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Establishing a database for sickle cell disease patient mapping and survival tracking: The sickle pan-african research consortium Nigeria example.
Nnodu, Obiageli; Madu, Anazoeze; Chianumba, Reuben; Isa, Hezekiah Alkali; Olanrewaju, Isaac; Osagie, Samuel; Oyekanmi, Nash; Sangeda, Raphael Zozimus; Stewart, Annemie; Nembaware, Victoria; Morrice, Jack; Jonas, Mario; Mazandu, Gaston; Wonkam, Ambroise; Owolabi, Olumide.
Afiliação
  • Nnodu O; Centre of Excellence for Sickle Cell Disease Research and Training (CESRTA), University of Abuja, Abuja, Nigeria.
  • Madu A; Department of Haematology and Blood Transfusion, University of Abuja, Abuja, Nigeria.
  • Chianumba R; Department of Haematology and Immunology, College of Medicine, University of Nigeria, Enugu, Nigeria.
  • Isa HA; Department of Haematology and Blood Transfusion, University of Abuja, Abuja, Nigeria.
  • Olanrewaju I; Centre of Excellence for Sickle Cell Disease Research and Training (CESRTA), University of Abuja, Abuja, Nigeria.
  • Osagie S; Department of Haematology and Blood Transfusion, University of Abuja, Abuja, Nigeria.
  • Oyekanmi N; Department of Computer Science, University of Abuja, Abuja, Nigeria.
  • Sangeda RZ; ITMS Unit, University of Abuja, Abuja, Nigeria.
  • Stewart A; H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, Abuja, Nigeria.
  • Nembaware V; Department of Pharmaceutical Microbiology, Muhimbili University of Health and Allied Sciences, Dar Es Salaam, Tanzania.
  • Morrice J; UCT Clinical Research Centre, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
  • Jonas M; Computational Biology Division, IDM, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
  • Mazandu G; Division of Human Genetics, Department of Pathology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
  • Wonkam A; Faculty of Health Sciences, Department of Pathology, Division of Human Genetics, University of Cape Town, Cape Town, South Africa.
  • Owolabi O; Computational Biology Division, IDM, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
Front Genet ; 13: 1041462, 2022.
Article em En | MEDLINE | ID: mdl-36406113
ABSTRACT

Background:

The Sickle Pan-African Research Consortium (SPARCO) and Sickle Africa Data Coordinating Center (SADaCC) were set up with funding from the US National Institute of Health (NIH) for physicians, scientists, patients, support groups, and statisticians to collaborate to reduce the high disease burden and alleviate the impact of Sickle Cell Disease (SCD) in Africa. For 5 years, SPARCO and SADaCC have been collecting basic clinical and demographic data from Nigeria, Tanzania, and Ghana. The resulting database will support analyses to estimate significant clinical events and provide directions for targeting interventions and assessing their impacts.

Method:

The Nigerian study sited at Centre of Excellence for Sickle Cell Disease Research and Training (CESRTA), University of Abuja, adopted REDCap for online database management. The case report form (CRF) was adapted from 1,400 data elements adopted by SPARCO sites. It captures 215 data elements of interest across sub-sites, i.e., demographic, social, diagnostic, clinical, laboratory, imaging, and others. These were harmonized using the SADaCC data dictionary. REDCap was installed on University of Abuja cloud server at https//www.redcap.uniabuja.edu.ng. Data collected at the sites are sent to CESRTA for collation, cleaning and uploading to the database.

Results:

7,767 people living with sickle cell disease were enrolled at 25 health institutions across the six zones in Nigeria with 5,295 having had at least one follow-up visit with their clinical data updated. They range from 44 to 1,180 from 3 centers from South East, 4 from South, 5 from South West, 8 from North Central, 4 in North West and 3 in the North East. North West has registered 1,383 patients, representing 17.8%; North East, 359 (4.6%); North Central, 2,947 (37.9%); South West, 1,609 (20.7%); South, 442 (5.7%) and South East, 1,027 patients (13.2%).

Conclusion:

The database is being used to support studies including analysis of clinical phenotypes of SCD in Nigeria, and evaluation of Hydroxyurea use in SCD. Reports undergoing review in journals have relied on the ease of data access in REDCap. The database is regularly updated by batch and individual record uploads while we are utilizing REDCap's in-built functions to generate simple statistic.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Genet Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Nigéria

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Genet Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Nigéria