Evidence map›Paper›PMID 40021914›Full record

ArticleScientific reports2025

Development and validation of a nomogram for arthritis: a cross-sectional study based on the NHANES.

Yue Lin, Yaxin Feng, Shanke Wu, Hai Kang, Xi Han, Baoguo Wang

Abstract readValidation Study
In one paragraph

Article in Scientific reports, 2025. 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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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

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yue LinGuangdong Pharmaceutical University, Hai Zhu District, Guangzhou, Guang Dong, China.
Yaxin FengGuangdong Pharmaceutical University, Hai Zhu District, Guangzhou, Guang Dong, China.
Shanke WuGuangdong Pharmaceutical University, Hai Zhu District, Guangzhou, Guang Dong, China.
Hai KangGuangdong Pharmaceutical University, Hai Zhu District, Guangzhou, Guang Dong, China.
Xi HanGuangdong Pharmaceutical University, Hai Zhu District, Guangzhou, Guang Dong, China.
Baoguo WangGuangdong Pharmaceutical University, Hai Zhu District, Guangzhou, Guang Dong, China. gdwangbaoguo@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous epidemiological studies have associated various body-related indicators with arthritis; however, the results have been inconclusive. Therefore, this research aimed to develop and validate a nomogram model for predicting the risk of arthritis using easily available indicators and to assess the model's predictive performance. Cross-sectional data were collected from 3660 participants in the 2021-2023 National Health and Nutrition Examination Survey. The research conducted variable selection and model development using the Least Absolute Shrinkage and Selection Operator regression model and multivariate logistic regression analysis, and the performance of the nomogram was validated. The nomogram model incorporated nine independent predictors: age, sex, family poverty-income ratio, race, diabetes status, vitamin D level, systemic immunity-inflammation index, and waist-to-height ratio. After validation, it has been proven that the nomogram model has good performance. The nomogram model developed in this study effectively predicts the risk probability of arthritis in the general population of the United States. All variables included in this nomogram can be easily obtained from the population.

Indexed as

ArthritisNomogramsAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedNutrition SurveysRisk FactorsUnited StatesArthritisCross-sectional studyNHANESNomogramObesity indicatorsWaist height ratio

Identifiers

PMID40021914
PMCPMC11871000

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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.