Evidence map›Paper›PMID 42851381›Full record

ArticleFrontiers in nutrition2026

Cholesterol-modified prognostic nutritional index: a novel nutritional biomarker for prevalent diabetic retinopathy in patients with type 2 diabetes mellitus.

Shimeng Huang, Li Wang, Cong Zhang, Ruoxuan Zheng, Xiaotong Sun, Jingjing Li, Kexin Cui, Yihan Wang, Rui Hou, Siyu Dong and 5 more

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

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

15 authors.

Shimeng HuangDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Li WangDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Cong ZhangDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Ruoxuan ZhengDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Xiaotong SunDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Jingjing LiDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Kexin CuiDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Yihan WangDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Rui HouDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Siyu DongDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Shuang WuDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Tianpeng ZhangDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Xinyu ZhangDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Chengye XuDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Hongyu KuangDepartment of Endocrinology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To investigate the association and dose-response relationship between the cholesterol-modified prognostic nutritional index (CPNI) and diabetic retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM), and to evaluate its utility in identifying prevalent DR. Methods: In this retrospective cross-sectional study, 1,750 patients with T2DM (654 with DR and 1,096 without DR) were enrolled. Multivariable logistic regression, subgroup, trend, and restricted cubic spline analyses were performed to evaluate the association between CPNI and prevalent DR. A nomogram for identifying prevalent DR was developed using variables selected by least absolute shrinkage and selection operator regression and multivariable logistic regression. Model performance was evaluated using discrimination, calibration, bootstrap internal validation, incremental predictive performance, and decision curve analysis. Results: Higher CPNI levels were independently associated with prevalent DR (OR = 1.024, 95% CI: 1.012-1.037, Conclusion: CPNI was independently and positively associated with prevalent DR in patients with T2DM and exhibited a linear dose-response relationship. A nomogram incorporating CPNI demonstrated acceptable performance for identifying prevalent DR.

Indexed as

cholesterol-modified prognostic nutritional indexdiabetic retinopathyLASSO regressionnomogram modeltype 2 diabetes mellitus

Identifiers

PMID42851381
PMCPMC13645571

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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.