Cargando…

Lessons learned from hemolytic uremic syndrome registries: recommendations for implementation

BACKGROUND: Hemolytic uremic syndrome (HUS) is a rare condition which diagnosed with the triad of thrombocytopenia, microangiopathic hemolytic anemia, and acute renal injury. There is a high requirement for research to discover treatments. HUS registries can be used as an important information infra...

Descripción completa

Detalles Bibliográficos
Autores principales: Lazem, Mina, Sheikhtaheri, Abbas, Hooman, Nakysa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8146148/
https://www.ncbi.nlm.nih.gov/pubmed/34034793
http://dx.doi.org/10.1186/s13023-021-01871-9
_version_ 1783697331942588416
author Lazem, Mina
Sheikhtaheri, Abbas
Hooman, Nakysa
author_facet Lazem, Mina
Sheikhtaheri, Abbas
Hooman, Nakysa
author_sort Lazem, Mina
collection PubMed
description BACKGROUND: Hemolytic uremic syndrome (HUS) is a rare condition which diagnosed with the triad of thrombocytopenia, microangiopathic hemolytic anemia, and acute renal injury. There is a high requirement for research to discover treatments. HUS registries can be used as an important information infrastructure. In this study, we identified and compared the different features of HUS registries to present a guide for the development and implementation of HUS registries. RESULTS: The purposes of registries were classified as clinical (9 registries), research (7 registries), and epidemiological (5 registries), and only 3 registries pursued all three types of purposes. The data set included demographic data, medical and family history, para-clinical and diagnostic measures, treatment and pharmacological data, complications, and outcomes. The assessment strategies of data quality included monthly evaluation and data audit, the participation of physicians to collect data, editing and correcting data errors, increasing the rate of data completion, following guidelines and data quality training, using specific data quality indicators, and real-time evaluation of data at the time of data entry. 8 registries include atypical HUS patients, and 7 registries include all patients regardless of age. Only two registries focused on children. 4 registries apply prospective and 4 applied both prospective, and retrospective data collection. Finally, specialized hospitals were the main data source for these registries. CONCLUSION: Based on the findings, we suggested a learning framework for developing and implementing an HUS registry. This framework includes lessons learned and suggestions for HUS registry purposes, minimum data set, data quality assurance, data collection methods, inclusion and exclusion criteria as well as data sources. This framework can help researchers develop HUS registries. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13023-021-01871-9.
format Online
Article
Text
id pubmed-8146148
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-81461482021-05-25 Lessons learned from hemolytic uremic syndrome registries: recommendations for implementation Lazem, Mina Sheikhtaheri, Abbas Hooman, Nakysa Orphanet J Rare Dis Research BACKGROUND: Hemolytic uremic syndrome (HUS) is a rare condition which diagnosed with the triad of thrombocytopenia, microangiopathic hemolytic anemia, and acute renal injury. There is a high requirement for research to discover treatments. HUS registries can be used as an important information infrastructure. In this study, we identified and compared the different features of HUS registries to present a guide for the development and implementation of HUS registries. RESULTS: The purposes of registries were classified as clinical (9 registries), research (7 registries), and epidemiological (5 registries), and only 3 registries pursued all three types of purposes. The data set included demographic data, medical and family history, para-clinical and diagnostic measures, treatment and pharmacological data, complications, and outcomes. The assessment strategies of data quality included monthly evaluation and data audit, the participation of physicians to collect data, editing and correcting data errors, increasing the rate of data completion, following guidelines and data quality training, using specific data quality indicators, and real-time evaluation of data at the time of data entry. 8 registries include atypical HUS patients, and 7 registries include all patients regardless of age. Only two registries focused on children. 4 registries apply prospective and 4 applied both prospective, and retrospective data collection. Finally, specialized hospitals were the main data source for these registries. CONCLUSION: Based on the findings, we suggested a learning framework for developing and implementing an HUS registry. This framework includes lessons learned and suggestions for HUS registry purposes, minimum data set, data quality assurance, data collection methods, inclusion and exclusion criteria as well as data sources. This framework can help researchers develop HUS registries. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13023-021-01871-9. BioMed Central 2021-05-25 /pmc/articles/PMC8146148/ /pubmed/34034793 http://dx.doi.org/10.1186/s13023-021-01871-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Lazem, Mina
Sheikhtaheri, Abbas
Hooman, Nakysa
Lessons learned from hemolytic uremic syndrome registries: recommendations for implementation
title Lessons learned from hemolytic uremic syndrome registries: recommendations for implementation
title_full Lessons learned from hemolytic uremic syndrome registries: recommendations for implementation
title_fullStr Lessons learned from hemolytic uremic syndrome registries: recommendations for implementation
title_full_unstemmed Lessons learned from hemolytic uremic syndrome registries: recommendations for implementation
title_short Lessons learned from hemolytic uremic syndrome registries: recommendations for implementation
title_sort lessons learned from hemolytic uremic syndrome registries: recommendations for implementation
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8146148/
https://www.ncbi.nlm.nih.gov/pubmed/34034793
http://dx.doi.org/10.1186/s13023-021-01871-9
work_keys_str_mv AT lazemmina lessonslearnedfromhemolyticuremicsyndromeregistriesrecommendationsforimplementation
AT sheikhtaheriabbas lessonslearnedfromhemolyticuremicsyndromeregistriesrecommendationsforimplementation
AT hoomannakysa lessonslearnedfromhemolyticuremicsyndromeregistriesrecommendationsforimplementation