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Screening high school students in Italy for sudden cardiac death prevention by using a telecardiology device: a retrospective observational study

Published online by Cambridge University Press:  04 March 2016

Claudio De Lazzari*
Affiliation:
CNR, Institute of Clinical Physiology, U.O.S. of Rome, Via S. Martino della Battaglia, Rome, Italy National Institute for Cardiovascular Research, Via Irnerio, Bologna, Rome, Italy
Igino Genuini
Affiliation:
Department of Cardiovascular, Respiratory, Nephrological, Anaesthesiological and Geriatric Sciences, “Sapienza” University, Viale del Policlinico, Rome, Italy National Institute for Cardiovascular Research, Via Irnerio, Bologna, Rome, Italy
Maria C. Gatto
Affiliation:
Department of Cardiovascular, Respiratory, Nephrological, Anaesthesiological and Geriatric Sciences, “Sapienza” University, Viale del Policlinico, Rome, Italy
Alessandra Cinque
Affiliation:
Department of Cardiovascular, Respiratory, Nephrological, Anaesthesiological and Geriatric Sciences, “Sapienza” University, Viale del Policlinico, Rome, Italy
Massimo Mancone
Affiliation:
Department of Cardiovascular, Respiratory, Nephrological, Anaesthesiological and Geriatric Sciences, “Sapienza” University, Viale del Policlinico, Rome, Italy
Alessandra D’Ambrosi
Affiliation:
Department of Cardiovascular, Respiratory, Nephrological, Anaesthesiological and Geriatric Sciences, “Sapienza” University, Viale del Policlinico, Rome, Italy National Institute for Cardiovascular Research, Via Irnerio, Bologna, Rome, Italy
Elisa Silvetti
Affiliation:
Department of Cardiovascular, Respiratory, Nephrological, Anaesthesiological and Geriatric Sciences, “Sapienza” University, Viale del Policlinico, Rome, Italy National Institute for Cardiovascular Research, Via Irnerio, Bologna, Rome, Italy
Antonio Fusto
Affiliation:
Department of Cardiovascular, Respiratory, Nephrological, Anaesthesiological and Geriatric Sciences, “Sapienza” University, Viale del Policlinico, Rome, Italy
Domenico M. Pisanelli
Affiliation:
National Institute for Cardiovascular Research, Via Irnerio, Bologna, Rome, Italy CNR, Institute of Cognitive Science and Technologies, Via Nomentana, Rome, Italy
Francesco Fedele
Affiliation:
Department of Cardiovascular, Respiratory, Nephrological, Anaesthesiological and Geriatric Sciences, “Sapienza” University, Viale del Policlinico, Rome, Italy National Institute for Cardiovascular Research, Via Irnerio, Bologna, Rome, Italy
*
Correspondence to: C. De Lazzari, National Research Council, Institute of Clinical Physiology, U.O.S. of Rome, Via S.M. della Battaglia, 44 00185 Rome, Italy. Tel: +39 064 993 6222; Fax: +39 064 993 2688; E-mail: claudio.delazzari@ifc.cnr.it
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Abstract

Background

In 2010, an Italian project was launched aimed at using a telecardiology device in order to perform early diagnosis of young students at risk of sudden cardiac death.

Methods

Our retrospective observational study was conducted on a population of 13,016 students, aged between 16 and 19 years, in different Italian regions. It consisted of analysis of data recorded during a telecardiology pilot study. The recorded data were electrocardiograms and data concerning lifestyle habits and family history of cardiovascular diseases. In total, 14 alterations in the electrocardiogram signal have been considered in this study. Some of these alterations are as follows: ventricular ectopic beats, atrioventricular block, Brugada-like electrocardiogram pattern, left anterior/posterior fascicular block, left/right ventricular hypertrophy, long/short QT interval, left atrial enlargement, right atrial enlargement, short PQ interval, and ventricular pre-excitation Wolff–Parkinson–White syndrome. On the basis of the collected data, we implemented this retrospective observational study.

Results

The analysed data showed that 13.60% of students had a family history for cardiovascular diseases, 22.43% reported smoking habits, 26.23% reported alcohol consumption, and 7.24% reported abuse of drugs. A total of 24% of students had at least one of the 14 electrocardiogram pathological alterations considered in our study and 32% had electrocardiogram values within the normal range.

Conclusions

This retrospective observational study analysed data registered during our telecardiology activity. This activity permitted to maximise data collection and minimise the costs for collecting such data. This activity of screening is being continued and in the next few years it will allow us to have a greater mass of data.

Information

Type
Original Articles
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© Cambridge University Press 2016
Figure 0

Table 1 Results obtained analysing data collected in the questionnaire.

Figure 1

Figure 1 Percentage of students having an electrocardiogram with at least one of the 14 alterations considered in our study, having electrocardiogram values within the normal range and in the borderline range. The percentages are calculated for 13,016 students in Italy (left upper window). The students from the Central (right upper window), Northern (left lower window), and Southern regions (right lower window) of Italy are about 1/3 of the entire examined population.

Figure 2

Table 2 Distribution between male and female students having at least one of the electrocardiogram pathological alterations considered in this study.

Figure 3

Table 3 Students presenting the 14 electrocardiogram pathological alterations considered in the retrospective study.

Figure 4

Table 4 Correlations between altered electrocardiogram and one or more risk factors.

Figure 5

Figure 2 Correlation between students affected by altered electrocardiograms and high body mass index (BMI>25). The correlation was studied only on students having electrocardiogram signal alterations. Percentages for males and females are calculated for each geographical area. ECG=electrocardiogram.

Figure 6

Table 5 Percentage of students having electrocardiogram signal alterations correlated with each of the risk factors.