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

• Main Authors: Ylenia Bartolacelli, Andrea Barbieri, Francesco Antonini-Canterin, Mauro Pepi, Ines Paola Monte, Giuseppe Trocino, Agata Barchitta, Alberto Cresti, Sofia Miceli, Licia Petrella, Frank Benedetto, Concetta Zito, Giovanni Benfari, Francesca Bursi, Alessandro Malagoli, Francesca Mantovani, Quirino Ciampi, Angela Zagatina, Eszter Dalma Palinkas, Attila Palinkas, Szilvia Rostasne Toth, Karina Wierzbowska-Drabik, Ana Djordievic-Dikic, Patricia A. Pellikka, Eugenio Picano, on behalf of the Stress Echo 2030 Study Group of the Italian Society of Echocardiography and Cardiovascular Imaging
• Format: Article
• Language: English
• Published: MDPI AG 2021-07-01
• Series: Journal of Clinical Medicine
• Subjects: stress echo; redcap; methodology
• Online Access: https://www.mdpi.com/2077-0383/10/14/3020

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.