Evidence map›Paper›PMID 29402765›Full record

ArticleCerebrovascular diseases (Basel, Switzerland)2018

Computed Tomography Perfusion Derived Blood-Brain Barrier Permeability Does Not Yet Improve Prediction of Hemorrhagic Transformation.

Alexander D Horsch, Edwin Bennink, Tom van Seeters, L Jaap Kappelle, Yolanda van der Graaf, Willem P T M Mali, Hugo W A M de Jong, Birgitta K Velthuis, Jan Willem Dankbaar, DUST Investigators

Open access · hybridAbstract readMulticenter Study
In one paragraph

Article in Cerebrovascular diseases (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 3 pooled it
1.9field-weighted citation impact, top 14% 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

10 citing papers in PubMed, 3 syntheses or guidelines pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Minimal Imaging Requirements.Journal of neuroendovascular therapy · 2023
    Review
  7. Value of pre-intervention CT perfusion imaging in acute ischemic stroke prognosis.Diagnostic and interventional radiology (Ankara, Turkey) · 2021
    Article
  8. Article
  9. Article
  10. 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

10 authors at 2 institutions in 1 country.

Alexander D HorschDepartment of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands.
Edwin BenninkDepartment of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands.
Tom van SeetersDepartment of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands.
L Jaap KappelleDepartment of Neurology, Utrecht Stroke Center, University Medical Center Utrecht, Utrecht, the Netherlands.
Yolanda van der GraafJulius Center for Health Sciences and Primary Care, Utrecht, the Netherlands.
Willem P T M MaliDepartment of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands.
Hugo W A M de JongDepartment of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands.
Birgitta K VelthuisDepartment of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands.
Jan Willem DankbaarDepartment of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands.
DUST Investigators
University Medical Center Utrecht · NLUtrecht University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionHemorrhagic transformation (HT) in acute ischemic stroke can occur as a result of reperfusion treatment. While withholding treatment may be warranted in patients with increased risk of HT, prediction of HT remains difficult. Nonlinear regression analysis can be used to estimate blood-brain barrier permeability (BBBP). The aim of this study was to identify a combination of clinical and imaging variables, including BBBP estimations, that can predict HT. MATERIALS AND

methodsFrom the Dutch acute stroke study, 545 patients treated with intravenous recombinant tissue plasminogen activator and/or intra-arterial treatment were selected, with available admission extended computed tomography (CT) perfusion and follow-up imaging. Patient admission treatment characteristics and CT imaging parameters regarding occlusion site, stroke severity, and BBBP were recorded. HT was assessed on day 3 follow-up imaging. The association between potential predictors and HT was analyzed using univariate and multivariate logistic regression. To compare the added value of BBBP, areas under the curve (AUCs) were created from 2 models, with and without BBBP.

resultsHT occurred in 57 patients (10%). In univariate analysis, older age (OR 1.03, 95% CI 1.006-1.05), higher admission National Institutes of Health Stroke Scale (NIHSS; OR 1.13, 95% CI 1.08-1.18), higher clot burden (OR 1.28, 95% CI 1.16-1.41), poor collateral score (OR 3.49, 95% CI 1.85-6.58), larger Alberta Stroke Program Early CT Score cerebral blood volume deficit size (OR 1.26, 95% CI 1.14-1.38), and increased BBBP (OR 2.22, 95% CI 1.46-3.37) were associated with HT. In multivariate analysis with age and admission NIHSS, the addition of BBBP did not improve the AUC compared to both independent predictors alone (AUC 0.77, 95% CI 0.71-0.83).

conclusionBBBP predicts HT but does not improve prediction with age and admission NIHSS.

Indexed as

Computed Tomography AngiographyAgedAged, 80 and overAge FactorsBlood-Brain BarrierBrain IschemiaCapillary PermeabilityCerebral AngiographyCerebrovascular CirculationDisability EvaluationFemaleFibrinolytic AgentsHumansInfusions, IntravenousIntracranial HemorrhagesMaleFibrinolytic AgentsTissue Plasminogen ActivatorBrainComputed tomographyHemorrhagic transformationIschemic strokeNonlinear regression permeabilityPrediction

Identifiers

PMID29402765
PMCPMC5972514
OpenAlexW2784082603

What OpenQuestion holds

Textmetadata
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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.