Evidence map›Paper›PMID 39593231›Full record

ArticleRenal failure2024

Inflammation-based scores predict chronic kidney disease progression in patients with chronic kidney disease and chronic heart failure.

Lu Cai, Licong Su, Ying Hu, Endi Cai, Hong Xu, Bicheng Liu, Jianping Weng, Chunbo Chen, Huafeng Liu, Qiongqiong Yang and 11 more

Abstract read
In one paragraph

Article in Renal failure, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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

21 authors.

Lu CaiDepartment of Nephrology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Licong SuDivision of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangdong Provincial Institute of Nephrology, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, China.
Ying HuDepartment of Nephrology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Endi CaiDigital Health China Technologies Co., Ltd, Beijing, China.
Hong XuChildren's Hospital of Fudan University, Shanghai, China.
Bicheng LiuInstitute of Nephrology, Zhongda Hospital, Southeast University School of Medicine, Nanjing, China.
Jianping WengDepartment of Endocrinology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
Chunbo ChenDepartment of Critical Care Medicine, Maoming People's Hospital, Maoming, China.
Huafeng LiuKey Laboratory of Prevention and Management of Chronic Kidney Disease of Zhanjiang City, Institute of Nephrology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
Qiongqiong YangDepartment of Nephrology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Hua LiSir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Yaozhong KongDepartment of Nephrology, the First People's Hospital of Foshan, Foshan, Guangdong, China.
Guisen LiRenal Department and Institute of Nephrology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Sichuan Clinical Research Center for Kidney Diseases, Chengdu, China.
Qijun WanThe Second People's Hospital of Shenzhen, Shenzhen University, Shenzhen, China.
Yan ZhaGuizhou Provincial People's Hospital, Guizhou University, Guiyang, China.ORCID 0000-0002-1185-455X
Gang XuDivision of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yongjun ShiHuizhou Municipal Central Hospital, Sun Yat-Sen University, Huizhou, China.
Yilun ZhouDepartment of Nephrology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Guobin SuDepartment of Nephrology, Guangdong Provincial Hospital of Chinese Medicine, The Second Affiliated Hospital, The Second Clinical College, Guangzhou University of Chinese Medicine, Guangzhou, China.
Ying TangThe Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
Mengchun GongDigital Health China Technologies Co., Ltd, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInflammation is associated with adverse outcomes of chronic kidney disease (CKD) or chronic heart failure (CHF), but few large data exist. We aimed to explore the clinical associations, and prognostic consequences of inflammation-based scores in patients with CKD and CHF.

methodsThis work was a retrospective cohort study. Glasgow Prognostic Score (GPS), modified Glasgow Prognostic Score (mGPS), Prognostic Nutritional Index (PNI) and Prognostic Index (PI), were used to explore its relationship with CKD progression in patients with CKD stage 1-3b and CHF from the China Renal Data System (CRDS). The composite end point of this study was CKD progression which was defined as eGFR reduction of 40% or progression to end stage renal disease (ESRD).

resultsOf 8491 patients were enrolled. Kaplan-Meier curve showed that compared to the lower inflammation-based scores, the increased scores have a higher rate of CKD progression, whether in GPS, mGPS, PNI or PI (log-rank test,

conclusionsInflammation-based scores, especially PNI may be a useful clinical biomarker for CKD progression in CKD with CHF patients.

Indexed as

Disease ProgressionHeart FailureInflammationRenal Insufficiency, ChronicAgedChinaFemaleGlomerular Filtration RateHumansKaplan-Meier EstimateMaleMiddle AgedNutrition AssessmentPrognosisProportional Hazards ModelsRetrospective Studieschronic heart failurechronic kidney diseaseInflammation-based scoresprognosis

Identifiers

PMID39593231
PMCPMC11610343

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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.