ReviewFrontiers in stroke2023
Potential and limitations of computed tomography images as predictors of the outcome of ischemic stroke events: a review.
Review in Frontiers in stroke, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Deep Learning-Based Extraction of Biomarkers for the Prediction of the Functional Outcome of Ischemic Stroke Patients.Diagnostics (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The prediction of functional outcome after a stroke remains a relevant, open problem. In this article, we present a systematic review of approaches that have been proposed to predict the most likely functional outcome of ischemic stroke patients, as measured by the modified Rankin scale. Different methods use a variety of clinical information and features extracted from brain computed tomography (CT) scans, usually obtained at the time of hospital admission. Most studies have concluded that CT data contains useful information, but the use of this information by models does not always translate into statistically significant improvements in the quality of the predictions.
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Registered trials
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.