin sensitivity in the Zucker Rat from IVGTT data. To this aim 25 Zucker Lean Rats (ZLR) and 25 Zucker Fatty Rats (ZFR) were considered. Reference insulin sensitivity (SI) was estimated in each rat through the minimal model methodology. CSI is defined as the ratio between the rate of glucose disappearance (KG) and the mean supra-basal area under the insulin curve during the test (ΔAUCINS), corrected by the proportionality term, α. Regression analysis between SI and KG/ΔAUCINS was performed to identify the α coefficient. Results showed as the computed value of CSI presented a high correlation (r = 0.89, R-square = 0.80 and p < 0.0001, slope ≈1) with SI. Mean value of CSI over the whole population was not significantly different from correspondent SI value (p = 0.17). CSI is able to detect the well-known reduction of insulin sensitivity in the ZFR group (1.0±0.1 vs. 5.0±0.7 min-1/μU·ml-1, p < 0.001), in accordance with the results provided by SI. In conclusion, the present study proposes CSI, as a suitable empiric index for a simple and reliable assessment of insulin sensitivity in Zucker rat and able to provide the same quantitative information of model-based SI.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250217

Second heart sound onset to identify T-wave offset
Computing in Cardiology
Autore/i: Sbrollini, Agnese; Bartoli, Marta Beghella; Agostinelli, Angela; Morettini, Micaela; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Phonocardiography (PCG) second heart sound represents aortic-pulmonary valves closure and beginning of isovolumetric relaxation of the ventricles. Electrocardiography (ECG) T wave represents electrical repolarization of the ventricles. Ventricular electrical repolarization is known to drive ventricular mechanical relaxation. Thus, the aim of the present study was to investigate whether, in normal conditions, second heart sound onset (S2on) matches in time T-wave offset (Toff) so that S2on may be used to identify Toff. To this aim, 99 couples of simultaneously recorded short (around 30 s PCG and ECG) signals relative to normal subjects (selected from PhysioNet/CinC Challenge 2016: Training Set A) were analyzed. S2on was identified by application of our newly developed threshold-based algorithm to the median beat of the PCG envelope. Instead, Toff was identified by application of the Laguna and Thakor algorithm to the median ECG beat. Median time-distance (δt) between S2on and Toff was 5 ms (P=0.007). Thus, in normal conditions, S2on and Toff differ on average of 5 ms, whose meaning remain to be defined. Still, 5 ms is included in the Toff identification variability (of the order of tens ms) due to different Toff identification methods and electrocardiographic leads. Consequently, in normal condition, S2on may be used to estimate Toff
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259389

IVGTT-based simple assessment of glucose tolerance in the Zucker fatty rat: Validation against minimal models
PLOS ONE
Autore/i: Morettini, Micaela; Faelli, Emanuela; Perasso, Luisa; Fioretti, Sandro; Burattini, Laura; Ruggeri, Piero; DI NARDO, Francesco
Classificazione: 1 Contributo su Rivista
Abstract: For the assessment of glucose tolerance from IVGTT data in Zucker rat, minimal model methodology is reliable but time- and money-consuming. This study aimed to validate for the first time in Zucker rat, simple surrogate indexes of insulin sensitivity and secretion against the glucose-minimal-model insulin sensitivity index (SI) and against first- (φ1) and second-phase (φ2) β-cell responsiveness indexes provided by C-peptide minimal model. Validation of the surrogate insulin sensitivity index (ISI) and of two sets of coupled insulinbased indexes for insulin secretion, differing from the cut-off point between phases (FPIR3- SPIR3, t = 3 min and FPIR5- SPIR5, t = 5 min), was carried out in a population of ten Zucker fatty rats (ZFR) and ten Zucker lean rats (ZLR). Considering the whole rat population (ZLR+ZFR), ISI showed a significant strong correlation with SI (Spearman's correlation coefficient, r = 0.88; P<0.001). Both FPIR3 and FPIR5 showed a significant (P<0.001) strong correlation with φ1 (r = 0.76 and r = 0.75, respectively). Both SPIR3 and SPIR5 showed a significant (P<0.001) strong correlation with φ2 (r = 0.85 and r = 0.83, respectively). ISI is able to detect (P<0.001) the well-recognized reduction in insulin sensitivity in ZFRs, compared to ZLRs. The insulin-based indexes of insulin secretion are able to detect in ZFRs (P<0.001) the compensatory increase of first- and second-phase secretion, associated to the insulinresistant state. The ability of the surrogate indexes in describing glucose tolerance in the ZFRs was confirmed by the Disposition Index analysis. The model-based validation performed in the present study supports the utilization of low-cost, insulin-based indexes for the assessment of glucose tolerance in Zucker rat, reliable animal model of human metabolic syndrome.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/245897

Epidemiology/Genetics
DIABETES
Autore/i: Morettini, Micaela; DI NARDO, Francesco; Burattini, Laura; Fioretti, Sandro; Tura, Andrea; Pacini, Giovanni
Classificazione: 1 Contributo su Rivista
Abstract: Two are the main processes regulating post-challenge glucose uptake: one insulin-dependent, and the other mainly due to glucose disappearance per se (glucose effectiveness, SG, min-1), accounting for 60-80% of the whole disappearance. Aim of this study was providing an easy method for assessing SG with a short IVGTT (regular). Three groups of subjects were considered: CNT (control subjects, with normal glucose tolerance: n=158), PRE (subjects with prediabetes and/or pathologies causing insulin resistance: n=220), and T2D (subjects with type 2 diabetes: n=31). Fasting glucose and insulin (mean±SD) were 4.7±0.6, 4.8±0.9, 5.9±1.0 mmol·L-1 and 8.3±3.8, 12.3±9.3, 11.0±4.3 pmol·L-1, for CNT, PRE, T2D, respectively. Reference SG was assessed by Minimal Model analysis. In all grouped subjects, regression analyses were performed to identify a simple predictor (calculated SG, CSG) of reference SG, yielding CSG=α0+α1·KG/Gpeak, with KG slope of the glucose curve (10-50 min), Gpeak maximum glucose, α0=0.007 and α1=0.141. We found SG=0.022±0.010 min-1 and CSG=0.021±0.007 min-1. CSG showed excellent correlation with SG (r=0.65, p<0.001). Similar results were found in each group (r=0.64, p<0.001 in CNT, r=0.63, p<0.001 in PRE, r=0.75, p<0.001 in T2D). Also, SG and CSG were not significantly different, both in all subjects (p=0.34, paired t-test) and in the single groups (p>0.10). Bland-Altman analysis confirmed the substantial equivalence of the two indices, showing only 5% of samples outside the limits of agreement (both in all subjects and the single groups). When comparing SG and CSG among groups, both indices consistently showed lower values in PRE and T2D compared to CNT (p<0.008 for SG and p<0.0001 for CSG, by ANOVA). In conclusion, the first 50 minutes of the IVGTT are sufficient to yield a reliable estimation of glucose effectiveness through a simple approach, not requiring sophisticated mathematical modeling.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/255420

No changes in glucose effectiveness in condition of reduced insulin action but preserved glucose tolerance as assessed by minimal model analysis
IFMBE Proceedings
Autore/i: Morettini, Micaela; DI NARDO, Francesco; Fioretti, Sandro; Pacini, G.; Tura, A.; Burattini, Laura
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Glucose effectiveness (SG) represents the ability of glucose per se, under basal insulin concentrations, to stimulate its own uptake and to suppress its own production. SG and its two components BIE (Basal Insulin Effect) and GEZI (Glucose Effectiveness at Zero Insulin) are known to decline in subjects whose glycemic status worsens, but no study aimed to analyze whether changes may occur even before, when a normal glucose tolerance status is still preserved but insulin resistance has already arisen. To investigate this issue, SG, BIE and GEZI were estimated from the minimal model interpretation of frequently sampled intravenous glucose tolerance (FSIGT) test data in two groups of subjects with normal glucose tolerance (basal glycemia < 5.6 mmol/l): a group of control participants (CNT, n=50) and a group of subjects with pathologies or conditions causing insulin resistance (IR, n=50). No difference in mean values of SG was observed in the IR with respect to the CNT group (2.3 ± 0.9 vs. 2.5 ± 0.9 10-2 min-1; p = 0.17). BIE was found to be the minor component of SG in both CNT and IR group. The GEZI component provided a significantly higher proportional contribution to SG in the IR with respect to CNT (89% vs. 81% of SG, p <0.0001). In proportion, a significantly lower contribution was provided by BIE in IR group (11 ± 1 vs. 18 ± 1, p <0.0001). These results indicate that, at the real starting phase of the process of glucose tolerance impairment (reduced insulin action but normal tolerance), no variation in SG occurs with respect to normality. An increased proportional contribution of GEZI, when BIE declines, may allow the maintenance of normal glucose effectiveness.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250219

CTG Analyzer: A graphical user interface for cardiotocography
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Autore/i: Sbrollini, Agnese; Agostinelli, Angela; Burattini, Luca; Morettini, Micaela; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Cardiotocography (CTG) is the most commonly used test for establishing the good health of the fetus during pregnancy and labor. CTG consists in the recording of fetal heart rate (FHR; bpm) and maternal uterine contractions (UC; mmHg). FHR is characterized by baseline, baseline variability, tachycardia, bradycardia, acceleration and decelerations. Instead, UC signal is characterized by presence of contractions and contractions period. Such parameters are usually evaluated by visual inspection. However, visual analysis of CTG recordings has a well-demonstrated poor reproducibility, due to the complexity of physiological phenomena affecting fetal heart rhythm and being related to clinician's experience. Computerized tools in support of clinicians represents a possible solution for improving correctness in CTG interpretation. This paper proposes CTG Analyzer as a graphical tool for automatic and objective analysis of CTG tracings. CTG Analyzer was developed under MATLAB®; it is a very intuitive and user friendly graphical user interface. FHR time series and UC signal are represented one under the other, on a grid with reference lines, as usually done for CTG reports printed on paper. Colors help identification of FHR and UC features. Automatic analysis is based on some unchangeable features definitions provided by the FIGO guidelines, and other arbitrary settings whose default values can be changed by the user. Eventually, CTG Analyzer provides a report file listing all the quantitative results of the analysis. Thus, CTG Analyzer represents a potentially useful graphical tool for automatic and objective analysis of CTG tracings.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/255424

Statistical baseline assessment in cardiotocography
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Autore/i: Agostinelli, Angela; Braccili, Eleonora; Marchegiani, Enrico; Rosati, Riccardo; Sbrollini, Agnese; Burattini, Luca; Morettini, Micaela; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Cardiotocography (CTG) is the most common non-invasive diagnostic technique to evaluate fetal well-being. It consists in the recording of fetal heart rate (FHR; bpm) and maternal uterine contractions. Among the main parameters characterizing FHR, baseline (BL) is fundamental to determine fetal hypoxia and distress. In computerized applications, BL is typically computed as mean FHR±ΔFHR, with ΔFHR=8 bpm or ΔFHR=10 bpm, both values being experimentally fixed. In this context, the present work aims: to propose a statistical procedure for ΔFHR assessment; to quantitatively determine ΔFHR value by applying such procedure to clinical data; and to compare the statistically-determined ΔFHR value against the experimentally-determined ΔFHR values. To these aims, the 552 recordings of the 'CTU-UHB intrapartum CTG database' from Physionet were submitted to an automatic procedure, which consisted in a FHR preprocessing phase and a statistical BL assessment. During preprocessing, FHR time series were divided into 20-min sliding windows, in which missing data were removed by linear interpolation. Only windows with a correction rate lower than 10% were further processed for BL assessment, according to which ΔFHR was computed as FHR standard deviation. Total number of accepted windows was 1192 (38.5%) over 383 recordings (69.4%) with at least an accepted window. Statistically-determined ΔFHR value was 9.7 bpm. Such value was statistically different from 8 bpm (P<10-19) but not from 10 bpm (P=0.16). Thus, ΔFHR=10 bpm is preferable over 8 bpm because both experimentally and statistically validated.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/255427

Overnight T-wave alternans in sleep apnea patients
Computing in Cardiology
Autore/i: Burattini, Laura; Ciotti, Ilaria; D'Ignazio, Michela; Miccoli, Alessandro; Agostinelli, Angela; Sbrollini, Agnese; Morettini, Micaela; Di Nardo, Francesco; Fioretti, Sandro
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Sleep apnea (SA) is linked to cardiovascular complications and to an increased risk of sudden cardiac death. Microvolt T-wave alternans (TWA) is a noninvasive electrocardiographic (ECG) index of cardiovascular risk; its rate of occurrence in SA patients remains unknown. Thus, this study investigated the occurrence of TWA in SA patients during night. To this aim, overnight ECG recordings of 16 SA patients were analyzed for TWA identification by means of our heart rate adaptive match filter. Results indicate that overnight TWA was characterized by a low mean amplitude (mean TWA: 6±3 µV). However, higher-amplitude transient TWA episodes (max TWA: 29±21 µV) occurred overnight, sometimes when patients were awake (max TWA: 33±18 µV; 56% of cases) and sometimes when patients were sleeping (max TWA: 24±23 µV; 44% of cases with 13%, 19%, 6% and 6% during sleep stage 1, 2, 3 and 4, respectively). In only 3 subjects (19%) TWA peaks occurred during an SA episode: during obstructive apnea with arousal in two cases (max TWA of 7 µV and 17 µV, during stages 1 and 2, respectively) and during hypoapnea with arousal in one case (max TWA of 6 µV while awake). Thus, SA patients show significant transient overnight TWA episodes, not necessarily occurring during a SA episode.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259391

Separation of superimposed electrocardiographic and electromyographic signals
IFMBE Proceedings
Autore/i: Sbrollini, Agnese; Agostinelli, Angela; Morettini, Micaela; Verdini, Federica; DI NARDO, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Electrocardiography (ECG) and surface electromyography (SEMG) are two non-invasive tests to evaluate cardiac and muscular functionality, respectively. They are both acquired by placing electrodes on the body surface so they become one the interference of the other. Typically, linear filters are used for ECG and SEMG separation: high-pass filters with cutoff at 20 Hz to attenuate ECG interference in SEMG, and low-pass filters with cut-off at 50 Hz to attenuate SEMG interference in ECG. In spite of that, linear filtering is not adequate due to the presence of a 20-50 Hz frequency-band in which the two signal spectra overlap. The aim of the present study was to evaluate the ability of the Segmented-Beat Modulation Method (SBMM) for ECG and SEMG separation and by accurately maintaining signals characteristics. SBMM is a template-based technique for ECG denoising: under the hypothesis of ECG and SEMG linearly superimposed, it first provides an ECG estimation, and then an SEMG estimation by subtraction. In order to test the method under several conditions, SBMM was applied to simulated as well as clinical recordings with superimposed ECG and SEMG. SBMM was able to accurately estimate both ECG and SEMG in all cases. Indeed, ECG and SEMG were estimated by maintain their features such as amplitude (estimation errors <6%), heart rate and heart-rate variability. Moreover, estimated ECG was always characterized by a spectrum mostly (76.4-100.0%) included in the 0-50 Hz frequency-band, whereas estimated SEMG was always characterized by a spectrum mostly (80.9-95.6%) included in the 20-450 Hz frequency-band. Such results confirm the existence of a 20-50 Hz frequency-band in which ECG and SEMG spectral components are overlapped. Thus, SBMM is a robust filtering procedure to separate superimposed ECG and SEMG.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250221

AThrIA: A new adaptive threshold identification algorithm for electrocardiographic P Waves
Computing in Cardiology
Autore/i: Sbrollini, Agnese; Mercanti, Sofia; Agostinelli, Angela; Morettini, Micaela; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Proposed algorithms for P-wave identification and segmentation usually search for it within a window just before the R peak, thus hypothesizing the presence of at most one P wave, as it is in a normal electrocardiographic (ECG) tracings. In presence of abnormal atrial depolarization, however, there might be no P waves (as in atrial fibrillation) or multiple P waves (as in second- or third-degree atrioventricular blocks). Thus, this study proposes a new Adaptive Threshold Identification Algorithm (AThrIA) for ECG P-waves whose most innovative feature is to look for P waves all along the heartbeat, potentially allowing multiple Pwaves identification. AThrIA ability to identify and segment (finding onset, maximum and offset) P waves was tested in simulated and experimental ECG tracings with no P waves, one P wave and two P waves, respectively. All P waves involved in the study were annotated. Results indicate that AThrIA correctly identified all P waves (no false-negative or false-positive detections). Segmentation errors were 0 ms for the simulated ECG tracings, and no more than 10 ms for the experimental tracings. Thus, AThrIA represents a promising tool for P-wave identification and segmentation in both physiological (one P wave) and pathological (none or multiple P waves) conditions.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259393

Association between accelerations and decelerations of fetal heart rate
IFMBE Proceedings
Autore/i: Agostinelli, Angela; Belgiovine, G.; Fiorentino, M. C.; Turri, G.; Sbrollini, Agnese; Burattini, Laura; Morettini, Micaela; DI NARDO, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Cardiotocography (CTG) is the most popular test for establishing the fetal health status. Among its characterizing features there are the fetal heart rate (FHR) accelerations (ACC), usually considered a sign of fetal well-being; and decelerations (DEC), some of which may indicate the risk of fetal hypoxia. Thus, ACC and DEC are usually considered independent phenomena possibly providing opposite information on the fetus clinical status. CTG is typically analyzed by visual inspection; still a computerized analysis may provide a more objective CTG interpretation and precise ACC and DEC characterization. Aim of the present study is to propose an automatic procedure for ACC and DEC identification and characterization, and to investigate a potential relationship between their occurrence. The 552 tracings of the Physionet “CTU-CHB intra-partum CTG database” were analyzed according to a procedure that includes: FHR pre-processing; 20 min windowing; baseline estimation; and ACC and DEC identification and characterization. Specifically, ACC and DEC were defined as FHR deviations from baseline of at least 15 bpm for at least 15 s and then characterized in terms of length (s), amplitude (bpm) and area (length·amplitude; bpm·s). Only 383 (69.4%) CTG recordings showed sufficiently good FHR signal quality to be enrolled in the study. Number of DEC per window was significantly higher than ACC (4.0 vs 2.5; P<10-14). DEC were characterized by a comparable length but higher amplitude and area than ACC (LNG: 56 s vs 61 s, P=0.2573; AMP: 12 bpm vs 10 bpm, P<10-11; AREA: 688 s·bpm vs 618 s·bpm, P=0.0032). DEC total area in a 20-min window was higher than that of ACC (3074 s·bpm vs 2007 s·bpm, P<10-9), but such areas were also strictly correlated (ρ=0.72; P<10-62). Thus, in a CTG recording, ACC and DEC are not independent phenomena but their occurrence is strictly associated.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250213

T-Wave alternans identification in direct fetal electrocardiography
Computing in Cardiology
Autore/i: Marcantoni, Ilaria; Vagni, Marica; Agostinelli, Angela; Sbrollini, Agnese; Morettini, Micaela; Burattini, Luca; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Very little is known about the incidence and etiology of fetal T-wave alternans (TWA), an electrophysiologic phenomenon potentially associated to fetal suboptimal outcomes. Thus, availability of automatic methods for quantification of TWA from digital electrocardiograms (ECG) is desirable, since TWA occurrence might indicate the need of taking actions before or during delivery. The heart-rate adaptive match filter (HRAMF) is a wellestablished method to identify TWA in adult ECG. Aim of the present study was to investigate the possibility of using HRAMF to identify and quantify TWA also in direct fetal ECG (DFECG) recordings. To this aim, HRAMF was applied to 5 min-long DFECG acquired during delivery (“Abdominal and Direct Fetal Electrocardiogram Database” by Physionet) of five healthy fetuses. Significant levels of TWA were measured in all DFECG. Specifically, on average, TWA was quite high in amplitude (9±2 µV) and variable in time, as indicated by values of standard deviation (6±2 µV) and maximum (28±10 µV) of TWA amplitude. Eventually, a positive correlation (ρ=0.68) was observed between maximum TWA and fetal heart rate, even though the limited number of recordings makes this result preliminary. In conclusion, HRAMF proved to be a suitable tool to automatically identify TWA from DFECG.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259390

Quantification of fetal ST-segment deviations
Computing in Cardiology
Autore/i: Agostinelli, Angela; Di Cosmo, Mariachiara; Sbrollini, Agnese; Burettini, Luca; Morettini, Micaela; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: By fetal electrocardiogram (FECG) analysis it has been found that changes in the ST segment are associated with acid-base status, and thus fetus health state. Currently, the most popular estimation of fetal STsegment deviations is performed as ratio between T-wave height and QRS-complex amplitude using the STAN monitor. Thus, this evaluation is indirect because not directly derived from measurements on the ST segment. This study proposes a new procedure for an automated direct quantification of fetal ST-segment deviations, which are described in terms of ST-amplitude and STtrend. Particularly, ST-amplitude corresponds to the maximum of the mean amplitude values obtained through a moving-average (15 ms) operation over the ST segment. Instead, ST-trend corresponds to the difference between the ST-segment amplitudes calculated in the first and the last of three intervals in which the ST segment is divided; thus, ST-trend sign indicates a ST-segment elevation (positive sign) or depression (negative sign). The procedure was evaluated on five direct FECG recordings (in https://physionet.org/physiobank/database/adfecgdb/). Mean values (over population) of ST-amplitude and STtrend were 9.6 ± 5.5 μV and 1.4 ± 2.3 μV, respectively. All found values were validated by visual inspection of the magnified FECG plots.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259395

Fetal phonocardiogram denoising by wavelet transformation: Robustness to noise
Computing in Cardiology
Autore/i: Sbrollini, Agnese; Strazza, Annachiara; Caragiuli, Manila; Mozzoni, Claudia; Tomassini, Selene; Agostinelli, Angela; Morettini, Micaela; Fioretti, Sandro; Di Nardo, Francesco; Burattini, Laura
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Fetal phonocardiography (fPCG) is a clinical test to assess fetal wellbeing during pregnancy, labor and delivery. Still, its interpretation may be jeopardized by the presence of noise. Specifically, fPCG is typically corrupted by maternal heart and body organs sounds, fetal movements noise and surrounding environment noise. Thus, appropriate filtering procedures have to be applied in order to make fPCG clinically usable. Wavelet transformation (WT) has been proposed to filter fPCG; however, WT robustness to noise remains unknown. Thus, aim of the present work is to evaluate WT ability and robustness to denoise fPCG characterized by varying signal-to-noise ratios (SNR). To this aim a filtering procedure based on Coiflets mother wavelet (4th order, 7 levels of decomposition) was applied to 37 fPCG simulated tracings, all available in the Simulated Fetal PCGs database by Physionet. Original SNR values ranged from -1.38 dB to 4.54 dB; after application of WT-filtering procedure to fPCG, SNR increased significantly, ranging from 12.95 dB to 17.94 dB (P<10- 14). Moreover, SNR values before and after filtering were associated by a low correlation (ρ=0.4; P=0.01). Eventually, WT filtering introduced no fPCG signal delay and left heart rate unaltered. Thus, WT filtering is a suitable and robust technique to denoise fPCG signals.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259394

CaRiSMA 1.0: Cardiac risk self-monitoring assessment
THE OPEN SPORTS SCIENCES JOURNAL
Autore/i: Agostinelli, Angela; Morettini, Micaela; Sbrollini, Agnese; Maranesi, Elvira; Migliorelli, Lucia; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Classificazione: 1 Contributo su Rivista
Abstract: Background: Sport-related sudden cardiac death (SRSCD) can only be fought through prevention. Objective: The aim of this study is to propose an innovative software application, CaRiSMA 1.0 (Cardiac Risk Self-Monitoring Assessment), as a potential tool to help contrasting SRSCD and educating to a correct training. Methods: CaRiSMA 1.0 analyzes the electrocardiographic and heart-rate (HR) signals acquired during a training session through wearable sensors and provides intuitive graphical outputs consisting of two traffic lights, one related to cardiac health, based on resting QTc (a parameter quantifying the duration of ventricular contraction and subsequent relaxation), and one related to training, based on exercise HR. Safe and worthwhile training sessions have green traffic lights. A red QTc traffic light indicates the need of a medical consultation, whereas a red HR traffic light indicate the need of a reduction of training intensity. By way of example, CaRiSMA 1.0 was applied to sample data acquired in 10 volunteers (age= 27±11 years; males/females 3/7). Results: Two acquisitions (20.0%) were rejected because too noisy, indicating that wearable sensors may record poor quality signals. The QTc traffic light was red in 1 case, indicating that people practicing sport may not be aware of being at risk. The HR traffic light was red in 0 cases. Conclusion: CaRiSMA 1.0 is a software application that, for the first time in the sport context, uses QTc, the most important index of cardiac risk in clinics. Thus, it has the potential for giving a contribution in the fight against SRSCD.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/252423

The relative role of insulin action and secretion in experimental animal models of metabolic syndrome
IFMBE Proceedings
Autore/i: Morettini, Micaela; DI NARDO, Francesco; Cogo, C. E.; Faelli, E.; Fioretti, Sandro; Burattini, Laura; Ruggeri, P.
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In the present study we evaluated insulin action and secretion in a group of 7 young Zucker fatty rats (ZFR), and in a group of 8 spontaneously hypertensive rats (SHR), compared with two control groups of 7 young Zucker lean rats (ZLR) and 8 Wistar Kyoto rats (WKY), respectively. Our goal is to broaden the characterization of glucose tolerance, including insulin secretion, in two animal models used for the characterization of human metabolic syndrome: the ZFR and the SHR. Reliable estimates of insulin sensitivity index, SI, was provided by minimal model analysis of IVGTT data. To characterize insulin secretion we calculated an index based on IVGTT data: AIRG, i.e. the acute insulin response after glucose bolus, related to the first phase insulin secretion. The ZFR showed a significantly (p<0.005) lower mean estimate of SI, and a significantly (p<0.001) higher mean value of AIRG, compared to control groups (ZLR and WKY) and hypertensive rats (SHR). Thus, only the ZFR shows a reduced insulin action, compensated only partially by insulin hypersecretion. This suggests obesity, with respect to hypertension, as a primary factor in the deterioration of glucose tolerance. © Springer International Publishing Switzerland 2016.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/236267

Health monitoring in sport through wearable sensors: A novel approach based on heart-rate variability
Lecture Notes in Electrical Engineering
Autore/i: Maranesi, Elvira; Morettini, Micaela; Agostinelli, Angela; Giuliani, Corrado; DI NARDO, Francesco; Burattini, Laura
Editore: Springer Verlag
Classificazione: 2 Contributo in Volume
Abstract: Sudden cardiac death (SCD) is one of the leading cause of death during sport activities. Heart rate (HR) and HR variability (HRV) provide a measure of how the organism adapts to physical fatigue, and can be monitored by commercial wearable sensors. Still, HR and HRV, widely used to optimize a training session, were rarely used to evaluate the athlete’s health-status, even though widely known to provide indexes of risk for SCD. This work, developed in collaboration with Bio-Medical Engineering Development Srl, aims to provide a contribution to the problem of preventive identification of athletes at increased risk of SCD, by developing and testing a low-cost, large-scale procedure for HR and HRV monitoring from signals obtained using comfortable wearable sensors. To this aim a new protocol for the acquisition of the tachogram was proposed. It included recordings of the signals during resting, exercise and recovery phases, to allow evaluation of prevention as well as performance indexes. The procedure was tested on 10 sedentary subjects (SS) and 10 amateur athletes (AA). Compared to SS, AA showed a better health-status, quantified in a lower resting HR (63 bpm vs. 73 bpm; P < 0.005) and a higher resting HRV (29 ms vs. 23 ms; P < 0.05), and a better performance level, quantifies in a lower recovery time (130 ms vs. 174 ms; P < 0.05). Thus, the proposed procedure allows evaluation of both the health-status and the performance level of an athlete, and represents a valuable tool to contrast SCD in sport.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/240332

Estimation of first-phase insulin secretion in the Zucker Fatty Rat
IFMBE Proceedings
Autore/i: DI NARDO, Francesco; Morettini, Micaela; Cogo, C. E.; Faelli, E.; Fioretti, Sandro; Burattini, Laura; Ruggeri, P.
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The present study was designed to test the efficacy of the popular index AIRG(i.e. acute insulin response after glucose bolus) in the characterization of the first-phase insulin secretion in the Zucker Fatty Rat. The reliability of the AIRGwas evaluated by direct comparison with the first-phase β-cell responsiveness index (Φ1)provided by C-peptide minimal model. To this aim, AIRG and Φ1were simultaneously computed from IVGTT data, measured in six Zucker fatty rats (ZFR), 7-to-9week-old, and seven age-matched Zucker lean rats (ZLR). In the whole 13 rats population, the AIRG showed a significant linear correlation with Φ1(r = 0.89, P < 0.0001). Moreover, both Φ1(P < 0.05) and AIRG (p<0.001) showed a significant increase, in the ZFRs, compared to control group (ZLR). These findings suggest that the AIRG index is able to provide similar information of Φ1, in the evaluation of the alteration of the first-phase insulin secretion in Zucker Fatty Rats. Thus, the present study proposes the AIRG, as a suitable empiric index for a simple, reliable and low-cost quantification of the first-phase insulin secretion in Zucker Fatty Rats. © Springer International Publishing Switzerland 2016.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/236266

On the Heart-Rate Signal Provided by the Zephyr BioHarness 3.0
Proceeding of the 8th International workshop on Biosignal Interpretation
Autore/i: Nepi, D.; Agostinelli, Angela; Maranesi, Elvira; Sbrollini, Agnese; Morettini, Micaela; DI NARDO, Francesco; Fioretti, Sandro; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The BioHarness 3 system (BH3) by Zephyr is a wearable cardiac sensor specifically designed for training optimization of professional athletes. BH3 records the electrocardiogram (BH3_ECG) and the heart-rate signal (BH3_HRS). Specifically, BH3_HRS is neither the popular tachogram nor the direct not-uniformly sampled heart-rate sequence as function of time. Consequently, the aim of the present study is to gain more insights on BH3_HRS that, if found reliable, would allow a future evaluation of the possibility of a clinical use of the sensor for cardiac risk evaluation. Data were acquired from an amateur athlete (male, 25 years old) during a 5-min rest followed by a 10 min exercise. R-peak detection was performed on BH3_ECG, and the obtained heart-rate signal (HRS) was low-pass filtered using the following six filters: 3-, 4-, and 5-sample averages and 0.30 Hz, 0.35 Hz, and 0.40 Hz 6th order Butterworth low-pass filters. The filtered HRSs were then compared to BH3_HRS in terms of correlation coefficient (ρ), mean square error (MSE), resting heart-rate variability (HRV) and exercise maximum heart rate. Results indicate that the HRS closest to BH3_HRS was obtained with the 3-point average (ρ=0.9688-0.9991, MSE=0.45-0.47 mV2; comparable resting HRV and exercise maximum heart rate).
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/247675

Estimation of second-phase insulin secretion in the Zucker fatty rat
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Autore/i: Morettini, Micaela; DI NARDO, Francesco; Cogo, Carla E.; Faelli, Emanuela; Fioretti, Sandro; Burattini, Laura; Ruggeri, Piero
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The purpose of the present study was to test the efficacy of the empiric index SPIR (Second-phase Insulin Release) in the quantification of second-phase insulin secretion in the Zucker Fatty Rat. SPIR index is defined as the area under the curve of insulin between 8 and 90 min after an Intravenous Glucose Tolerance Test (IVGTT). The validation of such index was performed against the second-phase β-cell responsiveness index (Φ2) provided by C-peptide minimal model. To this aim, Φ2 and SPIR were simultaneously computed from IVGTT data, measured in six Zucker fatty rats (ZFR), 7-to-9week-old, and seven age-matched Zucker lean rats (ZLR). SPIR index showed a significant linear correlation with Φ2 (Pearson's correlation coefficient, r = 0.91, R-square = 0.82, P<0.001). Moreover, both Φ2 (P<0.001) and SPIR (P<0.001) showed a significant increase, in the ZFRs, compared to control group (ZLR). These findings suggest that the SPIR index is able to provide similar information of Φ2, in the evaluation of the second-phase insulin secretion and of its alteration in Zucker Fatty Rats. Thus, the study proposes the SPIR, as a suitable index for a simple, reliable and low-cost quantification of the second-phase insulin secretion in ZFR.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/245028

Validation of the Heart-Rate Signal Provided by the Zephyr BioHarness 3.0
Computing in Cardiology 2016
Autore/i: Nepi, Daniele; Sbrollini, Agnese; Agostinelli, Angela; Maranesi, Elvira; Morettini, Micaela; Di Nardo, Francesco; Fioretti, Sandro; Pierleoni, Paola; Pernini, Luca; Valenti, Simone; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The Zephyr BioHarness 3.0 (BH3) is a popular wearable system specifically designed for training optimization of professional athletes. BH3 provides the electrocardiogram (ECG BH3) and the heart-rate signal (HRSBH3). Aim of this study is to evaluate the reliability of HRSBH3 to assess its clinical applicability to the general population for cardiac-risk evaluations. Data were acquired from 10 healthy subjects (age: 34±17 years) during a 5-minutes rest. Since the tachogram represents the standard signal for studying the heart rate (HR) and its variability, ECG BH3 was elaborated in order to get the tachogram (HRSTG). HRSBH3 and HRSTG were compared in terms of mean HR (MHR, bpm), HR standard deviation (HRSD, bpm) and HRSD error (bpm). HRSBH3 and HRSTG provided comparable MHR (73.07±15.53 bpm vs 72.86±15.57 bpm, respectively) while HRSD by HRSBH3 was significantly lower than HRSD by HRS TG (4.51 ±2.29 bpm vs 5.63±2.99 bpm, respectively; P=0.0043). HRSD error was significantly greater than zero (0.20-3.00 bpm; P=0.0043); moreover, it was strongly correlated to HRSD by HRS TG (p=0.82, P=0.0036). Thus, HRS BH3 is appropriate only for sport applications based on MHR estimations, but not to clinical evaluations based on HRV measurements.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/246953

C-peptide-based assessment of insulin secretion in the Zucker fatty rat: A modelistic study
PLOS ONE
Autore/i: DI NARDO, Francesco; Cogo, Carla E.; Faelli, Emanuela; Morettini, Micaela; Burattini, Laura; Ruggeri, Piero
Classificazione: 1 Contributo su Rivista
Abstract: A C-peptide-based assessment of β-cell function was performed here in the Zucker fatty rat, a suitable animal model of human metabolic syndrome. To this aim, a 90-min intravenous glucose tolerance test (IVGTT) was performed in seven Zucker fatty rats (ZFR), 7-to-9week-old, and seven age-matched Zucker lean rats (ZLR). The minimal model of C-peptide (CPMM), originally introduced for humans, was adapted to Zucker rats and then applied to interpret IVGTT data. For a comprehensive evaluation of glucose tolerance in ZFR, CPMM was applied in combination with the minimal model of glucose kinetics (GKMM). Our results showed that the present CPMM-based interpretation of data is able to: 1) provide a suitable fit of C-Peptide data; 2) achieve a satisfactory estimation of parameters of interest 3) quantify both insulin secretion by estimating the time course of pre-hepatic secretion rate, SR(t), and total insulin secretion, TIS, and pancreatic sensitivity by means of three specific indexes of β-cell responsiveness to glucose stimulus (first-phase, φ1, second-phase, φ2, and steady-state, φsss, never assessed in Zucker rats before; 4) detect the significant enhancement of insulin secretion in the ZFR, in face of a severe insulin-resistant state, previously observed only using a purely experimental approach. Thus, the methodology presented here represents a reliable tool to assess β-cell function in the Zucker rat, and opens new possibilities for the quantification of further processes involved in glucose homeostasis such as the hepatic insulin degradation.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/228443

Preventing sudden cardiac death in sports: a novel monitoring service of the heart-rate variability trough wearable sensors
MBIDA - Proceedings of the International Workshop Mobile Networks for Biometric Data Analysis
Autore/i: Maranesi, Elvira; Morettini, Micaela; F., Palmieri; DI NARDO, Francesco; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/205745

MATLAB-implemented estimation procedure for model-based assessment of hepatic insulin degradation from standard intravenous glucose tolerance test data
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
Autore/i: DI NARDO, Francesco; Michele, Mengoni; Morettini, Micaela
Classificazione: 1 Contributo su Rivista
Abstract: Present study provides a novel MATLAB-based parameter estimation procedure for individual assessment of hepatic insulin degradation (HID) process from standard frequently-sampled intravenous glucose tolerance test (FSIGTT) data. Direct access to the source code, offered by MATLAB, enabled us to design an optimization procedure based on the alternating use of Gauss-Newton’s and Levenberg-Marquardt’s algorithms, which assures the full convergence of the process and the containment of computational time.Reliability was tested by direct comparison with the application, in eighteen non-diabetic subjects, of well-known kinetic analysis software package SAAM II, and by application on different data. Agreement between MATLAB and SAAM II was warranted by intraclass correlation coefficients ≥0.73; no significant differences between corresponding mean parameter estimates and prediction of HID rate; and consistent residual analysis. Moreover, MATLAB optimization procedure resulted in a significant 51% reduction of CV% for the worst-estimated parameter by SAAM II and in maintaining all model-parameter CV% <20%. In conclusion, our MATLAB-based procedure was suggested as a suitable tool for the individual assessment of HID process.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/110875

The onset of type 2 diabetes: Proposal for a multi-scale model
JMIR. JOURNAL OF MEDICAL INTERNET RESEARCH
Autore/i: Castiglione, F.; Tieri, P.; De Graaf, A.; Franceschi, C.; Lio, P.; Van Ommen, B.; Mazza, C.; Tuchel, A.; Bernaschi, M.; Samson, C.; Colombo, T.; Castellani, G. C.; Capri, M.; Garagnani, P.; Salvioli, S.; Nguyen, V. A.; Bobeldijk-Pastorova, I.; Krishnan, S.; Cappozzo, A.; Sacchetti, M.; Morettini, M.; Ernst, M.
Classificazione: 1 Contributo su Rivista
Abstract: Background: Type 2 diabetes mellitus (T2D) is a common age-related disease, and is a major health concern, particularly in developed countries where the population is aging, including Europe. The multi-scale immune system simulator for the onset of type 2 diabetes (MISSION-T2D) is a European Union-funded project that aims to develop and validate an integrated, multilevel, and patient-specific model, incorporating genetic, metabolic, and nutritional data for the simulation and prediction of metabolic and inflammatory processes in the onset and progression of T2D. The project will ultimately provide a tool for diagnosis and clinical decision making that can estimate the risk of developing T2D and predict its progression in response to possible therapies. Recent data showed that T2D and its complications, specifically in the heart, kidney, retina, and feet, should be considered a systemic disease that is sustained by a pervasive, metabolically-driven state of inflammation. Accordingly, there is an urgent need (1) to understand the complex mechanisms underpinning the onset of this disease, and (2) to identify early patient-specific diagnostic parameters and related inflammatory indicators. Objective: We aim to accomplish this mission by setting up a multi-scale model to study the systemic interactions of the biological mechanisms involved in response to a variety of nutritional and metabolic stimuli and stressors. Methods: Specifically, we will be studying the biological mechanisms of immunological/inflammatory processes, energy intake/expenditure ratio, and cell cycle rate. The overall architecture of the model will exploit an already established immune system simulator as well as several discrete and continuous mathematical methods for modeling of the processes critically involved in the onset and progression of T2D. We aim to validate the predictions of our models using actual biological and clinical data. Results: This study was initiated in March 2013 and is expected to be completed by February 2016. Conclusions: MISSION-T2D aims to pave the way for translating validated multilevel immune-metabolic models into the clinical setting of T2D. This approach will eventually generate predictive biomarkers for this disease from the integration of clinical data with metabolic, nutritional, immune/inflammatory, genetic, and gut microbiota profiles. Eventually, it should prove possible to translate these into cost-effective and mobile-based diagnostic tools.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/273188

Mathematical model of standard oral glucose tolerance test for characterization of insulin potentiation in health
Autore/i: Morettini, Micaela
Editore: Università Politecnica delle Marche
Classificazione: 8 Tesi di dottorato
Abstract: In questo lavoro di tesi vengono proposte due diverse formulazioni (INT_M1 e INT_M2) di un nuovo modello integrato per la descrizione delle risposte del sistema di regolazione glucosio-insulina alla somministrazione orale di glucosio (oral glucose tolerance test, OGTT). INT_M1 e INT_M2 si differenziano per la descrizione dell’assorbimento gastrointestinale adottata: un modello ad un compartimento ed una funzione empirica per il primo ed un modello a tre compartimenti non lineare per il secondo. L’implementazione del modello in ambiente Matlab, all’interno di una nuova procedura di stima parametrica a due passi, ha permesso l’ottimizzazione di parametri caratteristici dell’assorbimento gastro-intestinale e della cinetica del glucosio, dell’insulina e dell’incretina. Il comportamento del modello è stato testato mediante best-fit di dati medi, presi dalla letteratura, delle concentrazioni plasmatiche di glucosio, insulina, di GIP (glucose-dependent insulinotropic polipeptide) e GLP-1 (glucagon-like peptide 1) misurati in due gruppi di soggetti sani (HC-1 e HC-2) sottoposti ad un protocollo OGTT standard e, successivamente, ad un protocollo endovenoso caratterizzato dalla somministrazione di un eguale andamento temporale del glucosio (isoglycemic intravenous glucose, I-IVG, infusion). I due modelli sono stati confrontati per quanto riguarda la capacità di riprodurre il potenziamento dell’insulina indotto dall’incretina ovvero l’aumentata risposta insulinica che si osserva a seguito di un OGTT paragonata a quella dell’I-IVG. Nell’ipotesi di un’azione additiva del GIP e del GLP-1 sul potenziamento dell’insulina, i risultati hanno mostrato una sostanziale equivalenza dei due modelli nel riprodurre i dati. Inoltre, i parametri stimati sembrano essere buoni indicatori delle differenze osservate nei due gruppi di soggetti sani. Infine la procedura di stima messa a punto apre la strada a future applicazioni mirate all’individualizzazione dell’effetto incretina.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/241987

Identification of an integrated mathematical model of standard oral glucose tolerance test for characterization of insulin potentiation in health
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
Autore/i: Burattini, Roberto; Morettini, M.
Classificazione: 1 Contributo su Rivista
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/59113

Incretin-induced insulin potentiation characterized by an improvedmathematical model of oral glucose tolerance test
IFMBE Proceedings
Autore/i: Morettini, M.; Guercio, G.; Burattini, Roberto
Editore: Springer
Luogo di pubblicazione: Berlin
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/62346

Dynamics of insulin action in hypertension: assessment from minimal model interpretation of intravenous glucose tolerance test data
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
Autore/i: Burattini, Roberto; Morettini, Micaela; DI NARDO, Francesco; Boemi, M.
Classificazione: 1 Contributo su Rivista
Abstract: Based on glucose kinetics minimal model (GKMM) interpretation of frequently sampled intravenous glucose tolerance test (FSIGTT), the aim was to broaden the characterization of insulin-mediated glucose disposal in hypertension by aid of a dynamic insulin sensitivity index, S-{\text{I}} {\text{D}}, and the related efficiency, η = S-{\text{I}}{\text{D}} /S-{\text{I}}, of the metabolic system to convert the maximal individual response capacity, measured by S I, into an effective insulin control on glucose. The C-peptide minimal model (CPMM) was used to interpret the role of β-cell function. Plasma glucose, insulin, and C-peptide concentrations were measured, during a 5-h FSIGTT, in eighteen normoglycemic individuals: ten hypertensive patients (H-group) and eight normotensive subjects (N-group) with no metabolic syndrome. Compared to our N-group, the H-group showed a significant (P < 0.05) reduction of both S I (56%) and S-{\text{I}}{\text{D}} (50%), no significant change of η, a significant increase of both the first-phase β-cell responsiveness to glucose (105%) and total insulin secretion (55%), and no significant change in disposition indexes, defined as the product of insulin sensitivity (either S I and S-{\text{I}}{\text{D}} ) and β-cell responsiveness. These findings suggest that, in spite of no change of efficiency, insulin resistance in normoglycemic hypertensive patients is primarily compensated by an increase in first-phase insulin secretion to preserve glucose tolerance to intravenous glucose load.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/56748