Evidence map›Paper›PMID 42190692›Full record

ArticleJournal of Korean medical science2026

The SHIPE Index: A Tertile-Based Approach to Predict End-Stage Kidney Disease in ANCA-Associated Vasculitis.

Hyunsue Do, Lucy Eunju Lee, Jang Woo Ha, Jason Jungsik Song, Yong-Beom Park, Sang-Won Lee

Abstract read
In one paragraph

Article in Journal of Korean medical science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Hyunsue Do *Division of Rheumatology, Department of Internal Medicine, Kangwon National University School of Medicine, Chuncheon, Korea.ORCID https://orcid.org/0000-0002-9550-1048
Lucy Eunju Lee *Division of Rheumatology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-0897-661X
Jang Woo HaDivision of Rheumatology, Department of Internal Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Korea.ORCID https://orcid.org/0000-0002-3307-5215
Jason Jungsik SongDivision of Rheumatology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-0662-7704
Yong-Beom ParkDivision of Rheumatology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-4695-8620
Sang-Won LeeDivision of Rheumatology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-8038-3341

Funding

Eisai Korea Inc. 4-2024-0700Samsung Bioepis Co., Ltd. 4-2025-1066Yuhan Corporation 4-2025-0044
6 · The paper itself

Abstract

backgroundThis study aimed to develop a simple, robust, and ethnoregion-specific index for predicting progression to end-stage kidney disease (ESKD) in Korean patients with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV).

methodsBaseline data from 239 Korean patients with AAV enrolled in a tertiary hospital cohort were analyzed to identify independent predictors of ESKD using univariable and multivariable Cox proportional hazards models. The SHIPE (Summation of the Highest tertiles of Independent Predictors of ESKD) index was constructed by summing the highest tertiles of the identified predictors: Five-Factor Score (≥ 2) and serum creatinine (≥ 1.3 mg/dL), with 1 point assigned to each criterion met. Cumulative ESKD-free survival rates across SHIPE index scores were compared using Kaplan-Meier analysis.

resultsA SHIPE index score of 2 was significantly associated with lower cumulative ESKD-free survival rate compared to scores of 0 or 1 (

conclusionThe SHIPE index is a novel, robust, and convenient tool for predicting ESKD progression in Korean patients with AAV. This study introduces a practical framework for developing tailored prediction indices that can be adapted for diverse ethnic and regional populations. Its simplicity and practical applicability make it well-suited for routine clinical use. Future prospective studies are needed to validate the SHIPE index in larger, multi-ethnic cohorts and ensure its broader applicability.

Indexed as

Anti-Neutrophil Cytoplasmic Antibody-Associated VasculitisKidney Failure, ChronicAgedCreatinineDisease ProgressionFemaleHumansKaplan-Meier EstimateMaleMiddle AgedPrognosisProportional Hazards ModelsRisk FactorsCreatinineANCA-Associated VasculitisBiomarkersEnd-Stage Kidney DiseasePrognosisRisk Assessment

Identifiers

PMID42190692
PMCPMC13213018

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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.