Evidence map›Paper›PMID 36061380›Full record

ArticleFrontiers in pediatrics2022

Risk assessment and prediction model of renal damage in childhood immunoglobulin A vasculitis.

Ruqian Fu, Manqiong Yang, Zhihui Li, Zhijuan Kang, Mai Xun, Ying Wang, Manzhi Wang, Xiangyun Wang

Abstract readCase Reports
In one paragraph

Article in Frontiers in pediatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Ruqian FuAcademy of Pediatrics of University of South China, Changsha, China.
Manqiong YangDepartment of Pediatrics, Hunan Provincial People's Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, China.
Zhihui LiAcademy of Pediatrics of University of South China, Changsha, China.
Zhijuan KangAcademy of Pediatrics of University of South China, Changsha, China.
Mai XunDepartment of Nephrology and Rheumatology of Hunan Children's Hospital, Changsha, China.
Ying WangDepartment of Pediatrics of Changsha Central Hospital, Changsha, China.
Manzhi WangDepartment of Pediatrics of Changsha Central Hospital, Changsha, China.
Xiangyun WangDepartment of Pediatrics of Changsha First People's Hospital, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To explore the risk factors for renal damage in childhood immunoglobulin A vasculitis (IgAV) within 6 months and construct a clinical model for individual risk prediction. Methods: We retrospectively analyzed the clinical data of 1,007 children in our hospital and 287 children in other hospitals who were diagnosed with IgAV. Approximately 70% of the cases in our hospital were randomly selected using statistical product service soltions (SPSS) software for modeling. The remaining 30% of the cases were selected for internal verification, and the other hospital's cases were reviewed for external verification. A clinical prediction model for renal damage in children with IgAV was constructed by analyzing the modeling data through single-factor and multiple-factor logistic regression analyses. Then, we assessed and verified the degree of discrimination, calibration and clinical usefulness of the model. Finally, the prediction model was rendered in the form of a nomogram. Results: Age, persistent cutaneous purpura, erythrocyte distribution width, complement C Conclusion: The prediction model has a good degree of discrimination, calibration and clinical usefulness. Either the internal or external verification has better clinical efficacy, indicating that the model has repeatability and portability. Clinical trial registration: www.chictr.org.cn, identifier ChiCTR2000033435.

Indexed as

childrenclinical predictive modelimmunoglobulin vasculitisnomogramrenal damage

Identifiers

PMID36061380
PMCPMC9428464

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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.