Screening the health status of people working in a university.

BACKGROUND: We aimed to evaluate the physical and mental well being of people working in our academic institution. METHODS: This online survey targeted professors ( n  = 108), researchers ( n  = 78), technical and administrative staff ( n  = 279) working in the Scuola Superiore Sant'Anna (Pisa, Italy). Twenty-four multiple-choice questions explored the physical and mental health status, the main cardiovascular risk factors and levels of physical activity, the risk of cancer, and eating and drinking habits. RESULTS: Over 1 week, 112 participants out of 465 (24%) completed the survey [69% women, median age 43 years (interquartile range 33-53)]. The physical and mental health were judged as 'poor' by 5% and 13%. Many individuals had at least one cardiovascular risk factor (diabetes, 4%; hypertension, 10%; family history of coronary artery disease before 40 years, 21%; hypercholesterolemia, 24%; current or former smoking habit, 39%), and 6% had all of them. Many participants were rather sedentary: for example, 44% never or hardly ever walked at a quick pace for ≥20 min. As for eating and drinking habits, 36% ate sweets five or six times a week or every day, 15% drank beer and/or wine at least five or six times a week, and 5% drank spirits three or four times a week. CONCLUSIONS: A small but not negligeable proportion of responders complained of 'poor' health, and 65% had at least one cardiovascular risk factor. The global levels of physical activity and eating and drinking habits were globally suboptimal. Educational and screening activities to improve the wellbeing of people working in academia are advisable.

Gender Differences in Knowledge and Perception of Cardiovascular Disease among Italian Thalassemia Major Patients.

We evaluated gender differences in knowledge and perception of cardiovascular disease (CVD) among Italian thalassemia major (TM) patients. An anonymous questionnaire was completed by 139 ß-TM patients (87 (62.7%) females, 40.90 ± 8.03 years). Compared to females, males showed a significantly higher frequency of CVDs, and they less frequently selected tumors in general as the greatest health problem for people of the same age and gender (48.1% vs. 66.7%; p = 0.031) and as the greatest danger to their future health (26.9% vs. 43.7%; p = 0.048). CVDs were designated as the greatest danger to their future health by a significantly higher percentage of males than females (53.8% vs. 36.8%; p = 0.048). Both males and females showed a good knowledge of cardiovascular risk factors and preventive measures for CVDs. No gender differences were detected in the subjective well-being and the perceived cardiovascular risk. The perceived risk was not influenced by age, presence of cardiovascular risk factors, or disease, but no patient with a low perceived CVD risk had myocardial iron overload. Our findings highlight the need to implement future educational programs aimed at increasing the awareness of CVD as the greatest health issue, especially among the female TM population, and at informing TM patients of the different actors, besides iron, that play a role in the development of cardiovascular complications.

A New Web Score to Predict Health Status in Paediatric Patients with Chronic Diseases: Design and Development of the PENSAMI Study.

Paediatric chronic diseases (CD) are characterised by their ongoing duration and the fact that they are often managed throughout the lifespan, with the need to adjust lifestyle and expectations with the limitations coming from the CD. The aim of the PENSAMI study is to not only cure the disease, but to also care for the person from a clinical and psychosocial perspective. Data will be collected from 150 paediatric patients affected by heart disease, diabetes, and asthma admitted during in-hospital stay or outpatient visits, and from 200 healthy control subjects. The protocol will consist of two phases. The first one will aim at elaborating the predictive model by detecting (clinical, anthropometric at birth, environmental, lifestyle, social context, emotional state, and mental abilities) in order to develop a model predictive of the events considered: (1) re-hospitalisation; (2) severity and progression of the disease; (3) adherence to therapy; (4) HRQoL; (5) obesity and metabolic syndrome; (6) illness-stress related; (7) school drop-out; (8) school performance. The second one will address validating the previous predictive model. This model will aim to: (1) understand, prevent, and halt the progression of childhood CD; (2) develop new and improved diagnostic tools; (3) pave the way for innovative treatments and additional therapies to traditional clinical practice; and (4) create truly personalised therapeutic and preventive strategies in various sectors, such as cardiology, diabetes, and respiratory diseases.

Relevance of eHealth standards for big data interoperability in radiology and beyond.

The aim of this paper is to report on the implementation of radiology and related information technology standards to feed big data repositories and so to be able to create a solid substrate on which to operate with analysis software. Digital Imaging and Communications in Medicine (DICOM) and Health Level 7 (HL7) are the major standards for radiology and medical information technology. They define formats and protocols to transmit medical images, signals, and patient data inside and outside hospital facilities. These standards can be implemented but big data expectations are stimulating a new approach, simplifying data collection and interoperability, seeking reduction of time to full implementation inside health organizations. Virtual Medical Record, DICOM Structured Reporting and HL7 Fast Healthcare Interoperability Resources (FHIR) are changing the way medical data are shared among organization and they will be the keys to big data interoperability. Until we do not find simple and comprehensive methods to store and disseminate detailed information on the patient's health we will not be able to get optimum results from the analysis of those data.

Multicentre multi-device hybrid imaging study of coronary artery disease: results from the EValuation of INtegrated Cardiac Imaging for the Detection and Characterization of Ischaemic Heart Disease (EVINCI) hybrid imaging population.

AIMS: Hybrid imaging provides a non-invasive assessment of coronary anatomy and myocardial perfusion. We sought to evaluate the added clinical value of hybrid imaging in a multi-centre multi-vendor setting. METHODS AND RESULTS: Fourteen centres enrolled 252 patients with stable angina and intermediate (20-90%) pre-test likelihood of coronary artery disease (CAD) who underwent myocardial perfusion scintigraphy (MPS), CT coronary angiography (CTCA), and quantitative coronary angiography (QCA) with fractional flow reserve (FFR). Hybrid MPS/CTCA images were obtained by 3D image fusion. Blinded core-lab analyses were performed for CTCA, MPS, QCA and hybrid datasets. Hemodynamically significant CAD was ruled-in non-invasively in the presence of a matched finding (myocardial perfusion defect co-localized with stenosed coronary artery) and ruled-out with normal findings (both CTCA and MPS normal). Overall prevalence of significant CAD on QCA (>70% stenosis or 30-70% with FFR≤0.80) was 37%. Of 1004 pathological myocardial segments on MPS, 246 (25%) were reclassified from their standard coronary distribution to another territory by hybrid imaging. In this respect, in 45/252 (18%) patients, hybrid imaging reassigned an entire perfusion defect to another coronary territory, changing the final diagnosis in 42% of the cases. Hybrid imaging allowed non-invasive CAD rule-out in 41%, and rule-in in 24% of patients, with a negative and positive predictive value of 88% and 87%, respectively. CONCLUSION: In patients at intermediate risk of CAD, hybrid imaging allows non-invasive co-localization of myocardial perfusion defects and subtending coronary arteries, impacting clinical decision-making in almost one every five subjects.

A modular informatics platform for effective support of collaborative and multicenter studies in cardiology.

Collaborative and multicenter studies permit a large number of patients to be enrolled within a reasonable time and providing the opportunity to collect different data. Informatics platforms play an important role in management, storage, and exchange of data between the participants involved in the study. In this article, we describe a modular informatics platform designed and developed to support collaborative and multicenter studies in cardiology. In each developed module, data management is implemented following local defined protocols. The modular characteristic of the developed platform allows independent transfer of different kinds of data, such as biological samples, imaging raw data, and patients' digital information. Moreover, it offers safe central storage of the data collected during the study. The developed platform was successfully tested during a European collaborative and multicenter study, focused on evaluating multimodal non-invasive imaging to diagnose and characterize ischemic heart disease.

Detection of significant coronary artery disease by noninvasive anatomical and functional imaging.

BACKGROUND: The choice of imaging techniques in patients with suspected coronary artery disease (CAD) varies between countries, regions, and hospitals. This prospective, multicenter, comparative effectiveness study was designed to assess the relative accuracy of commonly used imaging techniques for identifying patients with significant CAD. METHODS AND RESULTS: A total of 475 patients with stable chest pain and intermediate likelihood of CAD underwent coronary computed tomographic angiography and stress myocardial perfusion imaging by single photon emission computed tomography or positron emission tomography, and ventricular wall motion imaging by stress echocardiography or cardiac magnetic resonance. If ≥1 test was abnormal, patients underwent invasive coronary angiography. Significant CAD was defined by invasive coronary angiography as >50% stenosis of the left main stem, >70% stenosis in a major coronary vessel, or 30% to 70% stenosis with fractional flow reserve ≤0.8. Significant CAD was present in 29% of patients. In a patient-based analysis, coronary computed tomographic angiography had the highest diagnostic accuracy, the area under the receiver operating characteristics curve being 0.91 (95% confidence interval, 0.88-0.94), sensitivity being 91%, and specificity being 92%. Myocardial perfusion imaging had good diagnostic accuracy (area under the curve, 0.74; confidence interval, 0.69-0.78), sensitivity 74%, and specificity 73%. Wall motion imaging had similar accuracy (area under the curve, 0.70; confidence interval, 0.65-0.75) but lower sensitivity (49%, P<0.001) and higher specificity (92%, P<0.001). The diagnostic accuracy of myocardial perfusion imaging and wall motion imaging were lower than that of coronary computed tomographic angiography (P<0.001). CONCLUSIONS: In a multicenter European population of patients with stable chest pain and low prevalence of CAD, coronary computed tomographic angiography is more accurate than noninvasive functional testing for detecting significant CAD defined invasively. CLINICAL TRIAL REGISTRATION URL: http://www.clinicaltrials.gov. Unique identifier: NCT00979199.

Hybrid image visualization tool for 3D integration of CT coronary anatomy and quantitative myocardial perfusion PET.

PURPOSE: Multimodal cardiac imaging by CTA and quantitative PET enables acquisition of patient-specific coronary anatomy and absolute myocardial perfusion at rest and during stress. In the clinical setting, integration of this information is performed visually or using coronary arteries distribution models. We developed a new tool for CTA and quantitative PET integrated 3D visualization, exploiting XML and DICOM clinical standards. METHODS: The hybrid image tool (HIT) developed in the present study included four main modules: (1) volumetric registration for spatial matching of CTA and PET data sets, (2) an interface to PET quantitative analysis software, (3) a derived DICOM generator able to build DICOM data set from quantitative polar maps, and (4) a 3D visualization tool of integrated anatomical and quantitative flow information. The four modules incorporated in the HIT tool communicate by defined standard XML files: XML-transformation and XML MIST standards. RESULTS: The HIT tool implements a 3D representation of CTA showing real coronary anatomy fused to PET-derived quantitative myocardial blood flow distribution. The technique was validated on 16 data sets from EVINCI study population. The validation of the method confirmed the high matching between "original" and derived data sets as well as the accuracy of the registration procedure. CONCLUSIONS: Three-dimensional integration of patient- specific coronary artery anatomy provided by CTA and quantitative myocardial blood flow obtained from PET imaging can improve cardiac disease assessment. The HIT tool introduced in this paper may represent a significant advancement in the clinical use of this multimodal approach.