ReviewStroke (Hoboken, N.J.)2024
Clinical Scales in Aneurysm Rupture Prediction.
Review in Stroke (Hoboken, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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
9 citing papers in PubMed.
- Estimating Rupture Risk of Intracranial Aneurysms: What We Know, What We Do Not Know, and What We Need.Stroke · 2026Review
- Article
- Review
- There Is Poor Agreement between the Subjective and Quantitative Adjudication of Aneurysm Wall Enhancement.AJNR. American journal of neuroradiology · 2025Article
- Radiomics-Based Predictive Nomogram for Assessing the Risk of Intracranial Aneurysms.Translational stroke research · 2025Article
- Machine Learning-Based Prediction of Clinical Outcomes in Microsurgical Clipping Treatments of Cerebral Aneurysms.Diagnostics (Basel, Switzerland) · 2024Article
- Radiomics-Based Predictive Nomogram for Assessing the Risk of Intracranial Aneurysms.Research square · 2024Article
- Retrospective Application of Risk Scores to Unruptured Anterior Communicating Artery Aneurysms.Journal of clinical medicine · 2024Article
- Advancements in Machine Learning for Cerebral Aneurysm Detection: Progress at a Steady Pace.Stroke (Hoboken, N.J.) · 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rate of incidentally discovered unruptured intracranial aneurysms has increased with the broad availability of neuroimaging. The determination of the risk of rupture of brain aneurysms is challenging. Several clinical scales for aneurysm rupture prediction have been developed. The most common scales are PHASES, ELAPSS, and UIATS. These scales are not routinely used in clinical practice due to inherent shortcomings. In this review, we analyze the risk factors used in generating these scales and the performance of these scales in clinical studies. We also discuss new potential biomarkers and tools to predict aneurysm rupture.
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What OpenQuestion holds
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.