Evidence map›Paper›PMID 39192601›Full record

SynthesisRenal failure2024

Long-term renal survival in patients with IgA nephropathy: a systematic review.

Huijian Zhang, Song Ren, Jieqiang Hu, Guisen Li

Abstract readSystematic Review
In one paragraph

Synthesis in Renal failure, 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

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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
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

4 authors.

Huijian ZhangRenal Department, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Song RenRenal Department, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Jieqiang HuRenal Department, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Guisen LiRenal Department, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The management strategy for IgA nephropathy (IgAN), has undergone constant improvements since the disease entity was first described 50 years ago. However, it is still unknown how these changes affected the long-term renal survival of IgAN patients. We systematically evaluate changes in IgAN renal survival by searching PubMed, Embase, and the Cochrane Library Database of Systematic Reviews from inception to 19 May 2024. We included a large sample of 103076 IgAN cases from 158 studies. Renal survival rates were 94.16% (95% CI: 94.02% to 94.31%), 88.68% (95% CI: 88.48% to 88.87%), and 78.13% (95% CI: 77.82% to 78.43%) at three, five, and ten-year, respectively. Over the past few decades, there haven't been any sound changes in the 3-year and 5-year renal survival rates. The kidney survival rate in developed countries is higher than in developing countries. Researchers consistently show that while proteinuria < 1.0 g/24 h, renal survival rates increase dramatically. In IgAN, long-term renal survival fluctuated rather than continuously improving over time. Our system review's findings indicate that supportive care-the most important recommendation for managing IgAN has shown promising results. The long-term outcomes of IgAN could be significantly improved by the latest developed treatment options.

Indexed as

Glomerulonephritis, IGAHumansProteinuriaSurvival RateIgA nephropathylong-term outcomesrenal survivalsystematic review

Identifiers

PMID39192601
PMCPMC11360644

What OpenQuestion holds

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Registered trials

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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.