Evidence map›Paper›PMID 29416120›Full record

ArticleJournal of human hypertension2018

Relationship of serum immunoglobulin levels to blood pressure and hypertension in an adult population.

Xiaotong Wang, Yajun Li, Huihui Li, Yeqing Gu, Yanqi Song, Qing Zhang, Li Liu, Ge Meng, Zhanxin Yao, Hongmei Wu and 16 more

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of human hypertension, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 26% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
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  4. Multiple Sclerosis, Rituximab, Hypogammaglobulinemia, and Risk of Infections.Neurology(R) neuroimmunology & neuroinflammation · 2024
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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

26 authors at 3 institutions in 1 country.

Xiaotong WangNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Yajun LiNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Huihui LiNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Yeqing GuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Yanqi SongTianjin University of Traditional Chinese Medicine, Tianjin, China.
Qing ZhangHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Li LiuHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Ge MengNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Zhanxin YaoTianjin Institute of Health and Environmental Medicine, Tianjin, China.
Hongmei WuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Yang XiaNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Xue BaoNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Hongbin ShiHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Qian SuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Liyun FangNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Huijun YangNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Fei YuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Shaomei SunHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Xing WangHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Ming ZhouHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Huanli JiaoHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Qiyu JiaHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Kun SongHealth Management Centre, Tianjin Medical University General Hospital, Tianjin, China.
Yuntang WuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China.
Hong ChangNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China. nkj0809@gmail.com.
Kaijun NiuNutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China. niukaijun@tmu.edu.cn.
Tianjin Medical University · CNTianjin Medical University General Hospital · CNTianjin University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Evidence suggests long-term chronic inflammation, as the pathological basis of formation and development, plays an important part in atherosclerosis. Immunoglobulins (Igs) provided key information on the humoral immune status. However, few studies have evaluated the correlation between Igs and hypertension and blood pressure (BP) in a general population. We designed a cross-sectional study to evaluate whether serum Ig levels are related to BP and the prevalence of hypertension. About 12,373 participants in Tianjin, China were recruited for this study. Hypertension was diagnosed according to the criteria of the JNC 7 and serum levels of Igs were determined by the immunonephelometric technique. Multiple logistic regression analysis and analysis of covariance were used to assess relationships between serum Ig concentrations and the prevalence of hypertension and BP. The overall prevalence of hypertension was 35.5%. The means (standard deviation) of immunoglobulins [immunoglobulin G (IgG), immunoglobulin E (IgE), immunoglobulin M (IgM), and immunoglobulin A (IgA)] were 1206.0 (249.0) mg/dL, 93.8 (235.4) IU/mL, 105.3 (56.8) mg/dL, and 236.7 (98.1) mg/dL, respectively. The multivariable-adjusted odds ratios (95% confidence interval) of hypertension for the highest immunoglobulins (IgG, IgE, IgM, and IgA) quintile, when compared to the lowest quintile were 1.10 (0.96-1.26), 1.04 (0.91-1.19), 0.83 (0.72-0.96), and 1.32 (1.15-1.51), respectively. Decreased IgM and increased IgG and IgA were related to a higher prevalence of hypertension. IgM was negatively correlated with BP, while IgG and IgA were positively correlated with BP.

Indexed as

Blood PressureCross-Sectional StudiesFemaleHumansHypertensionImmunoglobulinsMaleMiddle AgedImmunoglobulins

Identifiers

PMID29416120
OpenAlexW2883610233

What OpenQuestion holds

Textmetadata
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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.