Group 1 was submitted to a two-day MIBI protocol in a conventional camera, and group 2 was submitted to a 1-day MIBI protocol in CZT camera. MPI were classified as normal or abnormal, and perfusion scores were calculated. Propensity score matching methods were performed RESULTS: 3554 patients were followed during 33±8 months. Groups 1 and 2 had similar distribution of age, gender, body mass index, risk factors, previous revascularization, and use of pharmacological stress. Group 1 had more abnormal scans, higher scores than group 2. Annualized hard events rate was higher in group 1 with normal scans but frequency of revascularization was similar to normal group 2. Patients with abnormal scans had similar event rates in both groups CONCLUSION: New protocol of MPI in CZT-SPECT showed similar prognostic results to those obtained in dedicated cardiac Na-I SPECT camera, with lower prevalence of hard events in patients with normal scan.
A pandemia da COVID-19 é uma ameaça global. Se, por um lado, contabilizamos muitas perdas de vidas, por outro lado tem-se acelerado a geração de datasets e demandas analíticas urgentes. Dentre as estratégias de combate, destacam-se a vacinação e as investigações epidemiológicas centradas em dados. Este artigo apresenta o processo de construção de datasets curados e anotados com metadados de proveniência retrospectiva, tendo como base os dados de registro da Campanha de Vacinação contra COVID-19 no Brasil. O dataset contém milhares de registros tratados até Março de 2021. Os dados foram analisados, investigados, tratados e cruzados com outras fontes, de modo a corrigi-los e complementá-los, resultando em datasets curados e alinhados aos princípios FAIR.
As the world struggles to face the challenges of vaccination against COVID-19, more attention needs to be paid to the issues related to the lack of transparency and accessibility of curated vaccination datasets. Among the strategies to combat COVID-19, vaccination and data-centered epidemiological investigations are the best ones. This paper presents the process of building cured and annotated datasets with provenance metadata. The primary dataset is based on the registration data of the Vaccination Campaign against COVID-19 in Brazil. The dataset contains thousands of records processed up to March 2021. The data were analyzed, treated, cross-checked, and linked with other sources to correct and complement them, resulting in cured datasets and aligned to the FAIR Data principles.
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