Evidence map›Paper›PMID 28267752›Full record

SynthesisPloS one2017

Serum glycated hemoglobin level as a predictor of atrial fibrillation: A systematic review with meta-analysis and meta-regression.

Wenwei Qi, Nixiao Zhang, Panagiotis Korantzopoulos, Konstantinos P Letsas, Min Cheng, Fusheng Di, Gary Tse, Tong Liu, Guangping Li

Abstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 6 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

29 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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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

9 authors.

Wenwei QiTianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin, China.
Nixiao ZhangTianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin, China.
Panagiotis KorantzopoulosFirst Department of Cardiology, University of Ioannina Medical School, Ioannina, Greece.
Konstantinos P LetsasSecond Department of Cardiology, Laboratory of Cardiac Electrophysiology, "Evangelismos" General Hospital of Athens, Athens, Greece.
Min ChengState Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Fusheng DiDepartment of Endocrinology and Metabolism, the Third Central Hospital of Tianjin, Tianjin, China.
Gary TseDepartment of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong, Special Administrative Region, P.R. China.
Tong LiuTianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin, China.
Guangping LiTianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimGlycated hemoglobin (HbA1c) is a long-term measure of glucose control. Although recent studies demonstrated a potential association between HbA1c levels and the risk of atrial fibrillation (AF), the results have been inconsistent. The aim of this meta-analysis is to evaluate the utility of HbA1c level in predicting AF.

methodsPubMed and the Cochrane Library databases were searched for relevant studies up to March 2016. Prospective cohort studies and retrospective case-control studies were included. Relative risk (RR) or odds ratio (OR) with 95% confidence intervals (CIs) of AF development were determined for different HbA1c levels. The random effect model was conducted according to the test of heterogeneity among studies. Subgroup analyses and meta-regression models were carried out to identify potential sources of heterogeneity.

resultsEight prospective cohort studies with 102,006 participants and 6 retrospective case-control studies with 57,669 patients were finally included in the meta-analysis. In the primary meta-analysis, HbA1c levels were not associated with an increased risk of AF whether as a continuous (RR, 1.06; 95% CI, 0.96-1.18) or categorical variable (RR, 0.99; 95% CI, 0.83-1.18). Nevertheless, prospective studies showed about 10% increased risk of AF with elevated HbA1c levels both as a continuous (RR, 1.11; 95% CI, 1.06-1.16) and as a categorical variable (RR, 1.09; 95% CI, 1.00-1.18). In subgroup analyses, pooled results from studies with longer follow-up durations, published after 2012, aged < 63 years, with exclusion of cardiac surgery patients demonstrated an increased risk of AF for every 1% increase in HbA1c levels, while studies conducted in the United States with longer follow-up (more than 96 months), larger sample size and higher quality score (≥6) showed an increased risk of AF for higher HbA1c level as a categorical variable.

conclusionsElevated serum HbA1c levels may be associated with an increased risk of AF, but further data are needed. Serum HbA1c levels might be considered as a potential biomarker for prediction of AF.

Indexed as

Glycated HemoglobinAtrial FibrillationBiomarkersHumansOdds RatioPrognosisPublication BiasRisk AssessmentBiomarkersGlycated Hemoglobin

Identifiers

PMID28267752
PMCPMC5340354

What Socratic holds

Textmetadata
LicenceCC BY
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.