Evidence map›Paper›PMID 39155783›Full record

ArticleJournal of Zhejiang University. Science. B2024

A novel clinical data management platform for acute pancreatitis.

Shiyin Chen, Cheng Zhang, Zhi'en Wang, Jian Zhang, Wenqiao Yu, Yanshuai Wang, Weiwei Si, Tingbo Liang, Yun Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of Zhejiang University. Science. B, 2024. 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
0cells of the map it votes in
0citing 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

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

0 citing papers in PubMed.

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

9 authors.

Shiyin ChenDepartment of Hepatobiliary and Pancreatic Surgery, Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Cheng ZhangDepartment of Hepatobiliary and Pancreatic Surgery, Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Zhi'en WangDepartment of Rehabilitation Medicine, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Jian ZhangDepartment of Hepatobiliary and Pancreatic Surgery, Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Wenqiao YuDepartment of Comprehensive Intensive Care Unit, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Yanshuai WangDepartment of Hepatobiliary and Pancreatic Surgery, Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Weiwei SiDepartment of Hepatobiliary and Pancreatic Surgery, Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Tingbo LiangDepartment of Hepatobiliary and Pancreatic Surgery, Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China. liangtingbo@zju.edu.cn.
Yun ZhangDepartment of Hepatobiliary and Pancreatic Surgery, Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China. bigzyun1977@zju.edu.cn.

Funding

the National Key Research and Development Project of China 2019YFC1316000the National Natural Science Foundation of China 81830089, 81801640, 81802359, 81871545 and 81802334
6 · The paper itself

Abstract

This study presents a multi-center clinical data management platform that facilitates unified and structured management of real-world data and serves as an ideal tool to enhance the quality and progress of clinical research related to severe acute pancreatitis (SAP). The use of the platform enables clinical teams to obtain safe, accurate, structurally unified, traceable, scene-clear, and fully functional real-world medical data in the diagnosis, treatment, and research of acute pancreatitis (AP).

Indexed as

PancreatitisAcute DiseaseData ManagementHumans

Identifiers

PMID39155783
PMCPMC11337090

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.