Evidence map›Paper›PMID 20809952›Full record

ArticleBMC musculoskeletal disorders2010

Protocol for a population-based ankylosing spondylitis (PAS) cohort in Wales.

Mark D Atkinson, Sinead Brophy, Stefan Siebert, Mike B Gravenor, Ceri Phillips, David V Ford, Kerina H Jones, Ronan A Lyons

Abstract read
In one paragraph

Article in BMC musculoskeletal disorders, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
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  7. Article
  8. HERALD (health economics using routine anonymised linked data).BMC medical informatics and decision making · 2012
    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.

Mark D AtkinsonSchool of Medicine, Swansea University, Singleton Park, Swansea SA2 8PP, UK. m.atkinson@swansea.ac.uk
Sinead Brophy
Stefan Siebert
Mike B Gravenor
Ceri Phillips
David V Ford
Kerina H Jones
Ronan A Lyons

Funding

Medical Research Council G0800583
6 · The paper itself

Abstract

backgroundTo develop a population-based cohort of people with ankylosing spondylitis (AS) in Wales using (1) secondary care clinical datasets, (2) patient-derived questionnaire data and (3) routinely-collected information in order to examine disease history and the health economic cost of AS.

methodsThis data model will include and link (1) secondary care clinician datasets (i.e. electronic patient notes from the rheumatologist) (2) patient completed questionnaires (giving information on disease activity, medication, function, quality of life, work limitations and health service utilisation) and (3) a broad range of routinely collected data (including; GP records, in-patient hospital admission data, emergency department data, laboratory/pathology data and social services databases). The protocol involves the use of a unique and powerful data linkage system which allows datasets to be interlinked and to complement each other. DISCUSSION: This cohort can integrate patient supplied, primary and secondary care data into a unified data model. This can be used to study a range of issues such as; the true economic costs to the health care system and the patient, factors associated with the development of severe disease, long term adverse events of new and existing medication and to understand the disease history of this condition. It will benefit patients, clinicians and health care managers. This study forms a pilot project for the use of routine data/patient data linked cohorts for other chronic conditions.

Indexed as

Cohort StudiesClinical ProtocolsCross-Sectional StudiesData CollectionHealth SurveysHumansPilot ProjectsSpondylitis, AnkylosingWales

Identifiers

PMID20809952
PMCPMC2941484

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Registered trials

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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.