Evidence map›Paper›PMID 35173849›Full record

ArticleAmerican journal of translational research2022

Clinical and prognostic value of CT perfusion imaging parameters in patients with primary liver cancer after therapy.

Yiming Li, Yuzhou Li, Yuan Sui, Guangyao Lin, Wenqi Huang, Yinshi Zheng

Open access · greenAbstract read
PubMed Full text at PMC
In one paragraph

Article in American journal of translational research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

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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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 1 institution in 1 country.

Yiming LiMedical Imaging Center, The First People's Hospital of Shangqiu City Shangqiu 476100, Henan Province, China.
Yuzhou LiMedical Imaging Center, The First People's Hospital of Shangqiu City Shangqiu 476100, Henan Province, China.
Yuan SuiMedical Imaging Center, The First People's Hospital of Shangqiu City Shangqiu 476100, Henan Province, China.
Guangyao LinMedical Imaging Center, The First People's Hospital of Shangqiu City Shangqiu 476100, Henan Province, China.
Wenqi HuangMedical Imaging Center, The First People's Hospital of Shangqiu City Shangqiu 476100, Henan Province, China.
Yinshi ZhengMedical Imaging Center, The First People's Hospital of Shangqiu City Shangqiu 476100, Henan Province, China.
Shangqiu First People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo explore the value of arterial enhancement fraction (AEF) of CT perfusion in evaluating the postoperative treatment efficacy on liver cancer (LC).

methodsClinical data of 60 patients with LC who were treated with transcatheter arterial chemoembolization for LC in our hospital from Jan. 2015 to Jan. 2017 were analyzed retrospectively. They underwent CT scanning before and after surgery. The change of arterial enhancement fraction (AEF) was analyzed, and its value in efficacy evaluation was assessed.

resultsAfter surgery, the AEF value of the effective group decreased greatly (P<0.05) and was significantly lower than that of the ineffective group (P<0.05). Alpha fetal protein (AFP) of both groups decreased after surgery, with a significantly lower AFP level in the effective group than that in the ineffective group (P<0.05). AEF and AFP were positively correlated. According to the follow-up results, patients with a low AEF level showed a higher survival rate than those with a high level. Cox regression analysis revealed that AEF was an independent factor for patients' prognosis.

conclusionCT perfusion imaging parameters are of high clinical value for patients with primary LC after therapy and can be used as independent factors for their prognosis.

Indexed as

arterial enhancement fractionCT perfusion imaging parametersprimary liver cancerprognosis

Identifiers

PMID35173849
PMCPMC8829621
OpenAlexW4213393429

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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.