Evidence map›Paper›PMID 35168089›Full record

ArticleInternational journal of medical informatics2022

Validation of UK Biobank data for mental health outcomes: A pilot study using secondary care electronic health records.

Zhenpeng Li, Andrey Kormilitzin, Marco Fernandes, Nemanja Vaci, Qiang Liu, Danielle Newby, Sarah Goodday, Tanya Smith, Alejo J Nevado-Holgado, Laura Winchester

Abstract read
In one paragraph

Article in International journal of medical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Artificial intelligence for dementia-Applied models and digital health.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2023
    Review
  9. Article
  10. Article
  11. Article
  12. 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

10 authors.

Zhenpeng LiDepartment of Psychiatry, University of Oxford, Oxford OX3 7JX, UK.
Andrey KormilitzinDepartment of Psychiatry, University of Oxford, Oxford OX3 7JX, UK.
Marco FernandesDepartment of Psychiatry, University of Oxford, Oxford OX3 7JX, UK.
Nemanja VaciDepartment of Psychiatry, University of Oxford, Oxford OX3 7JX, UK.
Qiang LiuDepartment of Psychiatry, University of Oxford, Oxford OX3 7JX, UK.
Danielle NewbyDepartment of Psychiatry, University of Oxford, Oxford OX3 7JX, UK.
Sarah GooddayDepartment of Psychiatry, University of Oxford, Oxford OX3 7JX, UK; 4youandme, Seattle, WA 98121-1031, USA.
Tanya SmithNIHR Biomedical Research Centre, Oxford Health NHS Foundation Trust, Warneford Hospital, Warneford Lane, Oxford OX3 7JX, UK.
Alejo J Nevado-HolgadoDepartment of Psychiatry, University of Oxford, Oxford OX3 7JX, UK.
Laura WinchesterDepartment of Psychiatry, University of Oxford, Oxford OX3 7JX, UK. Electronic address: laura.winchester@psych.ox.ac.uk.

Funding

Medical Research Council MC_PC_17215
6 · The paper itself

Abstract

UK Biobank (UKB) is widely employed to investigate mental health disorders and related exposures; however, its applicability and relevance in a clinical setting and the assumptions required have not been sufficiently and systematically investigated. Here, we present the first validation study using secondary care mental health data with linkage to UKB from Oxford - Clinical Record Interactive Search (CRIS) focusing on comparison of demographic information, diagnostic outcome, medication record and cognitive test results, with missing data and the implied bias from both resources depicted. We applied a natural language processing model to extract information embedded in unstructured text from clinical notes and attachments. Using a contingency table we compared the demographic information recorded in UKB and CRIS. We calculated the positive predictive value (PPV, proportion of true positives cases detected) for mental health diagnosis and relevant medication. Amongst the cohort of 854 subjects, PPVs for any mental health diagnosis for dementia, depression, bipolar disorder and schizophrenia were 41.6%, and were 59.5%, 12.5%, 50.0% and 52.6%, respectively. Self-reported medication records in UKB had general PPV of 47.0%, with the prevalence of frequently prescribed medicines to each typical mental health disorder considerably different from the information provided by CRIS. UKB is highly multimodal, but with limited follow-up records, whereas CRIS offers a longitudinal high-resolution clinical picture with more than ten years of observations. The linkage of both datasets will reduce the self-report bias and synergistically augment diverse modalities into a unified resource to facilitate more robust research in mental health.

Indexed as

Electronic Health RecordsMental HealthBiological Specimen BanksHumansPilot ProjectsSecondary Health CareUnited KingdomData resourceLinkage studiesMental healthNeuro-epidemiologyUK BiobankValidation study

Identifiers

PMID35168089
PMCPMC8889024

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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.