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A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods.
Dhafari, Thamer Ba; Pate, Alexander; Azadbakht, Narges; Bailey, Rowena; Rafferty, James; Jalali-Najafabadi, Farideh; Martin, Glen P; Hassaine, Abdelaali; Akbari, Ashley; Lyons, Jane; Watkins, Alan; Lyons, Ronan A; Peek, Niels.
Afiliação
  • Dhafari TB; Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK.
  • Pate A; Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK.
  • Azadbakht N; Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK.
  • Bailey R; Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK.
  • Rafferty J; Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK.
  • Jalali-Najafabadi F; Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, M13 9PL Manchester, UK.
  • Martin GP; Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK.
  • Hassaine A; Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK.
  • Akbari A; Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK.
  • Lyons J; Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK.
  • Watkins A; Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK.
  • Lyons RA; Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK.
  • Peek N; Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK; NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK. Electronic address
J Clin Epidemiol ; 165: 111214, 2024 Jan.
Article em En | MEDLINE | ID: mdl-37952700
ABSTRACT

OBJECTIVES:

Multimorbidity, the presence of two or more long-term conditions, is a growing public health concern. Many studies use analytical methods to discover multimorbidity patterns from data. We aimed to review approaches used in published literature to validate these patterns. STUDY DESIGN AND

SETTING:

We systematically searched PubMed and Web of Science for studies published between July 2017 and July 2023 that used analytical methods to discover multimorbidity patterns.

RESULTS:

Out of 31,617 studies returned by the searches, 172 were included. Of these, 111 studies (64%) conducted validation, the number of studies with validation increased from 53.13% (17 out of 32 studies) to 71.25% (57 out of 80 studies) in 2017-2019 to 2022-2023, respectively. Five types of validation were identified assessing the association of multimorbidity patterns with clinical outcomes (n = 79), stability across subsamples (n = 26), clinical plausibility (n = 22), stability across methods (n = 7) and exploring common determinants (n = 2). Some studies used multiple types of validation.

CONCLUSION:

The number of studies conducting a validation of multimorbidity patterns is clearly increasing. The most popular validation approach is assessing the association of multimorbidity patterns with clinical outcomes. Methodological guidance on the validation of multimorbidity patterns is needed.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Projetos de Pesquisa / Multimorbidade Tipo de estudo: Systematic_reviews Limite: Humans Idioma: En Revista: J Clin Epidemiol Assunto da revista: EPIDEMIOLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Projetos de Pesquisa / Multimorbidade Tipo de estudo: Systematic_reviews Limite: Humans Idioma: En Revista: J Clin Epidemiol Assunto da revista: EPIDEMIOLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Reino Unido