Evidence map›Paper›PMID 39081277›Full record

ArticleJournal of translational internal medicine2024

Nomogram for predicting risk of mild renal dysfunction among general residents from rural Northeast China.

Shasha Yu, Hongmei Yang, Bo Wang, Xiaofan Guo, Guangxiao Li, Yingxian Sun

Abstract read
In one paragraph

Article in Journal of translational internal medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  9. Observational
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

6 authors.

Shasha YuDepartment of Cardiology, First Hospital of China Medical University, Shenyang 110001, Liaoning Province, China.
Hongmei YangDepartment of Cardiology, First Hospital of China Medical University, Shenyang 110001, Liaoning Province, China.
Bo WangDepartment of Cardiology, First Hospital of China Medical University, Shenyang 110001, Liaoning Province, China.
Xiaofan GuoDepartment of Cardiology, First Hospital of China Medical University, Shenyang 110001, Liaoning Province, China.
Guangxiao LiDepartment of Clinical Epidemiology, Institute of Cardiovascular Diseases, First Hospital of China Medical University, Shenyang 110001, Liaoning Province, China.
Yingxian SunDepartment of Cardiology, First Hospital of China Medical University, Shenyang 110001, Liaoning Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objectives: Cumulative evidence confirms that mild renal dysfunction (MRD) is correlated with many cardiovascular risk factors and increases cardiovascular morbidity and mortality. The purpose of this study was to establish an effective nomogram for predicting the risk of MRD in the rural population of Northeast China. Methods: We analyzed the reports of 4944 subjects from the Northeast China Rural Cardiovascular Health Study (NCRCHS). All the participants completed the questionnaires, anthropometric measurements, and blood tests during the baseline study (2012-2013) and the follow-up study during 2015-2017 (an average of 4.6 years). The Chronic Kidney Disease Epidemiology (CKD-EPI) equation was used to calculate the estimated glomerular filtration rate (eGFR), and eGFR in the range of 60-90 mL/min/1.73m2 was defined as MRD. Results: The study revealed that a total of 889 subjects (18.0%) had MRD. Multivariate logistic analysis showed that annual income, abdominal obesity, hypertension, hyperglycemia, and frequent tea consumption were the independent risk factors ( Conclusion: We constructed a nomogram based on epidemiological data, which could provide an individual prediction of MRD with good accuracy.

Indexed as

epidemiologyestimated glomerular filtration ratemild renal dysfunctionpredictionrural

Identifiers

PMID39081277
PMCPMC11284527

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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.