Evidence map›Paper›PMID 34579654›Full record

ArticleBMC nephrology2021

Nomogram predicting the risk of three-year chronic kidney disease adverse outcomes among East Asian patients with CKD.

Huizhen Ye, Youyuan Chen, Peiyi Ye, Yu Zhang, Xiaoyi Liu, Guanqing Xiao, Zhe Zhang, Yaozhong Kong, Gehao Liang

Abstract readValidation Study
In one paragraph

Article in BMC nephrology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Trial
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

9 authors.

Huizhen Ye *Nephrology Department, The First People's Foshan Hospital, Foshan, Guangdong, China.
Youyuan Chen *Nephrology Department, The First People's Foshan Hospital, Foshan, Guangdong, China.
Peiyi Ye *Nephrology Department, The First People's Foshan Hospital, Foshan, Guangdong, China.
Yu ZhangNephrology Department, The First People's Foshan Hospital, Foshan, Guangdong, China.
Xiaoyi LiuNephrology Department, The First People's Foshan Hospital, Foshan, Guangdong, China.
Guanqing XiaoNephrology Department, The First People's Foshan Hospital, Foshan, Guangdong, China.
Zhe ZhangNephrology Department, The First People's Foshan Hospital, Foshan, Guangdong, China.
Yaozhong KongNephrology Department, The First People's Foshan Hospital, Foshan, Guangdong, China. kyzhong@fsyyy.com.ORCID 0000-0002-9178-6023
Gehao LiangDepartment of Breast Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China. lianggh@sysucc.org.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic kidney disease (CKD) is a common health challenge. There are some risk models predicting CKD adverse outcomes, but seldom focus on the Mongoloid population in East Asian. So, we developed a simple but intuitive nomogram model to predict 3-year CKD adverse outcomes for East Asian patients with CKD.

methodsThe development and internal validation of prediction models used data from the CKD-ROUTE study in Japan, while the external validation set used data collected at the First People's Hospital of Foshan in southern China from January 2013 to December 2018. Models were developed using the cox proportional hazards model and nomogram with SPSS and R software. Finally, the model discrimination, calibration and clinical value were tested by R software.

resultsThe development and internal validation data-sets included 797 patients (191 with progression [23.96%]) and 341 patients (89 with progression [26.10%]), respectively, while 297 patients (108 with progression [36.36%]) were included in the external validation data set. The nomogram model was developed with age, eGFR, haemoglobin, blood albumin and dipstick proteinuria to predict three-year adverse-outcome-free probability. The C-statistics of this nomogram were 0.90(95% CI, 0.89-0.92) for the development data set, 0.91(95% CI, 0.89-0.94) for the internal validation data set and 0.83(95% CI, 0.78-0.88) for the external validation data-set. The calibration and decision curve analyses were good in this model.

conclusionThis visualized predictive nomogram model could accurately predict CKD three-year adverse outcomes for East Asian patients with CKD, providing an easy-to-use and widely applicable tool for clinical practitioners.

Indexed as

NomogramsAgedAsia, EasternDatasets as TopicDisease ProgressionFemaleHumansMalePrognosisRenal Insufficiency, Chronic3-year adverse-outcome-free probabilityCKD progressionEast Asian patients with CKDNomogram

Identifiers

PMID34579654
PMCPMC8477525

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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.