Evidence map›Paper›PMID 38494690›Full record

ArticleAsia Pacific journal of clinical nutrition2024

Nomogram for predicting the risk of nonalcoholic fatty liver disease in older adults in Qingdao, China: A cross-sectional study.

Zhi Wang, Jing Cui, Xiaojing Li, Ruili Gao, Enqiang Feng, Guoqiang Luo, Baozhu Guo, Haojia Wu, Yongye Sun, Jianping Sun

Open access · greenAbstract read
In one paragraph

Article in Asia Pacific journal of clinical nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 39% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

10 authors at 3 institutions in 1 country.

Zhi Wang *School of Public Health, Qingdao University, Qingdao, China.
Jing Cui *Qingdao Centers for Disease Control and Prevention/Qingdao Institute for Preventive Medicine, Qingdao China.
Xiaojing LiQingdao Centers for Disease Control and Prevention/Qingdao Institute for Preventive Medicine, Qingdao China.
Ruili GaoAnqiu People's Hospital, Weifang, China.
Enqiang FengQingdao Centers for Disease Control and Prevention/Qingdao Institute for Preventive Medicine, Qingdao China.
Guoqiang LuoQingdao Centers for Disease Control and Prevention/Qingdao Institute for Preventive Medicine, Qingdao China.
Baozhu GuoSchool of Public Health and Management, Weifang Medical University, Weifang, China.
Haojia WuSchool of Public Health and Management, Weifang Medical University, Weifang, China.
Yongye SunSchool of Public Health, Qingdao University, Qingdao, China. Email: sunnyleaf@qdu.edu.cn.
Jianping SunQingdao Centers for Disease Control and Prevention/Qingdao Institute for Preventive Medicine, Qingdao China. Email: qdcdcsjp@126.com.
Weifang Medical University · CNQingdao University · CNWeifang People's Hospital · CN

Funding

Qingdao Diabetes Prevention Program and the World Diabetes Foundation WDF05-108Qingdao Diabetes Prevention Program and the World Diabetes Foundation WDF07-308Qingdao Science & Technology department program 19-6-1-5-nsh
6 · The paper itself

Abstract

BACKGROUND AND

objectivesTo explore the risk factors for non-alcoholic fatty liver disease (NAFLD) and to establish a non-invasive tool for the screening of NAFLD in an older adult population. METHODS AND STUDY

designA total of 131,161 participants were included in this cross-sectional study. Participants were randomly divided into training and validation sets (7:3). The least absolute shrinkage and selection operator method was used to screen risk factors. Multivariate logistic regression was employed to develop a nomogram, which was made available online. Receiver operating characteristic curve analysis, calibration plots, and decision curve analysis were used to validate the discrimination, calibration, and clinical practicability of the nomogram. Sex and age subgroup analyses were conducted to further validate the reliability of the model.

resultsNine variables were identified for inclusion in the nomogram (age, sex, waist circumference, body mass index, exercise frequency, systolic blood pressure, fasting plasma glucose, alanine aminotransferase, and low-density lipoprotein cholesterol). The area under the receiver operating characteristic curve values were 0.793 and 0.790 for the training set and the validation set, respectively. The calibration plots and decision curve analyses showed good calibration and clinical utility. Subgroup analyses demonstrated consistent discriminatory ability in different sex and age subgroups.

conclusionsThis study established and validated a new nomogram model for evaluating the risk of NAFLD among older adults. The nomogram had good discriminatory performance and is a non-invasive and convenient tool for the screening of NAFLD in older adults.

Indexed as

Non-alcoholic Fatty Liver DiseaseAgedChinaCross-Sectional StudiesHumansNomogramsReproducibility of ResultsRisk Factorsagednomogramnon-alcoholic fatty liver diseasenon-invasive model

Identifiers

PMID38494690
PMCPMC11170012
OpenAlexW4394766259

What Socratic holds

Textmetadata
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.