Evidence map›Paper›PMID 41998547›Full record

ArticleBMC pediatrics2026

IL-10, IL-17A, and IFN-γ as clinical early-warning indicators for severe Epstein-Barr virus-associated infectious mononucleosis in children.

Yingying Ye, Meng Cao, Yuewen Su, Weifang Zhou, Yuqin Li

Abstract read
In one paragraph

Article in BMC pediatrics, 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
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

5 authors.

Yingying Ye *Department of Infectious Diseases, Children's Hospital of Soochow University, No. 303, Jingde Road, Suzhou, China.
Meng Cao *Department of Infectious Diseases, Children's Hospital of Soochow University, No. 303, Jingde Road, Suzhou, China.
Yuewen SuDepartment of Infectious Diseases, Children's Hospital of Soochow University, No. 303, Jingde Road, Suzhou, China.
Weifang ZhouDepartment of Infectious Diseases, Children's Hospital of Soochow University, No. 303, Jingde Road, Suzhou, China. zwf_1969@163.com.
Yuqin LiDepartment of Infectious Diseases, Children's Hospital of Soochow University, No. 303, Jingde Road, Suzhou, China. liyuqin9004@126.com.

Funding

The Suzhou Clinical Key Disease Diagnosis and Treatment Technology Special Project LCZX202313
6 · The paper itself

Abstract

backgroundThis study aimed to assess the predictive value of plasma interleukin-17 A (IL-17 A), interleukin-10 (IL-10), interferon-γ (IFN-γ), along with laboratory parameters and clinical manifestations, for identifying severe illness in children with Epstein-Barr virus (EBV)-induced infectious mononucleosis (IM).

methodsPeripheral blood samples were collected from 90 children diagnosed with EBV-induced IM. The patients were divided into a non-severe group (n = 66) and a severe group (n = 24). Plasma levels of IL-17 A, IL-10, and IFN-γ were measured using enzyme-linked immunosorbent assay (ELISA). Using severe EBV-IM as the outcome, the clinical characteristics, laboratory parameters, immune function markers, and expression levels of three cytokines were first compared between the two groups. Indicators with a P value of less than 0.05 in the univariable analysis were selected using stepwise regression and included in the binary logistic regression analysis. The independent risk factors identified by the regression model were used to construct a nomogram. Internal validation was performed using the bootstrap resampling method. Calibration of the model was assessed using a calibration curve, and the clinical net benefit was evaluated through decision curve analysis (DCA).

resultsBinary logistic regression analysis identified IL-10, IL-17 A, Aspartate aminotransferase (AST), Glutamyl transpeptidase (GGT), and splenomegaly as independent risk factors for severe EBV-IM (P < 0.05). A nomogram was constructed by incorporating the significant predictors from the logistic regression analysis: IL-10, IL-17 A, AST, GGT, and splenomegaly. Internal validation using the Bootstrap resampling method indicated good discriminative ability of the model. The calibration curve suggested satisfactory agreement between predicted and observed probabilities. Furthermore, DCA confirmed the favorable clinical net benefit of this predictive model.

conclusionThe nomogram incorporating IL-10, IL-17 A, AST, GGT, and splenomegaly demonstrates substantial diagnostic value for identifying severe IM.

Indexed as

Infectious MononucleosisInterferon-gammaInterleukin-10Interleukin-17BiomarkersChildChild, PreschoolEnzyme-Linked Immunosorbent AssayFemaleHerpesvirus 4, HumanHumansMaleNomogramsPredictive Value of TestsSeverity of Illness IndexBiomarkersIL10 protein, humanIL17A protein, humanInterferon-gammaInterleukin-10Interleukin-17IFN-γIL-10IL-17AInfectious mononucleosisSevere

Identifiers

PMID41998547
PMCPMC13217798

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.