Evidence map›Paper›PMID 29759068›Full record

ArticleCardiovascular diabetology2018

Childhood retinol-binding protein 4 (RBP4) levels predicting the 10-year risk of insulin resistance and metabolic syndrome: the BCAMS study.

Ge Li, Issy C Esangbedo, Lu Xu, Junling Fu, Lujiao Li, Dan Feng, Lanwen Han, Xinhua Xiao, Mingyao Li, Jie Mi and 3 more

Open access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 2 pooled it
2.9field-weighted citation impact, top 8% 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

34 citing papers in PubMed, 2 syntheses or guidelines pooled it, 65 citations in OpenAlex.

  1. Pooled it
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  13. Analysis of Retinol Binding Protein 4 andDiagnostics (Basel, Switzerland) · 2023
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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

13 authors at 4 institutions in 2 countries.

Ge LiDepartment of Endocrinology, Key Laboratory of Endocrinology, National Health and Family Planning Commission, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, 1 Shuaifuyuan, Wangfujing, Dongcheng District, Beijing, 100730, China.
Issy C EsangbedoHealth Weight Program, The Children's Hospital of Philadelphia, Perelman School of Medicine at University of Pennsylvania, Philadelphia, PA, 19104, USA.
Lu XuDepartment of Endocrinology, Key Laboratory of Endocrinology, National Health and Family Planning Commission, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, 1 Shuaifuyuan, Wangfujing, Dongcheng District, Beijing, 100730, China.
Junling FuDepartment of Endocrinology, Key Laboratory of Endocrinology, National Health and Family Planning Commission, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, 1 Shuaifuyuan, Wangfujing, Dongcheng District, Beijing, 100730, China.
Lujiao LiDepartment of Endocrinology, Key Laboratory of Endocrinology, National Health and Family Planning Commission, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, 1 Shuaifuyuan, Wangfujing, Dongcheng District, Beijing, 100730, China.
Dan FengDepartment of Endocrinology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100043, China.
Lanwen HanDepartment of Endocrinology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100043, China.
Xinhua XiaoDepartment of Endocrinology, Key Laboratory of Endocrinology, National Health and Family Planning Commission, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, 1 Shuaifuyuan, Wangfujing, Dongcheng District, Beijing, 100730, China.
Mingyao LiDepartment of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Jie MiDepartment of Epidemiology, Capital Institute of Paediatrics, Beijing, 100020, China.
Ming LiDepartment of Endocrinology, Key Laboratory of Endocrinology, National Health and Family Planning Commission, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, 1 Shuaifuyuan, Wangfujing, Dongcheng District, Beijing, 100730, China. liming@pumch.cn.ORCID 0000-0001-8255-0433
Shan GaoDepartment of Endocrinology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100043, China. gaoshanmw@163.com.
Steven M WilliDepartment of Endocrinology/Diabetes, The Children's Hospital of Philadelphia, Perelman School of Medicine at University of Pennsylvania, Philadelphia, PA, 19104, USA.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNCapital Medical University · CNChildren's Hospital of Philadelphia · USCapital Institute of Pediatrics · CN

Funding

Beijing Science & Technology Star Program 2004A027Development Program of Beijing Chaoyang Hospital JXPY201606key program of Beijing Municipal Science &Technology Commission D111100000611001key program of Beijing Municipal Science &Technology Commission D111100000611002National Key Program of Clinical Science WBYZ 2011-873National Key Research program of China 2016YFC1304801Natural Science Foundation of Beijing Municipality 7172169Novo Nordisk Union Diabetes Research Talent Fund 2011A002
6 · The paper itself

Abstract

backgroundElevated retinol-binding protein 4 (RBP4) levels may contribute to the development of metabolic abnormalities, but prospective studies evaluating the association between childhood RBP4 levels and metabolic syndrome (MS) in adulthood are lacking. We investigated whether RBP4 levels during childhood predict cardiometabolic risk at 10-year follow-up.

methodsThe relationships between RBP4 levels, the established adipokines (leptin and adiponectin) and the components of MS were examined in 3445 school-aged children recruited in 2004 for the Beijing Child and Adolescent Metabolic Syndrome study. In 2015, 352 of these individuals completed an in-depth follow-up examination.

resultsParticipants with higher childhood RBP4 levels had adverse cardiometabolic profiles at follow-up. Those with incident or persistent MS had higher baseline RBP4 levels than those who never exhibited the elements of MS. Moreover, baseline RBP4 predicted hyperglycemia (OR per SD increase = 1.48, P = 0.009), elevated triglyceride (OR = 1.54, P < 0.001), elevated blood pressures (OR = 1.46, P = 0.015), MS (OR = 1.68, P = 0.002) and insulin resistance (OR = 1.44, P = 0.015) in the 10-year follow-up phase, independent of baseline BMI. Significant improvements were seen for the net reclassification improvement and integrated discrimination index after adding childhood RBP4 levels into the risk models using conventional cardiometabolic risk factors in predicting MS at follow-up (P < 0.05). Leptin and adiponectin demonstrated the expected associations with metabolic disorders.

conclusionsChildhood RBP4 serves as a risk factor for subsequent development of MS and its components, independent of pediatric obesity. Incorporating childhood RBP4 into conventional cardiometabolic risk assessment models significantly improves the prediction of MS.

Indexed as

Insulin ResistanceAdolescentAge FactorsBiomarkersChildChinaCross-Sectional StudiesDecision Support TechniquesFemaleHumansIncidenceLongitudinal StudiesMaleMetabolic SyndromePredictive Value of TestsProspective StudiesBiomarkersRBP4 protein, humanRetinol-Binding Proteins, PlasmaChildrenInsulin resistanceMetabolic syndromeRetinol-binding protein 4Youth

Identifiers

PMID29759068
PMCPMC5950249
OpenAlexW2804001633

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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.