Evidence map›Paper›PMID 38860211›Full record

ReviewPeerJ2024

Research advances in predicting the expansion of hypertensive intracerebral hemorrhage based on CT images: an overview.

Min Ai, Hanghang Zhang, Junbang Feng, Hongying Chen, Di Liu, Chang Li, Fei Yu, Chuanming Li

Abstract readReview
In one paragraph

Review in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

8 authors.

Min Ai *Department of Anesthesiology, Nanan District People's Hospital of Chongqing, Chongqing, China.
Hanghang Zhang *Department of Breast and Thyroid Surgery, Chongqing Bishan District Maternal and Child Health Care Hospital, Chongqing, China.
Junbang FengMedical Imaging Department, Chongqing University Central Hospital (Chongqing Emergency Medical Center), Chongqing, China.
Hongying ChenMedical Imaging Department, Chongqing University Central Hospital (Chongqing Emergency Medical Center), Chongqing, China.
Di LiuDepartment of Anesthesiology, Nanan District People's Hospital of Chongqing, Chongqing, China.
Chang LiMedical Imaging Department, Chongqing University Central Hospital (Chongqing Emergency Medical Center), Chongqing, China.
Fei YuMedical Imaging Department, Chongqing University Central Hospital (Chongqing Emergency Medical Center), Chongqing, China.
Chuanming LiMedical Imaging Department, Chongqing University Central Hospital (Chongqing Emergency Medical Center), Chongqing, China.

Funding

Chongqing Health Commission and Science and Technology BureauFundamental Research Funds for the Central Universities of ChinaNatural Science Foundation Project of Chongqing
6 · The paper itself

Abstract

Hematoma expansion (HE) is an important risk factor for death or poor prognosis in patients with hypertensive intracerebral hemorrhage (HICH). Accurately predicting the risk of HE in patients with HICH is of great clinical significance for timely intervention and improving patient prognosis. Many imaging signs reported in literatures showed the important clinical value for predicting HE. In recent years, the development of radiomics and artificial intelligence has provided new methods for HE prediction with high accuracy. Therefore, this article reviews the latest research progress in CT imaging, radiomics, and artificial intelligence of HE, in order to help identify high-risk patients for HE in clinical practice.

Indexed as

Intracranial Hemorrhage, HypertensiveTomography, X-Ray ComputedArtificial IntelligenceHematomaHumansPrognosisArtificial intelligenceHematoma expansionHypertensive intracerebral hemorrhageImaging signsRadiomics

Identifiers

PMID38860211
PMCPMC11164062

What OpenQuestion holds

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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.