Evidence map›Paper›PMID 41018786›Full record

ArticleFrontiers in public health2025

Evaluating disease burden in chronic kidney disease screening using a micro-simulation model.

Yang Li, Yuqin Ma, Pei Liu, Ping Xu, Guangfeng Duan

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. 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

5 authors.

Yang Li *Department of Health Service Management, Faculty of Health Service, Naval Medical University, Shanghai, China.
Yuqin Ma *Department of Health Service Management, Faculty of Health Service, Naval Medical University, Shanghai, China.
Pei Liu *Department of Mathematics and Physics, Naval Medical University, Shanghai, China.
Ping XuDepartment of Health Service Management, Faculty of Health Service, Naval Medical University, Shanghai, China.
Guangfeng DuanDepartment of Health Service Management, Faculty of Health Service, Naval Medical University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Chronic kidney disease (CKD) has a high prevalence, poor prognosis, and high medical costs, and awareness of the disease is low. Therefore, in this study, we aimed to simulate and analyze the evolution of CKD burden among different groups at high risk of CKD in Shanghai, with or without screening intervention, and provide a quantifiable basis for the selection of screening intervention strategies for CKD. Methods: A micro-simulation model was constructed to analyze the evolution of CKD burden using data from CKD screening of the population in the Jing'an and Minhang Districts of Shanghai, China, from January 2015 to December 2020. SAS Statistical Software 9.4 was used to simulate and analyze the evolution of disease burden under different screening intervention strategies. Results: By 2033, screening interventions for high-risk groups with hypertension, diabetes, and an age of 65 years and older would be associated with 6,250 fewer patients with end-stage renal disease. Furthermore, the number of patients with end-stage renal disease would be reduced to only 41.64% of the projected number of patients without screening intervention, leading to a general improvement in the quality of life of the population, better quality-adjusted life-years, and a reduction in the economic burden of disease. Discussion: The results of this study highlight the importance of combining the concepts of integrated prevention and treatment of chronic diseases to improve screening and intervention of CKD for people with hypertension, diabetes, and those aged 65 years and older, thereby effectively reducing the number of patients with end-stage renal disease, lowering the cost of treatment and intervention, and improving the quality of life of the population.

Indexed as

Cost of IllnessMass ScreeningRenal Insufficiency, ChronicAdultAgedChinaComputer SimulationFemaleHumansMaleMiddle AgedPrevalenceQuality-Adjusted Life YearsQuality of LifeRisk Factorschronic renal insufficiencycost of illnessdisease burdenmicro-simulationscreening interventions

Identifiers

PMID41018786
PMCPMC12463892

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.