Evidence mapPaperPMID 37693352Full record

Trial reportFrontiers in endocrinology2023

Development and evaluation of a risk prediction model for diabetes mellitus type 2 patients with vision-threatening diabetic retinopathy.

Di Gong, Lyujie Fang, Yixian Cai, Ieng Chong, Junhong Guo, Zhichao Yan, Xiaoli Shen, Weihua Yang, Jiantao Wang

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 3 pooled it
5.3field-weighted citation impact, top 4% of its field
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

20 citing papers in PubMed, 3 syntheses or guidelines pooled it, 19 citations in OpenAlex.

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  10. The Mechanisms of Inflammatory Factors and the Total Load of Cerebral Small Vessel Disease in Diabetic Retinopathy and Cognitive Impairment.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2025
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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

9 authors at 3 institutions in 2 countries.

Di GongShenzhen Eye Hospital, Jinan University, Shenzhen, Guangdong, China.
Lyujie FangThe First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, Guangdong, China.
Yixian CaiThe First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, Guangdong, China.
Ieng ChongMacau University Hospital, Macao, Macao SAR, China.
Junhong GuoShenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, China.
Zhichao YanShenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, China.
Xiaoli ShenShenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, China.
Weihua YangShenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, China.
Jiantao WangShenzhen Eye Hospital, Jinan University, Shenzhen Eye Institute, Shenzhen, Guangdong, China.
Jinan University · CNFirst Affiliated Hospital of Jinan University · CNUniversity of Macau · MO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to develop and evaluate a non-imaging clinical data-based nomogram for predicting the risk of vision-threatening diabetic retinopathy (VTDR) in diabetes mellitus type 2 (T2DM) patients. Methods: Based on the baseline data of the Guangdong Shaoguan Diabetes Cohort Study conducted by the Zhongshan Ophthalmic Center (ZOC) in 2019, 2294 complete data of T2DM patients were randomly divided into a training set (n=1605) and a testing set (n=689). Independent risk factors were selected through univariate and multivariate logistic regression analysis on the training dataset, and a nomogram was constructed for predicting the risk of VTDR in T2DM patients. The model was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC) in the training and testing datasets to assess discrimination, and Hosmer-Lemeshow test and calibration curves to assess calibration. Results: The results of the multivariate logistic regression analysis showed that Age (OR = 0.954, 95% CI: 0.940-0.969, Conclusion: The introduction of Age, BMI, SBP, Duration, and HbA1C as variables helps to stratify the risk of T2DM patients with VTDR.

Indexed as

Diabetes Mellitus, Type 2Diabetic RetinopathyCohort StudiesGlycated HemoglobinHumansRisk FactorsGlycated Hemoglobindiabetes mellitus type 2diabetic retinopathyprediction modelrisk factorsvision-threatening diabetic retinopathy

Identifiers

PMID37693352
PMCPMC10484608
OpenAlexW4386165080

What Socratic 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 Socratic graph.