A New Relational Database Including Clinical Data and Myocardial Perfusion Imaging Findings in Coronary Artery Disease.


Journal

Current medical imaging reviews
Titre abrégé: Curr Med Imaging Rev
Pays: United Arab Emirates
ID NLM: 101272516

Informations de publication

Date de publication:
2019
Historique:
received: 20 12 2017
revised: 28 06 2018
accepted: 12 07 2018
entrez: 4 2 2020
pubmed: 6 2 2020
medline: 23 10 2020
Statut: ppublish

Résumé

The aim of this study was to test a relational database including clinical data and imaging findings in a large cohort of subjects with suspected or known Coronary Artery Disease (CAD) undergoing stress single-photon emission computed tomography (SPECT) myocardial perfusion imaging. We developed a relational database including clinical and imaging data of 7995 subjects with suspected or known CAD. The software system was implemented by PostgreSQL 9.2, an open source object-relational database, and managed from remote by pgAdmin III. Data were arranged according to a logic of aggregation and stored in a schema with twelve tables. Statistical software was connected to the database directly downloading data from server to local personal computer. There was no problem or anomaly for database implementation and user connections to the database. The epidemiological analysis performed on data stored in the database demonstrated abnormal SPECT findings in 46% of male subjects and 19% of female subjects. Imaging findings suggest that the use of SPECT imaging in our laboratory is appropriate. The development of a relational database provides a free software tool for the storage and management of data in line with the current standard.

Sections du résumé

BACKGROUND
The aim of this study was to test a relational database including clinical data and imaging findings in a large cohort of subjects with suspected or known Coronary Artery Disease (CAD) undergoing stress single-photon emission computed tomography (SPECT) myocardial perfusion imaging.
METHODS
We developed a relational database including clinical and imaging data of 7995 subjects with suspected or known CAD. The software system was implemented by PostgreSQL 9.2, an open source object-relational database, and managed from remote by pgAdmin III. Data were arranged according to a logic of aggregation and stored in a schema with twelve tables. Statistical software was connected to the database directly downloading data from server to local personal computer.
RESULTS
There was no problem or anomaly for database implementation and user connections to the database. The epidemiological analysis performed on data stored in the database demonstrated abnormal SPECT findings in 46% of male subjects and 19% of female subjects. Imaging findings suggest that the use of SPECT imaging in our laboratory is appropriate.
CONCLUSION
The development of a relational database provides a free software tool for the storage and management of data in line with the current standard.

Identifiants

pubmed: 32008514
pii: CMIR-EPUB-92215
doi: 10.2174/1573405614666180807110829
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

661-671

Informations de copyright

Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Auteurs

Rosario Megna (R)

Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy.

Mario Petretta (M)

Department of Translational Medical Sciences, University of Naples Federico II, Naples, Italy.

Bruno Alfano (B)

Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy.

Valeria Cantoni (V)

Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.

Roberta Green (R)

Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.

Stefania Daniele (S)

Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy.

Wanda Acampa (W)

Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.

Carmela Nappi (C)

Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.

Valeria Gaudieri (V)

Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy.

Roberta Assante (R)

Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.

Emilia Zampella (E)

Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.

Emanuela Mazziotti (E)

Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.

Teresa Mannarino (T)

Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.

Pietro Buongiorno (P)

Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.

Alberto Cuocolo (A)

Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.

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Classifications MeSH