Evidence map›Paper›PMID 33240454›Full record

ReviewOntario health technology assessment series2020

Automated CT Perfusion Imaging to Aid in the Selection of Patients With Acute Ischemic Stroke for Mechanical Thrombectomy: A Health Technology Assessment.

Ontario Health (Quality)

Abstract readReview
In one paragraph

Review in Ontario health technology assessment series, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  3. Review
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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

1 author.

Ontario Health (Quality)

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStroke is a sudden interruption in the blood supply to a part of the brain, causing loss of neurological function. It is the third leading cause of death in Canada and affects mainly older people. In the acute setting, neuroimaging is integral to stroke evaluation and decision-making. The neuroimaging results guide patient selection for mechanical thrombectomy. Using automated image processing techniques facilitates efficient review of this information and communication between centres. We conducted a health technology assessment of automated CT perfusion imaging as a tool for selecting stroke patients with anterior circulation occlusion for mechanical thrombectomy. This assessment included an evaluation of clinical effectiveness, cost-effectiveness, and the budget impact of publicly funding automated CT perfusion imaging.

methodsWe performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each study using QUADAS-2 or the Cochrane risk-of-bias tool, and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We performed a systematic economic literature search and approximated cost-effectiveness based on previous analyses. We also analyzed the budget impact of publicly funding automated CT perfusion imaging to evaluate people with acute ischemic stroke in Ontario.

resultsAutomated CT perfusion imaging had a sensitivity of 84% for identifying the infarct core (dead tissue that does not recover despite restoring blood flow with mechanical thrombectomy), compared with diffusion-weighted MRI imaging at 24 hours. One study reported that 7% of patients were misclassified with respect to eligibility for mechanical thrombectomy (either erroneously classified as eligible or erroneously classified non-eligible). Two randomized controlled trials (DEFUSE 3 and DAWN) demonstrated the efficacy of mechanical thrombectomy up to 24 hours after stroke onset, with patient selection guided by automated CT perfusion imaging. These data showed that a significantly higher proportion of patients in the mechanical thrombectomy group achieved functional independence compared with the standard care group (DEFUSE 3: risk ratio: 2.67 [95% confidence interval 1.60-4.48]; DAWN: adjusted rate difference: 33% [95% credible interval 21%-44%]; GRADE: Moderate).A previous health technology assessment in stroke patients presenting at 0 to 6 hours after stroke symptom onset and the results from recent randomized controlled trials for patients presenting at 6 to 24 hours informed the evaluation of cost-effectiveness. Mechanical thrombectomy informed by automated CT perfusion imaging to assess eligibility is likely to be cost-effective for patients presenting at 6 to 24 hours after stroke symptom onset. The annual budget impact of publicly funding automated CT perfusion imaging in Ontario over the next 5 years would be $1.3 million in year 1 and $0.9 million each year thereafter. Some of the costs of automated CT perfusion imaging could be offset by avoiding unnecessary patient transfers between hospitals.

conclusionsAutomated CT perfusion imaging has an acceptable sensitivity and specificity for detecting brain areas that have been affected by stroke. In patients selected for mechanical thrombectomy using automated CT perfusion imaging, there was significant improvement in functional independence. Mechanical thrombectomy informed by automated CT perfusion imaging is likely to be cost-effective. We estimate that publicly funding automated CT perfusion imaging in Ontario would result in additional costs of $1.3 million in year 1 and $0.9 million per year thereafter.

Indexed as

Patient SelectionThrombectomyAgedAged, 80 and overBrainBrain IschemiaClinical Decision-MakingCost-Benefit AnalysisFemaleHumansIschemic StrokeMaleMiddle AgedOntarioPerfusion ImagingRegional Blood Flow

Identifiers

PMID33240454
PMCPMC7668535

What OpenQuestion holds

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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.