Evidence map›Paper›PMID 37094888›Full record

ArticleBMJ open2023

PREdiction and Diagnosis using Imaging and Clinical biomarkers Trial in Traumatic Brain Injury (PREDICT-TBI) study protocol: an observational, prospective, multicentre cohort study for the prediction of outcome in moderate-to-severe TBI.

Fatima Nasrallah, Judith Bellapart, James Walsham, Esther Jacobson, Xuan Vinh To, Silvia Manzanero, Nathan Brown, Jason Meyer, Janine Stuart, Tracey Evans and 9 more

Open access · goldAbstract readClinical Trial Protocol
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
2.9field-weighted citation impact, top 9% of its field
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 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Development and validation of a nomogram for predicting mortality in patients with acute severe traumatic brain injury: A retrospective analysis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024
    Article
  9. Article
  10. Review
  11. Article
  12. Review
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

19 authors at 9 institutions in 2 countries.

Fatima NasrallahThe Queensland Brain Institute, The University of Queensland, Saint Lucia, Queensland, Australia f.nasrallah@uq.edu.au.ORCID 0000-0002-7385-9559
Judith BellapartIntensive Care Unit, Royal Brisbane and Women's Hospital, Metro North Health Service District, Herston, Queensland, Australia.
James WalshamIntensive Care Unit, Princess Alexandra Hospital, Woolloongabba, Queensland, Australia.
Esther JacobsonJamieson Trauma Institute, Metro North Health Service District, Herston, Queensland, Australia.
Xuan Vinh ToThe Queensland Brain Institute, The University of Queensland, Saint Lucia, Queensland, Australia.
Silvia ManzaneroJamieson Trauma Institute, Metro North Health Service District, Herston, Queensland, Australia.
Nathan BrownIntensive Care Unit, Royal Brisbane and Women's Hospital, Metro North Health Service District, Herston, Queensland, Australia.
Jason MeyerIntensive Care Unit, Princess Alexandra Hospital, Woolloongabba, Queensland, Australia.ORCID 0000-0002-9344-1280
Janine StuartIntensive Care Unit, Royal Brisbane and Women's Hospital, Metro North Health Service District, Herston, Queensland, Australia.
Tracey EvansThe Queensland Brain Institute, The University of Queensland, Saint Lucia, Queensland, Australia.
Shekhar S ChandraSchool of Information Technology and Electrical Engineering, Architecture and Information Technology, The University of Queensland, Saint Lucia, Queensland, Australia.
Jason RossHealth and Biosecurity, CSIRO, Westmead, New South Wales, Australia.
Lewis CampbellIntensive Care Unit, Royal Darwin Hospital, Casuarina, Darwin, Australia.
Siva SenthuranIntensive Care Unit, Townsville Hospital and Health Service, Townsville, Queensland, Australia.
Virginia NewcombeUniversity Division of Anaesthesia, University of Cambridge, Cambridge, UK.ORCID 0000-0001-6044-9035
James McCulloughIntensive Care Unit, Gold Coast Hospital and Health Service, Gold Coast, Queensland, Australia.
Jennifer FlemingSchool of Health and Rehabilitation Sciences, The University of Queensland, Saint Lucia, Queensland, Australia.
Clifford PollardSchool of Information Technology and Electrical Engineering, Architecture and Information Technology, The University of Queensland, Saint Lucia, Queensland, Australia.
Michael ReadeIntensive Care Unit, Royal Brisbane and Women's Hospital, Metro North Health Service District, Herston, Queensland, Australia.ORCID 0000-0003-1570-0707
The University of Queensland · AUQueensland Health · AURoyal Brisbane and Women's Hospital · AUCSIRO Health and Biosecurity · AUFlinders University · AUGold Coast Hospital · AUPrincess Alexandra Hospital · AUTownsville Hospital · AUUniversity of Cambridge · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTraumatic brain injury (TBI) is a heterogeneous condition with a broad spectrum of injury severity, pathophysiological processes and variable outcomes. For moderate-to-severe TBI survivors, recovery is often protracted and outcomes can range from total dependence to full recovery. Despite advances in medical treatment options, prognosis remains largely unchanged. The objective of this study is to develop a machine learning predictive model for neurological outcomes at 6 months in patients with a moderate-to-severe TBI, incorporating longitudinal clinical, multimodal neuroimaging and blood biomarker predictor variables. METHODS AND ANALYSIS: A prospective, observational, cohort study will enrol 300 patients with moderate-to-severe TBI from seven Australian hospitals over 3 years. Candidate predictors including demographic and general health variables, and longitudinal clinical, neuroimaging (CT and MRI), blood biomarker and patient-reported outcome measures will be collected at multiple time points within the acute phase of injury. The predictor variables will populate novel machine learning models to predict the Glasgow Outcome Scale Extended 6 months after injury. The study will also expand on current prognostic models by including novel blood biomarkers (circulating cell-free DNA), and the results of quantitative neuroimaging such as Quantitative Susceptibility Mapping and Dynamic Contrast Enhanced MRI as predictor variables. ETHICS AND DISSEMINATION: Ethical approval has been obtained by the Royal Brisbane and Women's Hospital Human Research Ethics Committee, Queensland. Participants or their substitute decision-maker/s will receive oral and written information about the study before providing written informed consent. Study findings will be disseminated by peer-review publications and presented at national and international conferences and clinical networks. TRIAL REGISTRATION NUMBER: ACTRN12620001360909.

Indexed as

Brain Injuries, TraumaticAustraliaBiomarkersCohort StudiesFemaleHumansMulticenter Studies as TopicObservational Studies as TopicProspective StudiesBiomarkersINTENSIVE & CRITICAL CAREMagnetic resonance imagingNeurological injury

Identifiers

PMID37094888
PMCPMC10151972
OpenAlexW4366817606

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.