Evidence map›Paper›PMID 42662501›Full record

ArticleiScience2026

Quantifying inequalities and forecasting the burden of chronic kidney disease from 1990 to 2040.

Xian Shao, Wenyi Jin, Mingzhen Pang, Ruixuan Chen, Ting Luo, Heping Zhang, Liming Pan, Kexin Ding, Shuxian Ma, Lili Zheng and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

15 authors.

Xian ShaoDivision of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney and Urological Diseases, Nanfang Hospital, State Key Laboratory of Multi-organ Injury Prevention and Treatment, Southern Medical University, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangdong Provincial Institute of Nephrology, Guangzhou 510515, China.
Wenyi JinDepartment of Orthopaedics, Renmin Hospital of Wuhan University, Wuhan University, Wuhan 430060, China.
Mingzhen PangDivision of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney and Urological Diseases, Nanfang Hospital, State Key Laboratory of Multi-organ Injury Prevention and Treatment, Southern Medical University, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangdong Provincial Institute of Nephrology, Guangzhou 510515, China.
Ruixuan ChenDivision of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney and Urological Diseases, Nanfang Hospital, State Key Laboratory of Multi-organ Injury Prevention and Treatment, Southern Medical University, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangdong Provincial Institute of Nephrology, Guangzhou 510515, China.
Ting LuoThe Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Shanghai 200438, China.
Heping ZhangDepartment of Biostatistics, Yale University School of Public Health, New Haven, CT 06520, USA.
Liming PanSchool of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, China.
Kexin DingDepartment of Computer Science, The University of North Carolina at Charlotte, Charlotte, NC 28223, USA.
Shuxian MaDigital Services Section, Information Management Branch, United Nations Office for the Coordination of Humanitarian Affairs, 2511 BB The Hague, the Netherlands.
Lili ZhengGlobal Traditional Medicine Centre, World Health Organization, 1211 Geneva, Switzerland.
Baozhen HuangDepartment of Biomedical Sciences, City University of Hong Kong, Hong Kong 999077, China.
Pengpeng YeThe National Center for Chronic and Noncommunicable Disease Control and Prevention, the Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Sheng NieDivision of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney and Urological Diseases, Nanfang Hospital, State Key Laboratory of Multi-organ Injury Prevention and Treatment, Southern Medical University, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangdong Provincial Institute of Nephrology, Guangzhou 510515, China.
Xin XuDivision of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney and Urological Diseases, Nanfang Hospital, State Key Laboratory of Multi-organ Injury Prevention and Treatment, Southern Medical University, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangdong Provincial Institute of Nephrology, Guangzhou 510515, China.
Queran LinClinical Research Design Division, Guangdong Provincial Key Laboratory of Malignant Tumour Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Breast Tumor Center, Clinical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic kidney disease (CKD) poses a growing global health challenge. Using data from 953 locations, we analyzed spatiotemporal patterns of CKD burden, quantified disparities by inequality and frontier analysis, and developed a deep-learning model to forecast burden to 2040. Marked subnational heterogeneity was observed: a total of 76 locations experienced a doubling of age-standardized mortality rates (ASMR) since 1980, and no country achieved the health frontier level for mortality, incidence, or years of life lost. Accordingly, scenario forecasts indicate that prioritized management of high fasting plasma glucose (FPG) could yield the most substantial reduction globally, potentially lowering ASMR by 47.5% and disability-adjusted life years (DALYs) by 38.9% by 2040. Targeting high body mass index and high systolic blood pressure would also reduce DALYs by 27.6% and 26.6%, respectively, with ASMR reductions by 47.5% and 35.0%. This study provides comprehensive granular evidence on the pervasive and worsening inequalities in CKD.

Indexed as

chronic kidney diseasedeep-learning algorithmfasting plasma glucosefrontier analysisglobal burden of diseasehealth inequalitiesmortality and disability

Identifiers

PMID42662501
PMCPMC13521068

What OpenQuestion holds

Textmetadata
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.