Evidence map›Paper›PMID 33376565›Full record

ArticlePolish journal of radiology2020

Utility of brain parenchyma density measurement and computed tomography perfusion imaging in predicting brain death.

Asli I Akdogan, Hilal Sahin, Yeliz Pekcevik, Hatice Uluer

Open access · diamondAbstract read
In one paragraph

Article in Polish journal of radiology, 2020. 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
0.2field-weighted citation impact, top 40% of its field
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, 2 citations in OpenAlex.

  1. Article
  2. Article
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

4 authors at 3 institutions in 1 country.

Asli I AkdoganDepartment of Radiology, Buca Women Birth and Child Diseases Hospital, Izmir, Turkey.
Hilal SahinDepartment of Radiology, University of Health Sciences, Tepecik Training and Research Hospital, Izmir, Turkey.
Yeliz PekcevikDepartment of Radiology, University of Health Sciences, Tepecik Training and Research Hospital, Izmir, Turkey.
Hatice UluerDepartment of Biostatistics, Ege University, Faculty of Medicine, Izmir, Turkey.
Ege University · TRIzmir University · TRSağlık Bilimleri Üniversitesi · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo assess the utility of brain parenchyma density measurement on unenhanced computed tomography (CT) in predicting brain death (BD), in order to evaluate the added value of CT perfusion (CTP). MATERIAL AND

methodsA total of 77 patients who were clinically diagnosed as BD and had both CT angiography (CTA) and CTP imaging in the same session were retrospectively reviewed. On unenhanced phase of CTA, density measurement was performed from 23 regions of interests (ROIs) which were located in the following areas: level of basal ganglia (caudate nucleus, putamen, corpus callosum, posterior limb of internal capsule), level of brainstem, grey- white matters on levels of centrum semiovale (CS), high convexity (HC), and cerebellum. CTP images were evaluated qualitatively and independently. Grey matter (GM), white matter (WM), density, and GM/WM density ratio of BD patients were compared with control subjects.

resultsComparing with the normal control group, the GM and WM density at each level and GM/WM density ratio of CS, HC, and cerebellum level were significantly lower in brain-dead patients (

conclusionsThe GM/WM density ratio at the HC level on unenhanced CT may be a useful finding to predict BD. Also, the addition of CTP increases the sensitivity of this method.

Indexed as

brain deathcomputed tomography angiographycomputed tomography perfusiondensity

Identifiers

PMID33376565
PMCPMC7757508
OpenAlexW3109979789

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.