Evidence map›Paper›PMID 34877453›Full record

ArticleBJR open2021

A proposed model on MR elastography for predicting postoperative major complications in patients with hepatocellular carcinoma.

Kazu Shibutani, Masahiro Okada, Jitsuro Tsukada, Tomoko Hyodo, Kenji Ibukuro, Hayato Abe, Naoki Matsumoto, Yutaka Midorikawa, Mitsuhiko Moriyama, Tadatoshi Takayama

Open access · goldAbstract read
In one paragraph

Article in BJR open, 2021. 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 47% 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, 3 citations in OpenAlex.

  1. Article
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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

10 authors at 2 institutions in 1 country.

Kazu ShibutaniDepartment of Radiology, Nihon University School of Medicine, Tokyo, Japan.
Masahiro OkadaDepartment of Radiology, Nihon University School of Medicine, Tokyo, Japan.
Jitsuro TsukadaDepartment of Radiology, Nihon University School of Medicine, Tokyo, Japan.
Tomoko HyodoDepartment of Radiology, Kindai University school of medicine, Osaka, Japan.
Kenji IbukuroDepartment of Radiology, Nihon University School of Medicine, Tokyo, Japan.
Hayato AbeDepartment of Digestive Surgery, Nihon University School of Medicine, Tokyo, Japan.
Naoki MatsumotoDepartment of Gastroenterology and Hepatology, Nihon University School of Medicine, Tokyo, Japan.
Yutaka MidorikawaDepartment of Digestive Surgery, Nihon University School of Medicine, Tokyo, Japan.
Mitsuhiko MoriyamaDepartment of Gastroenterology and Hepatology, Nihon University School of Medicine, Tokyo, Japan.
Tadatoshi TakayamaDepartment of Digestive Surgery, Nihon University School of Medicine, Tokyo, Japan.
Nihon University · JPKindai University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop a model for predicting post-operative major complications in patients with hepatocellular carcinoma (HCC).

methodsIn all, 186 consecutive patients with pre-operative MR elastography were included. Complications were categorised using Clavien‒Dindo classification, with major complications defined as ≥Grade 3. Liver-stiffness measurement (LSM) values were measured on elastogram. The indocyanine green clearance rate of liver remnant (ICG-Krem) was based on the results of CT volumetry, intraoperative data, and ICG-K value. For an easy application to the prediction model, the continuous variables were converted to categories. Moreover, logistic regression analysis and fivefold cross-validation were performed. The prediction model's discriminative performance was evaluated using the area under the receiver operating characteristic curve (AUC), and the calibration of the model was assessed by the Hosmer‒Lemeshow test.

results43 of 186 patients (23.1%) had major complications. The multivariate analysis demonstrated that LSM, albumin-bilirubin (ALBI) score, intraoperative blood loss, and ICG-Krem were significantly associated with major complications. The median AUC of the five validation subsets was 0.878. The Hosmer-Lemeshow test confirmed no evidence of inadequate fit (

conclusionThe proposed prediction model can be used to predict post-operative major complications in patients with HCC. ADVANCES IN KNOWLEDGE: The proposed prediction model can be used in routine clinical practice to identify post-operative major complications in patients with HCC and to strategise appropriate treatments of HCC.

Identifiers

PMID34877453
PMCPMC8611681
OpenAlexW3204719459

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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.