Evidence map›Paper›PMID 40842545›Full record

ReviewFrontiers in medicine2025

Biomarkers to predict the severity of acute pancreatitis.

Xinwei Hao, Zimeng Wang, Xiaotong Niu, Longsong Li, Yawei Bi, Ningli Chai

Abstract readReview
In one paragraph

Review in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. 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

6 authors.

Xinwei HaoDepartment of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, China.
Zimeng WangDepartment of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, China.
Xiaotong NiuDepartment of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, China.
Longsong LiDepartment of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, China.
Yawei BiDepartment of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, China.
Ningli ChaiDepartment of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute pancreatitis (AP) is pancreatic inflammation caused by abnormal activation of trypsinogen, and moderately severe or severe acute pancreatitis (SAP) can lead to systemic inflammatory response syndrome (SIRS) and organ failure, associated with high mortality. Therefore, early prediction of the severity of acute pancreatitis is particularly important to improve patient survival rate and reduce complications. Currently, many scoring systems (e.g., Ranson scoring, etc) and classical biomarkers are available in the clinical practice, but there are still many limitations, such as low predictive value and time delay. Potential biomarkers for the prediction of SAP are still a hot topic in current research. In this review, we aim to summarize newly discovered biomarkers for the prediction of the severity of acute pancreatitis in the recent years, and provide an overview of serum markers, intestinal flora, and genetic markers. At the same time, the development of emerging detection technologies [e.g., Robust AP Identification and Diagnosis (RAPIDx) and droplet digital PCR (ddPCR)] also provides new possibilities for early prediction of SAP, allowing these biomarkers to be applied clinically.

Indexed as

acute pancreatitisbiomarkersextracellular trapsintestinal floramitochondrial DNA

Identifiers

PMID40842545
PMCPMC12364912

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Registered trials

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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.