Relationship Between Blood Pressure and Heart Rate Circadian Rhythms in Normotensive and Hypertensive Subjects

This paper focuses on the relationship between blood pressure (BP) and heart rate (HR) during 24 hours in 423 normotensive (NO) and 205 hypertensive (HE) subjects. Although considerable knowledge has been gained about BP and HR signals, their relationship over 24 hours has never been completely described. By using a Holter Blood Pressure Monitor, it was possible to record BP and HR for 24 hours. Systolic, Diastolic and Mean BP in both NO and HE subjects showed four different time intervals presenting well-defined trends The results demonstrated that changes in HR present closely parallel changes in BP with a marked reduction of both signals during nocturnal rest. On the contrary, in the period between 15:30 and 19:30, HR and BP showed an inverse relationship with decreasing heart rate and increasing blood pressure

Multi-criteria decision analysis for the assessment of non-clinical hospital services: Methodology and case study

Non-clinical hospital services to support clinical activities, such as the sterilization service and clinical engineering, are an important technology asset in healthcare, and require constant improvement aimed to reduce economic burden and increase quality. The selection of the most effective healthcare service to adopt in a healthcare facility is a multi-criteria decision problem that classical Health Technology Assessment, being mostly focused on medicines, vaccines and medical devices, cannot easily address. Here we present a methodology based on Multi-Criteria Decision Analysis allowing a full assessment of non-clinical hospital services and supporting the selection of the most suitable solution in a certain environment. The methodology involves two different panels of experts: the first one includes international professionals and is aimed at selecting the assessment criteria that are relevant to the target service; the second one is a local panel whose members know the needs and peculiarities of the specific healthcare facility. This approach allows the final decision makers to take into account changes and constraints of their environment, but examining criteria that are internationally recognized as of interest. The proposed methodology, tested in a real context of an Italian Local Health Authority, is versatile and can be applied in any context, even out of the healthcare domain, especially if data in the literature are not sufficient to allow comparisons with similar services in different settings. Abbreviations: HTA, Health Technology Assessment; NCHS, Non-Clinical Hospital Services; CSSD, Central Sterile Services Department; MCDA, Multi-Criteria Decision Analysis; ASM, Local Healt

Influence of hypertension and other risk factors on the onset of sublingual varices

Background: Sublingual varices (SV) are dilatations of tortuous veins that increased with age. Previous studies showed that this pathology could be correlated to some risk factors such as hypertension, age, gender and diabetes mellitus. In this study we evaluated, on a large number of subjects, the relationship between SV and different grades of hypertension as well as some risk factors extending the analysis to new risk factors such as dyslipidemia, obesity and antihypertensive therapy, modelling a possible dependence of SV on all these factors.Methods: In the study 1008 subjects, 284 with and 724 without SV, were examined. The blood pressure was measured in office condition and, to exclude subjects with white coat syndrome or masked hypertension, also using a 24 h Holter pressure monitor. Hypertensive subjects were divided in resistant, drugs controlled (compensated) and patients with prior unknown hypertension (new diagnosed) groups. The presence or absence of SV as well as of the risk factors was assessed clinically. We tested the influence of age on the presence of SV by using the chi-square test and the relation between each risk factor and SV by the Cochran-Mantel-Haenszel test. Finally, we carried out a multivariate regression tree analysis in order to predict the presence of SV.Results: We confirmed the influence of age on SV and found a significant relationship between SV and both the compensated and resistant hypertension grades. We highlighted a relationship between SV and dyslipidemia in subjects with new diagnosed hypertension, and between SV and smoking in subjects with compensated hypertension grade. The regression tree showed a classification accuracy of about 75% using as variables hypertension grades, age and antihypertensive treatment.Conclusions: We confirmed the SV dependence on age, resistant hypertension and smoking, highlighting a new association with dyslipidemia in new diagnosed hypertensive subjects and new relations depending on the hypertension grades. Thus, the SV inspection could be used to suggest a lipidologist as well as a hypertension specialist visit for a pharmacological and pressure check particularly in subjects presenting SV and dyslipidemia. However, further parameters are to be considered to improve the sensitivity of the prognostic tree model

Eye Movement Impairment Recovery in a Gaucher Patient Treated with Miglustat

In Gaucher Disease (GD) the enzyme (imiglucerase) replacement therapy (ERT) is not able to stop the progression of the neurological involvement, while the substrate reduction therapy (SRT), performed by N-Butyldeoxynojirimycin (miglustat), is an alternative that should be evaluated. Two sisters, presenting the same genotype (R353G/R353G), were diagnosed as suffering from GD; one of them later developed neurological alterations identified by quantitative saccadic eye movements analysis. The aim of the study was to quantitatively measure the miglustat effects in this GD neurological patient. Eye movement analysis during subsequent controls was performed by estimating the characteristic parameters of saccadic main sequence. The study demonstrates that the SRT alone can be effective in GD3. Moreover, it confirms that quantitative eye movement analysis is able to precociously identify also slight neurological alterations, permitting more accurate GD classification

Memorization test and resting state EEG components in mild and subjective cognitive impairment

BACKGROUND: Mild (MCI) and Subjective Cognitive Impairment (SCI) are conditions at risk of developing Alzheimer's disease (AD). Differential between normal aging at early stages can be really challenging; available biomarkers need to be combined and can be quite invasive and expensive. OBJECTIVE: The aim of this pilot study is to examine possible EEG alterations in MCI and SCI compared to controls, analyzing if a cognitive task could highlight early AD hallmarks. METHOD: We recruited 11 MCI, 8 SCI and 7 healthy subjects as controls (CS), all matched for age and education. Neuropsychological assessment and EEG recording, at resting state and during a mental memory task, were performed. Classical spectral measures and nonlinear parameters were used to characterize EEGs. RESULTS: During cognitive task, \u3b1-band power reduction was found predominantly in frontal regions in SCI and CS, diffused to all regions in MCI; moreover, decreased EEG complexity was found in SCI compared to controls. The \u3b1 -band power attenuation restricted to frontal regions in SCI during a free recall task (involving frontal areas), suggests that MCI patients compensate for encoding deficit by activating different brain networks to perform the same task. Furthermore, EEG complexity reduction - that has been found already in SCI - could be a possible early hallmark of AD. CONCLUSION: This study draws attention on the importance of nonlinear approach in EEG analysis and the potential role of cognitive task in highlighting EEG alterations at very early stages of cognitive impairment; EEG could therefore have a practical impact on dementia diagnosis

Promoting Health for Chronic Conditions: a Novel Approach that integrates Clinical and Personal Decision Support

Direct and indirect economic costs related to chronic diseases are increasing in Europe due to the aging of population. One of the most challenging goals is to improve the quality of life of patients affected by chronic conditions, and enhance their self-management. In this paper, we propose a novel architecture of a scalable solution, based on mobile tools, aimed to keep patients with chronic diseases away from acute episodes, to improve their quality of life and, consequently, to reduce their economic impact. Our solution aims to provide patients with a personalized tool for improving self-management, and it supports both patients and clinicians in decision-making through the implementation of two different Decision Support Systems. Moreover, the proposed architecture takes into account the interoperability and, particularly, the compliance with data transfer protocols (e.g., BT4/LE, ANT+, ISO/IEEE 11073) to ensure integration with existing devices, and with the semantic web approaches and standards related to the content and structure of the information (e.g., HL7, ICD-10 and openEHR) to ensure correct sharing of information with hospital information systems, and classification of patient behaviors (Coelition). The solution will be implemented and validated in future study

Detection of subjects with ischemic heart disease by using machine learning technique based on heart rate total variability parameters

OBJECTIVE: Ischemic heart disease (IHD), in its chronic stable form, is a subtle pathology due to its silent behavior before developing in unstable angina, myocardial infarction or sudden cardiac death. The clinical assessment is based on typical symptoms and finally confirmed, invasively, by coronary angiography. Recently, heart rate variability (HRV) analysis as well as some machine learning algorithms like Artificial Neural Networks (ANNs) were used to identify cardiovascular arrhythmias and, only in few cases, to classify IHD segments in a limited number of subjects. The goal of this study was the identification of the ANN structure and the HRV parameters producing the best performance to identify IHD patients in a non-invasive way, validating the results on a large sample of subjects. Moreover, we examined the influence of a clinical non-invasive parameter, the left ventricular ejection fraction (LVEF), on the classification performance.APPROACH: To this aim, we extracted several linear and non-linear parameters from 24h RR signal, considering both normal and ectopic beats (Heart Rate Total Variability), of 251 normal and 245 IHD subjects, matched by age and gender. ANNs using several different combinations of these parameters together with age and gender were tested. For each ANN, we varied the number of hidden neurons from 2 to 7 and simulated 100 times changing randomly training and test dataset.MAIN RESULTS: The HRTV parameters showed significant greater variability in IHD than in normal subjects. The ANN applied to meanRR, LF, LF/HF, Beta exponent, SD2 together with age and gender reached a maximum accuracy of 71.8% and, by adding as input LVEF, an accuracy of 79.8%.SIGNIFICANCE: The study provides a deep insight into how a combination of some HRTV parameters and LVEF could be exploited to reliably detect the presence of subjects affected by IHD

Ocular-following responses in school-age children

: Ocular following eye movements have provided insights into how the visual system of humans and monkeys processes motion. Recently, it has been shown that they also reliably reveal stereoanomalies, and, thus, might have clinical applications. Their translation from research to clinical setting has however been hindered by their small size, which makes them difficult to record, and by a lack of data about their properties in sizable populations. Notably, they have so far only been recorded in adults. We recorded ocular following responses (OFRs)-defined as the change in eye position in the 80-160 ms time window following the motion onset of a large textured stimulus-in 14 school-age children (6 to 13 years old, 9 males and 5 females), under recording conditions that closely mimic a clinical setting. The OFRs were acquired non-invasively by a custom developed high-resolution video-oculography system, described in this study. With the developed system we were able to non-invasively detect OFRs in all children in short recording sessions. Across subjects, we observed a large variability in the magnitude of the movements (by a factor of 4); OFR magnitude was however not correlated with age. A power analysis indicates that even considerably smaller movements could be detected. We conclude that the ocular following system is well developed by age six, and OFRs can be recorded non-invasively in young children in a clinical setting

Toward a diagnostic CART model for Ischemic heart disease and idiopathic dilated cardiomyopathy based on heart rate total variability

Diagnosis of etiology in early-stage ischemic heart disease (IHD) and dilated cardiomyopathy (DCM) patients may be challenging. We aimed at investigating, by means of classification and regression tree (CART) modeling, the predictive power of heart rate variability (HRV) features together with clinical parameters to support the diagnosis in the early stage of IHD and DCM. The study included 263 IHD and 181 DCM patients, as well as 689 healthy subjects. A 24 h Holter monitoring was used and linear and non-linear HRV parameters were extracted considering both normal and ectopic beats (heart rate total variability signal). We used a CART algorithm to produce classification models based on HRV together with relevant clinical (age, sex, and left ventricular ejection fraction, LVEF) features. Among HRV parameters, MeanRR, SDNN, pNN50, LF, LF/HF, LFn, FD, Beta exp were selected by the CART algorithm and included in the produced models. The model based on pNN50, FD, sex, age, and LVEF features presented the highest accuracy (73.3%). The proposed approach based on HRV parameters, age, sex, and LVEF features highlighted the possibility to produce clinically interpretable models capable to differentiate IHD, DCM, and healthy subjects with accuracy which is clinically relevant in first steps of the IHD and DCM diagnostic process

Enhanced and Flexible Software Tools for X-ray Computed Tomography at the Italian Synchrotron Radiation Facility Elettra

X-ray computed tomography (CT) experiments performed at synchrotron radiation facilities require adequate computing and storage resources due to the large amount of acquired and reconstructed data produced. To satisfy the heterogeneous needs of beamline users, flexible solutions are also required. Moreover, the growing demand of quantitative image analysis impose an easy integration between the CT reconstruction process and the subsequent feature extraction step. This paper presents some of the software solutions adopted by the SYRMEP beamline of the Italian synchrotron radiation facility Elettra. By using the enhanced version of the reconstruction software here presented as well as data reduction and data analysis tools, beamline users can easily implement an integrated and comprehensive approach to the digital image processing and image analysis required by a tomography-oriented scientific workflow