Evidence map›Paper›PMID 42088158›Full record

ArticleInternational journal of general medicine2026

CLEC4D as an Effective Indicator for Assessing Severity of Illness in Critically Ill Patients: A Prospective Study.

Guangjian Wang, Zhimao Li, Xinyue Zhao, Xiaoru Wang, Hui Lian, Yecheng Liu

Abstract read
In one paragraph

Article in International journal of general medicine, 2026. 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
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0citing papers in PubMed
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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

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

6 authors.

Guangjian Wang *Department of Health Care, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
Zhimao Li *Emergency Department, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
Xinyue ZhaoDepartment of Health Care, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
Xiaoru WangDepartment of Critical Care Medicine, The Second Hospital of Shanxi Medical University, Shanxi, People's Republic of China.
Hui LianDepartment of Health Care, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
Yecheng LiuEmergency Department, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Accurate assessment of illness severity is crucial in critically ill patients. The APACHE II score is widely used but complex and fails to reflect underlying immune-inflammatory dysregulation. C-type lectin domain family 4 member D (CLEC4D), a pattern recognition receptor on myeloid cells, is pivotal in immune responses. We investigated whether circulating CLEC4D levels could serve as a novel biomarker for severity of illness. Methods: 368 adult ICU patients were enrolled. Serum CLEC4D levels, APACHE II scores, and immune-inflammatory parameters were measured within 24 hours of admission. Associations were analyzed using generalized additive models and multiple linear regression. Results: Patients with high APACHE II scores (≥16) exhibited significantly elevated CLEC4D levels compared with those with lower scores (344.20 ± 65.75 pg/mL vs. 321.28 ± 73.31 pg/mL, Conclusion: Circulating CLEC4D levels positively correlate with APACHE II scores in critically ill patients, potentially associated with dynamic shifts in immune-inflammatory markers. CLEC4D represents a promising biomarker for assessing illness severity, especially in sepsis.

Indexed as

APACHE IIbiomarkerCLEC4Dcritically ill patientsimmune-inflammationseverity of illness

Identifiers

PMID42088158
PMCPMC13138305

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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.