Evidence map›Paper›PMID 35596917›Full record

SynthesisJournal of endocrinological investigation2022

Association between insulin-like growth factor-1 and cardiovascular events: a systematic review and dose-response meta-analysis of cohort studies.

T Li, Y Zhao, X Yang, Y Feng, Y Li, Y Wu, M Zhang, X Li, H Hu, J Zhang and 6 more

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Journal of endocrinological investigation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

3 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. 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

16 authors.

T LiDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Y ZhaoDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
X YangDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Y FengDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Y LiDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.
Y WuDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.
M ZhangDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.
X LiDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
H HuDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
J ZhangDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
L YuanDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Y LiuDepartment of General Practice, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, 518001, Guangdong, People's Republic of China.
X SunDepartment of General Practice, The Affiliated Luohu Hospital of Shenzhen University Health Science Center, Shenzhen, 518001, Guangdong, People's Republic of China.
P QinDepartment of Endocrinology, Shenzhen Qianhai Shekou Free Trade Zone Hospital, Shenzhen, Guangdong, People's Republic of China.
C ChenDepartment of Medical Record Management, Shenzhen Qianhai Shekou Free Trade Zone Hospital, Shenzhen, Guangdong, People's Republic of China.
D HuDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China. dongshenghu563@126.com.ORCID http://orcid.org/0000-0002-9998-8041

Funding

the National Natural Science Foundation of China 81673260the National Natural Science Foundation of China Grant nos. 81402752
6 · The paper itself

Abstract

backgroundInsulin-like growth factor-1 (IGF-1) has increasingly been reported as linked to cardiovascular (CV) events; however, reported results have been inconsistent, and no meta-analysis has been undertaken to quantitatively assess this association.

methodsWe searched PubMed, Embase, and Web of Science databases for cohort articles published up to December 1, 2020. Fixed or random-effects models were used to estimate the summary relative risks (RRs) and 95% confidence intervals (CIs) of CV events in relation to IGF-1. Restricted cubic splines were used to model the dose-response association.

resultsWe identified 11 articles (thirteen cohort studies) covering a total of 22,995 participants and 3040 CV events in this meta-analysis. The risk of overall CV events reduced by 16% from the highest to the lowest IGF-1 levels (RR 0.83, 95% CI 0.72-0.95), while the occurrence of CV events reduced by 28% (RR 0.72, 95% CI 0.56-0.92), but not for CV deaths, however (RR 1.00, 95% CI 0.65-1.55). We also found linear associations between IGF-1 levels and CV events. With each per 45 μg/mL IGF-1 increase, the pooled RRs were 0.91 (95% CI 0.86-0.96), 0.91 (95% CI 0.85-0.97) and 0.91 (95% CI 0.84-0.98) for overall CV events, for the occurrence of CV events, and for CV deaths, respectively.

conclusionsOur findings based on cohort studies support the contention that any increase in IGF-1 is helpful in reducing the overall risk of CV events. As an important biomarker for assessing the likelihood of CV events, IGF-1 appears to offer a promising prognostic approach for aiding prevention.

Indexed as

Cardiovascular DiseasesInsulin-Like Growth Factor ICohort StudiesHumansPrognosisRisk FactorsInsulin-Like Growth Factor ICardiovascular eventsCohort studyDose–responseInsulin-like growth factor-1Meta-analysis

Identifiers

What OpenQuestion holds

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Registered trials

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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.