Evidence mapPaperPMID 39717233Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2024

Construction and Evaluation of a Predictive Nomogram for Identifying Premature Failure of Arteriovenous Fistulas in Elderly Diabetic Patients.

Shuangyan Liu, Yaqing Wang, Xiaojie He, Xiaodong Li

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In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Shuangyan Liu *Graduate School of Hebei Medical University, Shijiazhuang, Hebei, 050017, People's Republic of China.
Yaqing Wang *Graduate School of Chengde Medical University, Chengde, Hebei, 067000, People's Republic of China.
Xiaojie HeGraduate School of Hebei Medical University, Shijiazhuang, Hebei, 050017, People's Republic of China.
Xiaodong LiDepartment of Nephrology, Baoding No 1 Central Hospital, Baoding, Hebei, People's Republic of China.ORCID 0000-0002-9231-4853

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This research aimed to identify risk factors contributing to premature maturation of arteriovenous fistulas (AVF) in elderly diabetic patients and develop a clinical prediction model. Methods: We conducted a retrospective review of 548 geriatric diabetic patients who underwent AVF creation for maintenance hemodialysis (MHD) at Baoding No 1 Central Hospital between January 2011 and December 2023. Patients were divided into mature (386) and immature (162) groups based on AVF maturation status. Univariate logistic regression analysis and the least absolute shrinkage and selection operator were used to identify independent risk factors, including D-dimer levels, low-density lipoprotein cholesterol levels, internal radial meridian, radial artery plaque presence, and cephalic vein indwelling needle use history. A predictive nomogram was developed specifically for immature AVF in elderly diabetic patients. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC). Results: Among elderly patients with diabetes mellitus, the incidence of immature AVF was 29.56%, affecting 162 of 548 individuals. The five-variable model demonstrated an AUROC value of 0.922, with a 95% confidence interval (CI) of 0.870 to 0.947 in the training dataset, and an AUROC of 0.912, accompanied by a 95% CI of 0.880 to 0.935 in the internal validation dataset. The calibration curve, derived from 1000 bootstrap samples, showed good agreement between predicted and observed outcomes. Additionally, both the DCA and CIC exhibited favorable clinical utility and net benefits. Conclusions: The nomogram prediction model, based on independent risk factors, serves as a valuable tool for accurate prognosis and has potential to aid in establishing and preserving hemodialysis access in elderly diabetic patients, ultimately optimizing their healthcare outcomes.

Indexed as

arteriovenous fistuladiabeteshemodialysisnomogramvascular access

Identifiers

PMID39717233
PMCPMC11665172

What Socratic holds

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Registered trials

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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 Socratic graph.