FAST-IT: Find A Simple Test - In TIA (Transient Ischaemic Attack) - a prospective cohort study to develop a multivariable prediction model for diagnosis of TIA through proteomic discovery and candidate lipid mass-spectrometry, neuroimaging and machine learning - study protocol

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dc.contributor.authorMilton, A.G.
dc.contributor.authorLau, S.
dc.contributor.authorKremer, K.L.
dc.contributor.authorRao, S.R.
dc.contributor.authorMAS, E.
dc.contributor.authorSnel, M.F.
dc.contributor.authorTrim, P.J.
dc.contributor.authorSharma, D.
dc.contributor.authorEdwards, S.
dc.contributor.authorJenkinson, M.
dc.contributor.authorKleinig, T.J.
dc.contributor.authorNoschka, E.
dc.contributor.authorHamilton-Bruce, M.A.
dc.contributor.authorKoblar, S.A.
dc.date.issued2022
dc.description.abstractIntroduction Transient ischaemic attack (TIA) may be a warning sign of stroke and difficult to differentiate from minor stroke and TIA-mimics. Urgent evaluation and diagnosis is important as treating TIA early can prevent subsequent strokes. Recent improvements in mass spectrometer technology allow quantification of hundreds of plasma proteins and lipids, yielding large datasets that would benefit from different approaches including machine learning. Using plasma protein, lipid and radiological biomarkers, our study will develop predictive algorithms to distinguish TIA from minor stroke (positive control) and TIA-mimics (negative control). Analysis including machine learning employs more sophisticated modelling, allowing non-linear interactions, adapting to datasets and enabling development of multiple specialised test-panels for identification and differentiation. Methods and analysis Patients attending the Emergency Department, Stroke Ward or TIA Clinic at the Royal Adelaide Hospital with TIA, minor stroke or TIA-like symptoms will be recruited consecutively by staff-alert for this prospective cohort study. Advanced neuroimaging will be performed for each participant, with images assessed independently by up to three expert neurologists. Venous blood samples will be collected within 48 hours of symptom onset. Plasma proteomic and lipid analysis will use advanced mass spectrometry (MS) techniques. Principal component analysis and hierarchical cluster analysis will be performed using MS software. Output files will be analysed for relative biomarker quantitative differences between the three groups. Differences will be assessed by linear regression, one-way analysis of variance, Kruskal-Wallis H-test, χ2 test or Fisher’s exact test. Machine learning methods will also be applied including deep learning using neural networks.
dc.description.statementofresponsibilityAustin G Milton, Stephan Lau, Karlea L Kremer, Sushma R Rao, Emilie Mas, Marten F Snel, Paul J Trim, Deeksha Sharma, Suzanne Edwards, Mark Jenkinson, Timothy Kleinig, Erik Noschka, Monica Anne Hamilton-Bruce, Simon A Koblar
dc.identifier.citationBMJ Open, 2022; 12(4):1-9
dc.identifier.doi10.1136/bmjopen-2020-045908
dc.identifier.issn2044-6055
dc.identifier.issn2044-6055
dc.identifier.orcidLau, S. [0000-0002-5952-0516]
dc.identifier.orcidMAS, E. [0000-0003-2848-9613]
dc.identifier.orcidSnel, M.F. [0000-0002-8502-7274]
dc.identifier.orcidTrim, P.J. [0000-0001-8734-3433]
dc.identifier.orcidSharma, D. [0000-0002-7775-6098]
dc.identifier.orcidEdwards, S. [0000-0003-2074-1685]
dc.identifier.orcidJenkinson, M. [0000-0001-6043-0166]
dc.identifier.orcidKleinig, T.J. [0000-0003-4430-3276]
dc.identifier.orcidNoschka, E. [0000-0002-6058-3549]
dc.identifier.orcidHamilton-Bruce, M.A. [0000-0002-5222-620X]
dc.identifier.orcidKoblar, S.A. [0000-0002-8667-203X]
dc.identifier.urihttps://hdl.handle.net/2440/140311
dc.language.isoen
dc.publisherBMJ Journals
dc.rights© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
dc.source.urihttps://doi.org/10.1136/bmjopen-2020-045908
dc.subjectTransient ischaemic attack (TIA)
dc.subject.meshHumans
dc.subject.meshIschemic Attack, Transient
dc.subject.meshLipids
dc.subject.meshProspective Studies
dc.subject.meshProteomics
dc.subject.meshMass Spectrometry
dc.subject.meshNeuroimaging
dc.subject.meshMachine Learning
dc.titleFAST-IT: Find A Simple Test - In TIA (Transient Ischaemic Attack) - a prospective cohort study to develop a multivariable prediction model for diagnosis of TIA through proteomic discovery and candidate lipid mass-spectrometry, neuroimaging and machine learning - study protocol
dc.typeJournal article
pubs.publication-statusAccepted

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