Evidence map›Paper›PMID 39379750›Full record

Observational studyNeurocritical care2025

Contribution of an Automatic Algorithm for Quantifying the Volume of Aneurysmal Subarachnoid Hemorrhage to the Evaluation of the Risk of Occurrence of Delayed Cerebral Ischemia: A Cohort Study.

Pierre Simeone, Thomas Corrias, Nicolas Bruder, Salah Boussen, Dan Cardoso, Audrey Alonzo, Anthony Reyre, Hervé Brunel, Nadine Girard, Thomas Graillon and 3 more

Abstract readObservational Study
PubMed Publisher
In one paragraph

Observational study in Neurocritical care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

13 authors.

Pierre Simeone *Department of Anesthesiology and Critical Care Medicine, University Hospital Timone, Aix Marseille University, Marseille, France. pierre.simeone@ap-hm.fr.ORCID 0000-0002-0682-9405
Thomas Corrias *Department of Anesthesiology and Critical Care Medicine, University Hospital Timone, Aix Marseille University, Marseille, France.
Nicolas BruderDepartment of Anesthesiology and Critical Care Medicine, University Hospital Timone, Aix Marseille University, Marseille, France.
Salah BoussenDepartment of Anesthesiology and Critical Care Medicine, University Hospital Timone, Aix Marseille University, Marseille, France.
Dan CardosoDepartment of Anesthesiology and Critical Care Medicine, University Hospital Timone, Aix Marseille University, Marseille, France.
Audrey AlonzoDepartment of Anesthesiology and Critical Care Medicine, University Hospital Timone, Aix Marseille University, Marseille, France.
Anthony ReyreDepartment of Radiology, University Hospital Timone, Aix Marseille University, Marseille, France.
Hervé BrunelDepartment of Radiology, University Hospital Timone, Aix Marseille University, Marseille, France.
Nadine GirardDepartment of Radiology, University Hospital Timone, Aix Marseille University, Marseille, France.
Thomas GraillonDepartment of Neurosurgery, University Hospital Timone, Aix Marseille University, Marseille, France.
Henry DufourDepartment of Neurosurgery, University Hospital Timone, Aix Marseille University, Marseille, France.
David CouretNeurocritical Care Unit, University Hospital Saint Pierre, Réunion University, Saint Denis de La Réunion, France.
Lionel VellyDepartment of Anesthesiology and Critical Care Medicine, University Hospital Timone, Aix Marseille University, Marseille, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study focuses on aneurysmal subarachnoid hemorrhage (aSAH) with a high risk of delayed cerebral ischemia (DCI) and acute hydrocephalus (AH). The aim was to compare the performance of an automatic algorithm for quantifying the volume of intracranial blood with the reference radiological scales to predict DCI, AH, and neurological outcome.

methodsThis was a single-center retrospective observational study of a cohort of patients with aSAH. We developed an automated blood detection algorithm based on the specific density of the blood clot. The blood clot was segmented on the first brain scan (total, supratentorial, cisternal, intraventricular). The predictive value of our model was compared, using the area under the receiver operating characteristic curve (ROC

resultsWe analyzed the scans of 145 patients with aSAH. In our cohort, 51 patients (43%) had DCI and 70 patients (54%) had AH. At 3 months, 22% of patients had died and 19% had poor outcome (Glasgow Outcome Scale extended 2-4). Cisternal blood volume was significantly correlated with cisternal Hijdra scale (R

conclusionsWith no manual intervention, our algorithm performed as well as the best radiological scores in predicting the occurrence of DCI, AH, and neurological outcome.

Indexed as

AlgorithmsBrain IschemiaHydrocephalusSubarachnoid HemorrhageAdultAgedFemaleHumansMaleMiddle AgedRetrospective StudiesAcute hydrocephalusCT scanDelayed cerebral ischemiaOutcomeRadiological scoresSubarachnoid hemorrhage

Identifiers

PMID39379750

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.