Dataset Information

A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data.

ABSTRACT: The COVID-19 pandemic has worldwide individual and socioeconomic consequences. Chest computed tomography has been found to support diagnostics and disease monitoring. A standardized approach to generate, collect, analyze, and share clinical and imaging information in the highest quality possible is urgently needed. We developed systematic, computer-assisted and context-guided electronic data capture on the FDA-approved mint Lesion^TM software platform to enable cloud-based data collection and real-time analysis. The acquisition and annotation include radiological findings and radiomics performed directly on primary imaging data together with information from the patient history and clinical data. As proof of concept, anonymized data of 283 patients with either suspected or confirmed SARS-CoV-2 infection from eight European medical centers were aggregated in data analysis dashboards. Aggregated data were compared to key findings of landmark research literature. This concept has been chosen for use in the national COVID-19 response of the radiological departments of all university hospitals in Germany.

SUBMITTER: Salg GA

PROVIDER: S-EPMC8041811 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data.

Salg Gabriel Alexander GA Ganten Maria-Katharina MK Bucher Andreas Michael AM Kenngott Hannes Goetz HG Fink Matthias Alexander MA Seibold Constantin C Fischbach Ricarda Elisabeth RE Schlamp Kai K Velandia Carlos Alberto CA Fervers Philipp P Doellinger Felix F Luger Anna A Afat Saif S Merle Uta U Diener Markus K MK Pereira Philippe L PL Penzkofer Tobias T Persigehl Thorsten T Othman Ahmed A Heußel Claus Peter CP Baumhauer Matthias M Widmann Gerlig G Stathopoulos Konstantinos K Hamm Bernd B Vogl Thomas J TJ Nikolaou Konstantin K Kauczor Hans-Ulrich HU Kleesiek Jens J

NPJ digital medicine 20210412 1

The COVID-19 pandemic has worldwide individual and socioeconomic consequences. Chest computed tomography has been found to support diagnostics and disease monitoring. A standardized approach to generate, collect, analyze, and share clinical and imaging information in the highest quality possible is urgently needed. We developed systematic, computer-assisted and context-guided electronic data capture on the FDA-approved mint Lesion<sup>TM</sup> software platform to enable cloud-based data collect ...[more]

PMID: 33846548

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Project description:BackgroundCOVID-19 has challenged health services throughout the world in terms of hospital capacity and put staff and vulnerable populations at risk of infection. In the face of these challenges, many health providers have implemented remote patient monitoring (RPM) of COVID-19 patients in their own homes. However systematic reviews of the literature on these implementations have revealed wide variations in how RPM is implemented; along with variations in particulars of RPM reported on, making comparison and evaluation difficult. A review of reported items is warranted to develop a framework of key items to enhance reporting consistency. The aims of this review of remote monitoring for COVID-19 patients are twofold: (1) to facilitate comparison between RPM implementations by tabulating information and values under common domains. (2) to develop a reporting framework to enhance reporting consistency.MethodA review of the literature for RPM for COVID-19 patients was conducted following PRISMA guidelines. The Medline database was searched for articles published between 2020 to February 2023 and studies reporting on items with sufficient detail to compare one with another were included. Relevant data was extracted and synthesized by the lead author. Quality appraisal was not conducted as the the articles considered were evaluated as informational reports of clinical implementations rather than as studies designed to answer a research question.ResultsFrom 305 studies retrieved, 23 studies were included in the review: fourteen from the US, two from the UK and one each from Africa, Ireland, China, the Netherlands, Belgium, Australia and Italy. Sixteen generally reported items were identified, shown with the percentage of studies reporting in brackets: Reporting Period (82%), Rationale (100%), Patients (100%), Medical Team (91%) Provider / Infrastructure (91%), Communications Platform (100%), Patient Equipment (100%), Training (48%), Markers (96%), Frequency of prompt / Input (96%),Thresholds (82%), Discharge (61%), Enrolled (96%), Alerts/Escalated (78%), Patient acceptance (43%), and Patient Adherence (52%). Whilst some studies reported on patient training and acceptance, just one reported on staff training and none on staff acceptance.ConclusionsVariations in reported items were found. Pending the establishment of a robust set of reporting guidelines, we propose a reporting framework consisting of eighteen reporting items under the following four domains: Context, Technology, Process and Metrics.

Dataset Information

A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data.

Publications

A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data.

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