Evidence map›Paper›PMID 38253872›Full record

ArticleScientific reports2024

Combination of clinical information and radiomics models for the differentiation of acute simple appendicitis and non simple appendicitis on CT images.

Yinming Zhao, Xin Wang, Yaofeng Zhang, Tao Liu, Shuai Zuo, Lie Sun, Junling Zhang, Kexin Wang, Jing Liu

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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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

6 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

9 authors.

Yinming Zhao *Department of Gastrointestinal Surgery, Peking University First Hospital, Beijing, China.
Xin Wang *Department of Gastrointestinal Surgery, Peking University First Hospital, Beijing, China.
Yaofeng ZhangBeijing Smart Tree Medical Technology Co. Ltd., Beijing, China.
Tao LiuDepartment of Gastrointestinal Surgery, Peking University First Hospital, Beijing, China.
Shuai ZuoDepartment of Gastrointestinal Surgery, Peking University First Hospital, Beijing, China.
Lie SunDepartment of Gastrointestinal Surgery, Peking University First Hospital, Beijing, China.
Junling ZhangDepartment of Gastrointestinal Surgery, Peking University First Hospital, Beijing, China. junlingzhang1999@163.com.
Kexin WangSchool of Basic Medical Sciences, Capital Medical University Beijing, Beijing, China. kexin_wang@mail.ccmu.edu.cn.
Jing LiuDepartment of Radiology, Peking University First Hospital, Beijing, China. 4527322@qq.com.

Funding

Beijing Municipal Natural Science Foundation 7154246National Natural Science Foundation of China 81401932National Project for Clinical Key Specialty Development; the National Natural Science Foundation of China 81641098the Scientific Research Seed Fund of Peking University First Hospital 2018SF090the Youth Clinical Research Project of Peking University First Hospital No. 2018CR23 and 2021CR03the Youth Cultivated Research Fund of Peking University Health Center No.BMU2020PYB026
6 · The paper itself

Abstract

To investigate the radiomics models for the differentiation of simple and non-simple acute appendicitis. This study retrospectively included 334 appendectomy cases (76 simple and 258 non-simple cases) for acute appendicitis. These cases were divided into training (n = 106) and test cohorts (n = 228). A radiomics model was developed using the radiomic features of the appendix area on CT images as the input variables. A CT model was developed using the clinical and CT features as the input variables. A combined model was developed by combining the radiomics model and clinical information. These models were tested, and their performance was evaluated by receiver operating characteristic curves and decision curve analysis (DCA). The variables independently associated with non-simple appendicitis in the combined model were body temperature, age, percentage of neutrophils and Rad-score. The AUC of the combined model was significantly higher than that of the CT model (P = 0.041). The AUC of the radiomics model was also higher than that of the CT model but did not reach a level of statistical significance (P = 0.053). DCA showed that all three models had a higher net benefit (NB) than the default strategies, and the combined model presented the highest NB. A nomogram of the combined model was developed as the graphical representation of the final model. It is feasible to use the combined information of clinical and CT radiomics models for the differentiation of simple and non-simple acute appendicitis.

Indexed as

AppendicitisAppendixAcute DiseaseHumansRadiomicsRetrospective StudiesTomography, X-Ray Computed

Identifiers

PMID38253872
PMCPMC10803326

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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.