Evidence map›Paper›PMID 38481502›Full record

ArticleKidney international reports2024

Evaluation of the Risk Prediction Models in Predicting Kidney Outcomes in Antiglomerular Basement Membrane Disease.

Huang Kuang, Yi-Yang Zhao, Jin-Wei Wang, Zhao Cui, Ming-Hui Zhao, Xiao-Yu Jia

Open access · goldAbstract read
In one paragraph

Article in Kidney international reports, 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
1.4field-weighted citation impact, top 18% of its field
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, 7 citations in OpenAlex.

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

6 authors at 1 institution in 1 country.

Huang KuangRenal Division, Peking University First Hospital, Beijing, China.
Yi-Yang ZhaoRenal Division, Peking University First Hospital, Beijing, China.
Jin-Wei WangRenal Division, Peking University First Hospital, Beijing, China.
Zhao CuiRenal Division, Peking University First Hospital, Beijing, China.
Ming-Hui ZhaoRenal Division, Peking University First Hospital, Beijing, China.
Xiao-Yu JiaRenal Division, Peking University First Hospital, Beijing, China.
Ministry of Education of the People's Republic of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: A previous study showed that the renal risk score (RRS) was transferrable to antiglomerular basement membrane (anti-GBM) disease and proposed a risk stratification according to the need of renal replacement therapy (RRT) and the percentage of normal glomeruli (N). Herein, we analyzed the risk factors associated with kidney outcomes in patients with biopsy-proven anti-GBM disease and evaluated these 2 prognosis systems. Methods: A total of 120 patients with biopsy-proven anti-GBM disease with complete clinicopathologic and outcome data were analyzed. Results: The median time to kidney biopsy was 41 days (interquartile range [IQR]: 22-63 days). RRT and N were the only independent predictors of end-stage kidney disease (ESKD). Patients with N ≥10% were more likely to achieve ESKD-free outcomes, even in the subcohort of patients who underwent posttreatment biopsies ( Conclusion: Normal glomeruli percentage, even posttreatment, was a strong indicator for kidney outcomes, especially on long-term prognosis. Serum creatinine is a predictor for kidney recovery, independent of biopsy findings. The risk stratification tool for kidney survival was transferrable to patients with anti-GBM disease with biopsy following treatment in our cohort; however, this needs further validations for long-term outcomes.

Indexed as

antiglomerular basement membrane diseasenormal glomeruliprognosisrenal replacement therapyrenal risk score

Identifiers

PMID38481502
PMCPMC10927471
OpenAlexW4389916271

What OpenQuestion 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 OpenQuestion graph.