Evidence map›Paper›PMID 38862943›Full record

ArticlePediatric rheumatology online journal2024

Clinical features and recurrence predictors of histiocytic necrotizing lymphadenitis in Chinese children.

Xiaoning Zhang, Xiuhong Jin, Xiangfeng Zhang, Yuelin Shen

Abstract read
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Article in Pediatric rheumatology online journal, 2024. 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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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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

4 authors.

Xiaoning ZhangRespiratory Department, Children's Hospital Affiliated to Zhengzhou University, Henan Children's hospital, Zhengzhou Children's Hospital, Zhengzhou, 450008, China.
Xiuhong JinRespiratory Department, Children's Hospital Affiliated to Zhengzhou University, Henan Children's hospital, Zhengzhou Children's Hospital, Zhengzhou, 450008, China.
Xiangfeng ZhangRespiratory Department, Children's Hospital Affiliated to Zhengzhou University, Henan Children's hospital, Zhengzhou Children's Hospital, Zhengzhou, 450008, China.
Yuelin ShenRespiratory Department II, National Clinical Research Center for Respiratory Diseases, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, NO.56, Nanlishi Road, Beijing, 100045, China. shenyuelin@hotmail.com.ORCID http://orcid.org/0009-0007-3206-610X

Funding

National Regional Medical Center Opening Project NRMC0107
6 · The paper itself

Abstract

objectivesTo characterize the clinical features and to identify the predictors of recurrence of histiocytic necrotizing lymphadenitis (HNL) in Chinese children. STUDY

designThis study retrospectively analyzed the clinical characteristics, laboratory and pathological findings, and recurrence status of children diagnosed with HNL at a single center in China from January 2018 to May 2023. Logistic regression analysis was employed to identify predictors of HNL recurrence.

results181 Chinese children with histopathologically confirmed HNL were enrolled (121 males and 60 females). The mean age was 9.3 ± 2.9 years. The most prominent clinical features were fever (98.9%) and cervical lymphadenopathy (98.3%). Aseptic meningitis was the most frequent complication (38.5%), while hemophagocytic lymphohistiocytosis and autoimmune disease were rare (1.7% and 1.2%, respectively). Recurrence occurred in 12.7% of patients. Erythrocyte sedimentation rate (> 30 mm/h) was the significant predictors of HNL recurrence, with odds ratios of 6.107, respectively.

conclusionOur study demonstrates that fever and cervical lymphadenopathy are the most frequent clinical manifestations of HNL in Chinese children, which often coexist with aseptic meningitis. HNL patients with risk factors require follow-up for recurrence.

Indexed as

Histiocytic Necrotizing LymphadenitisRecurrenceAdolescentChildChild, PreschoolChinaEast Asian PeopleFemaleFeverHumansLymphadenopathyMaleMeningitis, AsepticRetrospective StudiesRisk FactorsChinese childrenClinical featuresHistiocytic necrotizing lymphadenitisKikuchi-Fujimoto diseaseRecurrence

Identifiers

PMID38862943
PMCPMC11167820

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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.