Evidence map›Paper›PMID 42506668›Full record

ArticleVaccines2026

Influenza Vaccine Effectiveness Against Influenza-like Illness in Post-Operative Children with Congenital Heart Disease: A Retrospective Cohort Study Using Inverse Probability of Treatment Weighting.

Rui Liu, Pengfei Deng, Tian Yang, Yun Pan, Zhuoming Xu, Laibao Yang, Caoyi Xue, Qizhang Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Vaccines, 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

8 authors.

Rui LiuSchool of Public Health, Dali University, 2 Hongsheng Road, Dali 671003, China.
Pengfei DengShanghai Pudong New Area Center for Disease Control and Prevention (Shanghai Pudong New Area Health Supervision Institute), 3039 Zhangyang Road, Pudong New Area, Shanghai 200136, China.
Tian YangShanghai Pudong New Area Center for Disease Control and Prevention (Shanghai Pudong New Area Health Supervision Institute), 3039 Zhangyang Road, Pudong New Area, Shanghai 200136, China.
Yun PanDepartment of Pediatric Cardiology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, 1678 Dongfang Road, Pudong New Area, Shanghai 200127, China.
Zhuoming XuDepartment of Pediatric Cardiology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, 1678 Dongfang Road, Pudong New Area, Shanghai 200127, China.
Laibao YangShanghai Pudong New Area Center for Disease Control and Prevention (Shanghai Pudong New Area Health Supervision Institute), 3039 Zhangyang Road, Pudong New Area, Shanghai 200136, China.
Caoyi XuePudong Institute for Health Development, 818 Laiyang Road, Pudong New Area, Shanghai 200129, China.
Qizhang WangShanghai Pudong New Area Center for Disease Control and Prevention (Shanghai Pudong New Area Health Supervision Institute), 3039 Zhangyang Road, Pudong New Area, Shanghai 200136, China.

Funding

Outstanding Young Medical Talents Training Program of Pudong New Area Health System PWRq2023-24Shanghai Pudong New Area Science and Technology Development Fund Project PKJ2023-Y34Shanghai Three-year Action Plan to Strengthen the Construction of the Public Health System Excellent Academic Leader Project (2023-2025) GWVI-11.2-XD08
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

childrencongenital heart diseasedoubly robust estimationinfluenza vaccineinverse probability of treatment weightingvaccine effectiveness

Identifiers

PMID42506668
PMCPMC13416973

What Socratic holds

Textmetadata
LicenceCC BY
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.