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Imaging Quality Control, Methodology Harmonization and Clinical Data Management in Stress Echo 2030

Stress echo (SE) 2030 study is an international, prospective, multicenter cohort study that will include >10,000 patients from ≥20 centers from ≥10 countries. It represents the logical and chronological continuation of the SE 2020 study, which developed, validated, and disseminated the “ABCDE pro...

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Autores principales: Bartolacelli, Ylenia, Barbieri, Andrea, Antonini-Canterin, Francesco, Pepi, Mauro, Monte, Ines Paola, Trocino, Giuseppe, Barchitta, Agata, Cresti, Alberto, Miceli, Sofia, Petrella, Licia, Benedetto, Frank, Zito, Concetta, Benfari, Giovanni, Bursi, Francesca, Malagoli, Alessandro, Mantovani, Francesca, Ciampi, Quirino, Zagatina, Angela, Palinkas, Eszter Dalma, Palinkas, Attila, Toth, Szilvia Rostasne, Wierzbowska-Drabik, Karina, Djordievic-Dikic, Ana, Pellikka, Patricia A., Picano, Eugenio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8305320/
https://www.ncbi.nlm.nih.gov/pubmed/34300186
http://dx.doi.org/10.3390/jcm10143020
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author Bartolacelli, Ylenia
Barbieri, Andrea
Antonini-Canterin, Francesco
Pepi, Mauro
Monte, Ines Paola
Trocino, Giuseppe
Barchitta, Agata
Cresti, Alberto
Miceli, Sofia
Petrella, Licia
Benedetto, Frank
Zito, Concetta
Benfari, Giovanni
Bursi, Francesca
Malagoli, Alessandro
Mantovani, Francesca
Ciampi, Quirino
Zagatina, Angela
Palinkas, Eszter Dalma
Palinkas, Attila
Toth, Szilvia Rostasne
Wierzbowska-Drabik, Karina
Djordievic-Dikic, Ana
Pellikka, Patricia A.
Picano, Eugenio
author_facet Bartolacelli, Ylenia
Barbieri, Andrea
Antonini-Canterin, Francesco
Pepi, Mauro
Monte, Ines Paola
Trocino, Giuseppe
Barchitta, Agata
Cresti, Alberto
Miceli, Sofia
Petrella, Licia
Benedetto, Frank
Zito, Concetta
Benfari, Giovanni
Bursi, Francesca
Malagoli, Alessandro
Mantovani, Francesca
Ciampi, Quirino
Zagatina, Angela
Palinkas, Eszter Dalma
Palinkas, Attila
Toth, Szilvia Rostasne
Wierzbowska-Drabik, Karina
Djordievic-Dikic, Ana
Pellikka, Patricia A.
Picano, Eugenio
author_sort Bartolacelli, Ylenia
collection PubMed
description Stress echo (SE) 2030 study is an international, prospective, multicenter cohort study that will include >10,000 patients from ≥20 centers from ≥10 countries. It represents the logical and chronological continuation of the SE 2020 study, which developed, validated, and disseminated the “ABCDE protocol” of SE, more suitable than conventional SE to describe the complex vulnerabilities of the contemporary patient within and beyond coronary artery disease. SE2030 was started with a recruitment plan from 2021 to 2025 (and follow-up to 2030) with 12 subprojects (ranging from coronary artery disease to valvular and post-COVID-19 patients). With these features, the study poses particular challenges on quality control assurance, methodological harmonization, and data management. One of the significant upgrades of SE2030 compared to SE2020 was developing and implementing a Research Electronic Data Capture (REDCap)-based infrastructure for interactive and entirely web-based data management to integrate and optimize reproducible clinical research data. The purposes of our paper were: first, to describe the methodology used for quality control of imaging data, and second, to present the informatic infrastructure developed on RedCap platform for data entry, storage, and management in a large-scale multicenter study.
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spelling pubmed-83053202021-07-25 Imaging Quality Control, Methodology Harmonization and Clinical Data Management in Stress Echo 2030 Bartolacelli, Ylenia Barbieri, Andrea Antonini-Canterin, Francesco Pepi, Mauro Monte, Ines Paola Trocino, Giuseppe Barchitta, Agata Cresti, Alberto Miceli, Sofia Petrella, Licia Benedetto, Frank Zito, Concetta Benfari, Giovanni Bursi, Francesca Malagoli, Alessandro Mantovani, Francesca Ciampi, Quirino Zagatina, Angela Palinkas, Eszter Dalma Palinkas, Attila Toth, Szilvia Rostasne Wierzbowska-Drabik, Karina Djordievic-Dikic, Ana Pellikka, Patricia A. Picano, Eugenio J Clin Med Article Stress echo (SE) 2030 study is an international, prospective, multicenter cohort study that will include >10,000 patients from ≥20 centers from ≥10 countries. It represents the logical and chronological continuation of the SE 2020 study, which developed, validated, and disseminated the “ABCDE protocol” of SE, more suitable than conventional SE to describe the complex vulnerabilities of the contemporary patient within and beyond coronary artery disease. SE2030 was started with a recruitment plan from 2021 to 2025 (and follow-up to 2030) with 12 subprojects (ranging from coronary artery disease to valvular and post-COVID-19 patients). With these features, the study poses particular challenges on quality control assurance, methodological harmonization, and data management. One of the significant upgrades of SE2030 compared to SE2020 was developing and implementing a Research Electronic Data Capture (REDCap)-based infrastructure for interactive and entirely web-based data management to integrate and optimize reproducible clinical research data. The purposes of our paper were: first, to describe the methodology used for quality control of imaging data, and second, to present the informatic infrastructure developed on RedCap platform for data entry, storage, and management in a large-scale multicenter study. MDPI 2021-07-07 /pmc/articles/PMC8305320/ /pubmed/34300186 http://dx.doi.org/10.3390/jcm10143020 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bartolacelli, Ylenia
Barbieri, Andrea
Antonini-Canterin, Francesco
Pepi, Mauro
Monte, Ines Paola
Trocino, Giuseppe
Barchitta, Agata
Cresti, Alberto
Miceli, Sofia
Petrella, Licia
Benedetto, Frank
Zito, Concetta
Benfari, Giovanni
Bursi, Francesca
Malagoli, Alessandro
Mantovani, Francesca
Ciampi, Quirino
Zagatina, Angela
Palinkas, Eszter Dalma
Palinkas, Attila
Toth, Szilvia Rostasne
Wierzbowska-Drabik, Karina
Djordievic-Dikic, Ana
Pellikka, Patricia A.
Picano, Eugenio
Imaging Quality Control, Methodology Harmonization and Clinical Data Management in Stress Echo 2030
title Imaging Quality Control, Methodology Harmonization and Clinical Data Management in Stress Echo 2030
title_full Imaging Quality Control, Methodology Harmonization and Clinical Data Management in Stress Echo 2030
title_fullStr Imaging Quality Control, Methodology Harmonization and Clinical Data Management in Stress Echo 2030
title_full_unstemmed Imaging Quality Control, Methodology Harmonization and Clinical Data Management in Stress Echo 2030
title_short Imaging Quality Control, Methodology Harmonization and Clinical Data Management in Stress Echo 2030
title_sort imaging quality control, methodology harmonization and clinical data management in stress echo 2030
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8305320/
https://www.ncbi.nlm.nih.gov/pubmed/34300186
http://dx.doi.org/10.3390/jcm10143020
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