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A Pragmatic Method to Integrate Data from Pre-existing Cohort Studies using the Clinical Data Interchange Standards Consortium (CDISC) Study Data Tabulation Model: Practical use of REDCap2SDTM.
Matsuzaki, Keiichi; Kitayama, Megumi; Yamamoto, Keiichi; Aida, Rei; Imai, Takumi; Ishida, Mami; Katafichi, Ritsuko; Kawamura, Tetsuya; Yokoo, Takashi; Narita, Ichiei; Suzuki, Yusuke.
Afiliación
  • Matsuzaki K; Department of Public Health, Kitasato University School of Medicine, 1-15-1 Kitasato, Minami-ku, Sagamihara, JP.
  • Kitayama M; Progressive Renal Diseases Research, Research on Intractable Disease, from the Ministry of Health, Labour and Welfare of Japan, Tokyo, JP.
  • Yamamoto K; Clinical Study Support Center, Wakayama Medical University Hospital, Wakayama, JP.
  • Aida R; Translational Research Institute for Medical Innovation, Osaka Dental University, Osaka, JP.
  • Imai T; Department of Medical Statistics, Osaka Metropolitan University, Osaka, JP.
  • Ishida M; Clinical & Translational Research Center, Kobe University Hospital, Kobe, JP.
  • Katafichi R; Department of Medical Informatics and Clinical Epidemiology, Kyoto Prefectural University of Medicine, Kyoto, JP.
  • Kawamura T; Kidney Unit, National Hospital Organization Fukuokahigashi Medical Center, Fukuoka, JP.
  • Yokoo T; Kidney Unit, Medical Corporation Houshikai Kano Hospital, Fukuoka, JP.
  • Narita I; Progressive Renal Diseases Research, Research on Intractable Disease, from the Ministry of Health, Labour and Welfare of Japan, Tokyo, JP.
  • Suzuki Y; Division of Kidney and Hypertension, Department of Internal Medicine, Jikei University School of Medicine, Tokyo, JP.
JMIR Med Inform ; 2023 Sep 14.
Article en En | MEDLINE | ID: mdl-37768110
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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Etiology_studies / Guideline / Observational_studies / Prognostic_studies Idioma: En Revista: JMIR Med Inform Año: 2023 Tipo del documento: Article País de afiliación: Japón
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Etiology_studies / Guideline / Observational_studies / Prognostic_studies Idioma: En Revista: JMIR Med Inform Año: 2023 Tipo del documento: Article País de afiliación: Japón