Evidence map›Paper›PMID 37119293›Full record

ArticleAbdominal radiology (New York)2023

The added value of

Jing Lv, Hongyan Yin, Haojun Yu, Hongcheng Shi

Abstract read
PubMed Publisher
In one paragraph

Article in Abdominal radiology (New York), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 21% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. 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 1 institution in 1 country.

Jing LvDepartment of Nuclear Medicine, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
Hongyan YinDepartment of Nuclear Medicine, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
Haojun YuDepartment of Nuclear Medicine, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
Hongcheng ShiDepartment of Nuclear Medicine, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China. shi.hongcheng@zs-hospital.sh.cn.ORCID http://orcid.org/0000-0003-1922-1359
Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIn hepatocellular carcinoma (HCC), cytokeratin 19(CK19) has been proven to be associated with clinical aggressiveness. Therefore, this study aimed to explore the added value of

methodsSixty-six patients who underwent whole-body or abdominal

resultsThe areas under the ROC curve (AUCs) for T-SUVmax, SUVmax-T/L, T-ADCmean, and ADCmean-T/L in predicting the CK19-positive HCC were 0.700, 0.717, 0.717, and 0.735, respectively. In the logistic regression analysis, the T-SUVmax was an independent and significant factor to predict CK19-positive HCC, with an odds ratio of 1.27. In addition, no significant differences were found in the pathological grading, microvascular invasion, liver capsular invasion, Hepatitis B virus (HBV) infection, alpha fetoprotein (AFP) level, and tumor diameter between the CK19-positive and CK19-negative groups, except the recurrent rate.

conclusionsThe radiomic features derived from

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsFluorodeoxyglucose F18HumansKeratin-19Magnetic Resonance ImagingPositron-Emission TomographyPositron Emission Tomography Computed TomographyRadiopharmaceuticalsRetrospective StudiesFluorodeoxyglucose F18Keratin-19KRT19 protein, humanRadiopharmaceuticals18F-FDG PET/MRIADCmeanCytokeratin 19Hepatocellular carcinomaSUVmax

Identifiers

PMID37119293
OpenAlexW4367368947

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.