Evidence map›Paper›PMID 32935048›Full record

ArticleInternational journal of population data science2020

The Secure Anonymised Information Linkage databank Dementia e-cohort (SAIL-DeC).

C Schnier, T Wilkinson, A Akbari, C Orton, K Sleegers, J Gallacher, R A Lyons, Clm Sudlow

Abstract read
In one paragraph

Article in International journal of population data science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Observational
  5. Article
  6. Article
  7. Artificial intelligence for dementia-Applied models and digital health.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2023
    Review
  8. Article
  9. Observational
  10. Article
  11. Observational
  12. Observational
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. A Profile of the SAIL Databank on the UK Secure Research Platform.International journal of population data science · 2019
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

C SchnierUsher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.
T WilkinsonUsher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.
A AkbariHealth Data Research UK Wales and Northern Ireland, Swansea University, Swansea, UK.
C OrtonHealth Data Research UK Wales and Northern Ireland, Swansea University, Swansea, UK.
K SleegersCenter for Molecular Neurology, University of Antwerp, Antwerp, Belgium.
J GallacherDepartment of Psychiatry, University of Oxford, Oxford, UK.
R A LyonsHealth Data Research UK Wales and Northern Ireland, Swansea University, Swansea, UK.
Clm SudlowUsher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.

Funding

Medical Research Council MR/L023784/1Medical Research Council MR/L023784/2Medical Research Council MR/M024881/1Medical Research Council MR/P001823/1Wellcome Trust
6 · The paper itself

Abstract

introductionThe rising burden of dementia is a global concern, and there is a need to study its causes, natural history and outcomes. The Secure Anonymised Information Linkage (SAIL) Databank contains anonymised, routinely-collected healthcare data for the population of Wales, UK. It has potential to be a valuable resource for dementia research owing to its size, long follow-up time and prospective collection of data during clinical care.

objectivesWe aimed to apply reproducible methods to create the SAIL dementia e-cohort (SAIL-DeC). We created SAIL-DeC with a view to maximising its utility for a broad range of research questions whilst minimising duplication of effort for researchers.

methodsSAIL contains individual-level, linked primary care, hospital admission, mortality and demographic data. Data are currently available until 2018 and future updates will extend participant follow-up time. We included participants who were born between 1st January 1900 and 1st January 1958 and for whom primary care data were available. We applied algorithms consisting of International Classification of Diseases (versions 9 and 10) and Read (version 2) codes to identify participants with and without all-cause dementia and dementia subtypes. We also created derived variables for comorbidities and risk factors.

resultsFrom 4.4 million unique participants in SAIL, 1.2 million met the cohort inclusion criteria, resulting in 18.8 million person-years of follow-up. Of these, 129,650 (10%) developed all-cause dementia, with 77,978 (60%) having dementia subtype codes. Alzheimer's disease was the most common subtype diagnosis (62%). Among the dementia cases, the median duration of observation time was 14 years.

conclusionWe have created a generalisable, national dementia e-cohort, aimed at facilitating epidemiological dementia research.

Identifiers

PMID32935048
PMCPMC7473277

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.