Literature DB >> 28360407

Predictive Role of Coagulation, Fibrinolytic, and Endothelial Markers in Patients with Atrial Fibrillation, Stroke, and Thromboembolism: A Meta-Analysis, Meta-Regression, and Systematic Review.

Alexander Weymann1, Anton Sabashnikov2,3, Sadeq Ali-Hasan-Al-Saegh4, Aron-Frederik Popov5, Seyed Jalil Mirhosseini4, William L Baker6, Mohammadreza Lotfaliani4, Tong Liu7, Hamidreza Dehghan8, Senol Yavuz9, Michel Pompeu Barros de Oliveira Sá10,11,12, Jae-Sik Jang13, Mohamed Zeriouh2,3, Lei Meng14, Fabrizio D'Ascenzo15, Abhishek J Deshmukh16, Guiseppe Biondi-Zoccai17,18, Pascal M Dohmen1, Hugh Calkins19, Integrated Meta-Analysis Of Cardiac Cardiac Surgery And Cardiology-Group Imcsc-Group20.   

Abstract

BACKGROUND The pathophysiological mechanism associated with the higher prothrombotic tendency in atrial fibrillation (AF) is complex and multifactorial. However, the role of prothrombotic markers in AF remains inconclusive. MATERIAL AND METHODS We conducted a meta-analysis of observational studies evaluating the association of coagulation activation, fibrinolytic, and endothelial function with occurrence of AF and clinical adverse events. A comprehensive subgroup analysis and meta-regression was performed to explore potential sources of heterogeneity. RESULTS A literature search of major databases retrieved 1703 studies. After screening, a total of 71 studies were identified. Pooled analysis showed the association of coagulation markers (D-dimer (weighted mean difference (WMD) =197.67 and p<0.001), fibrinogen (WMD=0.43 and p<0.001), prothrombin fragment 1-2 (WMD=0.53 and p<0.001), antithrombin III (WMD=23.90 and p=0.004), thrombin-antithrombin (WMD=5.47 and p=0.004));  fibrinolytic markers (tissue-type plasminogen activator (t-PA) (WMD=2.13 and p<0.001), plasminogen activator inhibitor (WMD=11.44 and p<0.001), fibrinopeptide-A (WMD=4.13 and p=0.01)); and  endothelial markers (von Willebrand factor (WMD=27.01 and p<0.001) and soluble thrombomodulin (WMD=3.92 and p<0.001)) with AF. CONCLUSIONS The levels of coagulation, fibrinolytic, and endothelial markers have been reported to be significantly higher in AF patients than in SR patients.

Entities:  

Keywords:  Atrial Fibrillation; Blood Coagulation Disorders; Fibrinolysis

Mesh:

Substances:

Year:  2017        PMID: 28360407      PMCID: PMC5452871          DOI: 10.12659/MSMBR.902558

Source DB:  PubMed          Journal:  Med Sci Monit Basic Res        ISSN: 2325-4394


Background

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia in the general population and is associated with a high risk of developing morbidities such as hemodynamic instability, thromboembolism, stroke, hospital re-admissions, and increasing health care costs [1]. AF alone is associated with a 1.5% to 1.9% increase in risk of mortality in both sexes across a wide range of ages [2]. Moreover, the situation is likely to worsen since the number of people with AF is expected to double by 2050 [2], AF is linked to a 5-fold increased risk of cerebrovascular events, and approximately 20% of strokes are related to AF [3]. Recently, researchers have suggested several important mechanisms for the occurrence of AF, including oxidative stress reactions and systemic inflammation [4]. The pathophysiological mechanism associated with the higher prothrombotic tendency in AF is highly complex and multifactorial [5]. Virchow’s triad regarding prothrombotic state, including changed blood flow (arterial stasis), abnormalities in vessel wall, and coagulant alternations in the hemostatic balance, may play an important role in the occurrence of supraventricular arrhythmia [6]. Various studies have reported the association of hemostatic markers with the occurrence of AF. However, so far, the data from these studies are largely inconclusive. The present systematic review with meta-analysis sought to determine the strength of evidence for evaluating the role of coagulation activation, fibrinolytic, and endothelial function in the occurrence of AF and related consequent outcomes such as thromboembolism and stroke.

Material and Methods

Literature search

A systematic and comprehensive literature search was conducted in electronic databases (Medline/PubMed, Embase, Web of Science, and Google Scholar) from their inception through 5 August 2016 to identify relevant studies on the association of coagulation, fibrinolytic, and endothelial functional assessment with the occurrence of AF and related consequent clinical adverse events, including thromboembolism and stroke. Predefined search terms were: coagulation [“fibrinogen”, “D-dimer”, “prothrombin fragment 1–2”, “antithrombin III”, “thrombin-antithrombin”], fibrinolytic [“tissue-type plasminogen activator”, “plasminogen activator inhibitor”, “alfa-2 antiplasmin”, “fibrinopeptide-A”, “urokinase-type plasminogen activator”, “plasmin-antiplasmin”], endothelial function [“von Willebrand factor”, “soluble thrombomodulin”], and “atrial fibrillation”. No limitations were imposed on language, time of publication, or sample size of studies. All retrieved references of the included studies and recent published review articles and meta-analyses were also reviewed to determine additional studies not indexed in major databases.

Study selection

Studies were included in the analysis when they met the following criteria: 1) human subjects; 2) case-control or cohort studies; 3) the study investigated the comparison between AF-cases and non-AF-population regarding biomarkers of endothelial, coagulation, and fibrinolytic function; 4) the study compared cohorts of patients with and without stroke, as well as with and without thromboembolic events in patients with AF in terms of biomarkers. Abstracts without peer-review, abstracts from congress presentations, and gray literature were not included.

Data extraction and outcome measures

Three investigators (S.A.-H-S, A.W., and A.S.) extracted the data independently, and discrepancies were resolved via a consensus standardized abstraction checklist used for recording data in each enrolled study. Disagreements were resolved through discussion with senior authors (A.F.-P, G.B.Z, and H.C.). Author’s name, year of publication, country, design of study, procedure, sample size, mean age, sex, coexistent cardiovascular disease and risk factors, anticoagulants, type of AF, and details of hemostatic markers were extracted. For exploration of heterogeneity among trials, subgroup analyses of disparities in the patients’ characteristics were performed for (1) year of publication (before 2000 vs. after 2000); (2) geographic area (Asia, Europe, Africa, North-America, South-America, and Oceania); (3) design of the study (case-control vs. cohort); (4) number of patients (≤300 vs. >300); (5) mean age (≤60 years vs. >60 years); (6) percentage of males (≤70% vs. >70%); (7) diabetes (≤30% vs. >30%); (8) hypertension (≤70% vs. >70%); (9) myocardial infarction (≤20% vs. >20%); (10) AF-classification (acute and sub-acute vs. chronic); (11) type of AF (paroxysmal, persistent, permanent); and (12) anticoagulation (code-1: no patient received anticoagulants in both groups, code-2: all participants were anticoagulated in both groups, code-3: range of percentages between both groups more than 50%, code-4: range of percentages between both groups less than 50%, code-5: anticoagulation information was not available in both groups, and code-6: anticoagulation information was not available in 1 group only).

Homogenization of extracted data

The suitable form of data for analyzing was mean ± standard deviation (SD). For studies that reported interquartile ranges instead of the range, we estimated means according to [minimum+maximum+2(median)]/4 and SD according to (maximum-minimum)/4 for groups with sample sizes up to about 70 and (maximum-minimum)/6 for sample sizes more than 70 [7].

Quality assessment and statistical analysis

Two investigators (L.M. and M.G.) independently assessed the quality of studies by using the Newcastle-Ottawa scale [8]. The total scores ranged from 0 (worst quality) to 9 (best quality) for case-control or cohort studies. Data were analyzed by STATA software version 11.0 utilizing METAN and METABIAS modules. The pooled effect size measured was weighted mean difference (WMD) with 95% CI for non-categorical data. Heterogeneity p value <0.1 for Q test or I2 >50% indicated significant heterogeneity among the studies. Heterogeneity among trials was accounted for by applying a random effect model when indicated. Sample weighting assigned studies with larger sample sizes and more weight, and reduced the effect of sampling error because sampling error generally decreases as the sample size increases. The presence of publication bias was evaluated using the Begg tests. Results were considered statistically significant at a P value <0.05.

Results

Literature search strategy and included studies

The literature search retrieved 1703 studies from screened databases, of which 1527 (89.6%) were excluded after detailed evaluation in the initial review due to either redundant information (n=1095), insufficient reporting of endpoints of interest (n=398), or reporting of non-matched data according to mean ± SD or median [minimum-maximum] (n=34); 176 potentially relevant full-text articles were reviewed, and a total of 71 studies were finally included in the meta-analysis (Supplementary Table 1).

Association of coagulation markers with AF

D-dimer

A total of 7954 cases were included from 41 studies. Patient populations in the included studies ranged from 22 to 3120 patients. Of 7954 cases, 2269 were allocated to AF group and 5685 to the SR group. Mean D-dimer levels were 520.05 μg/mL in AF group and 249.28 μg/mL in SR group (details in Tables 1 and 2). Pooled assessment effect analysis revealed that the mean D-dimer level was significantly higher in patients with AF than in patients with SR with WMD of 197.67 (95% CI: 172.96–222.38; p<0.001, Figure 1) using a random effect model. Significant heterogeneity was observed among the studies (I2=99.8%; heterogeneity p<0.001).
Table 1

Characteristics of included studies for meta-analysis of association of biomarkers and AF.

First AuthorYearCountryDesignN-AFN-SRAge-AFAge-SRMale-AFMale-SRAC-AFAC-SRType of AFNOS
Negreva [9]2016BulgariaCohort515259.8459.550.95000Paroxysmal6
Amdur [10]2016USACohort642312060.85753.855.348.642ND9
Yusuf (disease control) [11]2015IndiaCase-Control353031.8631.1445.74000ND8
Yusuf (healthy control) [11]2015IndiaCase-control353028.9731.1437.14000ND8
Drabik (persistent) [12]2015PolandCase-control475060.859.465.96438.326Persistent8
Drabik (PAF) [12]2015PolandCase-control415060.659.446.36451.226Paroxysmal8
Borgi [13]2015TunisCase-control501961.8ND42NDNDNDCombined7
Oneal (with comorbidities) [14]2015USACohort79568716844644742ND9
Oneal (with comorbidities) [14]2015USACohort63820656422435838ND9
Erdogan [15]2014TurkeyCase-control343370.568.647.0551.566.60Permanent9
Chen (without comorbidities) [16]2014ChinaCohort6210055.152.2958.06641912Combined8
Chen (with comorbidities) [16]2014ChinaCohort10710059.452.2964.4642612Combined8
Schnabel [17]2014GermanyCohort161483764.955.25950NDNDND9
Wei-Hong Ma [18]2014ChinaCohort5550595774.570100100ND8
Xu (without comorbidities) [19]2014ChinaCohort575865.967.850.95050.915.5ND7
Xu (with comorbidities) [19]2014ChinaCohort575868.956752.65049.115.5ND7
Distelmaier [20]2014USACase-control6613273.573.56161NDNDND7
Scridon (PAF) [21]2013FranceCase-control5217565581761000Paroxysmal7
Scridon (persistent) [21]2013FranceCase-control3617555581761000Persistent7
Berge [22]2013NorwayCohort63126757571.470.6833Combined9
Acevedo [23]2012ChileCase-control1302067NDNDND00Combined8
Zorlu [24]2012TurkeyCohort311197267646000ND8
Alonso (White) [25]2012USACohort9761013157.354.158.446.100ND9
Alonso (African-American) [25]2012USACohort233351856.253.444.637.800ND9
Adamsson Eryd [26]2011SwedenCohort667536447.846.7100100NDNDND9
Fu [27]2011ChinaCase-control907954.154.87057220Combined8
Hou (disease control) [28]2010ChinaCase-control262665.264.557.657.67.611.5ND8
Hou (healthy control) [28]2010ChinaCase-control262665.265.457.657.67.60ND8
Schnabel [29]2010USACohort209291166.357.86045NDNDND9
Letsas (PAF) [30]2010GreeceCase-control454867.561.36256NDNDParoxysmal9
Letsas (permanent) [30]2010GreeceCase-control414871.961.36356NDNDPermanent9
Gartner [31]2008AustriaCase-control2222864.554.463685540ND6
Targonski (PAF and PeAF) [32]2008PolandCase-control263070.356.765.47084.683.3Combined (PAF and PeAF)8
Targonski (Permanent) [32]2008PolandCase-control433069.968.762.87048.883.3Permanent8
Marcus [33]2008USACase-control4692574669481NDNDND9
Blann [34]2007UKCase-control5428656464.860.7600ND6
Topaloglu (disease control) [35]2007TurkeyCase-control18283732NDNDNDNDND6
Topaloglu (healthy control) [35]2007TurkeyCase-control18203735NDNDNDNDND6
Cecchi (with cerebral ischemic) [36]2006ItalyCase-control62130757261.259.21000ND6
Cecchi (without cerebral ischemic) [36]2006ItalyCase-control94130747259.559.21000ND6
Turgut (disease control) [37]2006TurkeyCase-control262967.4264.830.858.638.520.7ND8
Turgut (healthy control) [37]2006TurkeyCase-control262067.4265.730.857.138.50ND8
Heeringa [38]2006UKCohort16232478775151NDNDND8
Roldan [39]2005SpainCase-control1917472ND51.3ND10062.2ND7
Marin (acute AF) [40]2004SpainCase-control24246463505016.60ND8
Marin (chronic AF) [40]2004SpainCase-control2424646345.85041.60ND8
Inoue (with comorbidities) [41]2004JapanCase-control15992NDNDNDNDNDNDND7
Inoue (Lone AF) [41]2004JapanCase-control8719NDNDNDNDNDNDND7
Conway [42]2004UKCase-control1064169676361860Permanent6
Hatzinikolaou-Kotsakou (PAF) [43]2004GreeceCase-control1817595972.282.3NDNDParoxysmal8
Hatzinikolaou-Kotsakou (persistent) [43]2004GreeceCase-control1717615964.782.3NDNDPersistent8
Hatzinikolaou-Kotsakou (permanent) [43]2004GreeceCase-control201764597082.3NDNDPermanent8
Conway [44]2004UKCase-control3737676872.967.5NDNDPersistent6
Kamath (PAF and PeAF) [45]2003UKCase-control3131616661.341.900Combined (PAF and PeAF)6
Kamath (permanent AF) [45]2003UKCase-control9331666663.441.900Permanent6
Marin [46]2003SpainCase-control483271706347389ND7
Conway [47]2003UKCohort162324787751.250.900ND8
Kamath (PAF) [48]2002UKCase-control2929616555.1741.337.90Paroxysmal7
Kamath (permanent AF) [48]2002UKCase-control8729656563.241.337.90Permanent7
Kamath [49]2002UKCase-control9350707062.46400ND6
Wang [50]2002TaiwanCohort53315966.153.956.646.7NDNDND9
Li-saw-Hee (PAF) [51]2001UKCase-control2320656369.68569.60Paroxysmal8
Li-saw-Hee (PeAF) [51]2001UKCase-control2320656369.5851000Persistent8
Li-saw-Hee (permanent) [51]2001UKCase-control2320676369.5851000Permanent8
Feng [52]2001USACase-control471676262.374.572.576.6NDND8
Topcuoglu [53]2000TurkeyCase-control152161.962.866.657.1400ND6
Mondillo [54]2000ItalyCase-control453567.666.38085.7550Permanent7
Giansante [55]2000ItalyCase-control3570646354.257.1400Paroxysmal7
Li-saw-Hee [56]2000UKCase-control52606866807500ND6
Marin (disease control) [57]1999SpainCase-control1824565122.212.500ND6
Marin (healthy control) [57]1999SpainCase-control182056ND22.2ND00ND6
Li-saw-Hee [58]1999UKCase-control252560582020NDNDND6
Roldan [59]1998SpainCase-control3620626262ND00ND7
Tsai [50]1998TaiwanCase-control7338656375.373.6110ND6
Minamino [61]1997JapanCase-control4545636373.373.3NDNDND6
Kahn [62]1997CanadaCase-control5031ND65ND38.700ND7
Sohara [63]1997JapanCase-control21959.159.171.4ND00Paroxysmal6
Lip (PAF) [64]1996UKCase-control3015860.858.96055.600Paroxysmal8
Lip (chronic) [64]1996UKCase-control5615864.758.957.1455.600ND8
Lip [65]1996UKCase-control512670.4NDNDND00ND6
Mitusch [66]1996GermanyCase-control692872704260.700ND7
Nagao [67]1995JapanCase-control171981.578.447.0542.100ND8
Lip [68]1995UKCase-control871586359.350.656NDNDND7
Sohara [69]1994JapanCase-control13960ND76.9ND00Paroxysmal6
Kumagai [70]1990JapanCase-control7321646153.442.900ND7
Gustafsson (with stroke) [71]1990Swedencase-control20407777NDND00ND8
Gustafsson (without stroke) [71]1990Swedencase-control20407777NDND00ND8
Table 2

Information about markers and these levels in each study.

First authorMarkersLevels
Occurrence of AF
Negreva [9]sTMsTM: AF: 6.5±0.4 vs. SR: 4.48±0.28
Amdur [10]FibrinogenFibrinogen: AF: 4.3±1.1 vs. SR: 4.1±1.2
Yusuf (disease control) [11]TAT and PAITAT: AF: 22.65±2.35 vs. SR: 9.07±1.22PAI: AF: 47.9±2.5 vs. SR: 13.52±3.57
Yusuf (healthy control) [11]TAT and PAITAT: AF: 15.37±1.87 vs. SR: 9.07±1.22PAI: AF: 26.72±3.37 vs. SR: 13.52±3.57
Drabik (persistent) [12]Fibrinogen, tPA, PAI, and vWFFibrinogen: AF: 3.32±0.27 vs. SR: 3.12±0.32tPA: AF: 12.8±1.8 vs. SR: 9.4±2.1PAI: AF: 28.1±1.35 vs. SR: 24.07±3.12vWF: AF: 171±8 vs. SR: 121.75±5.25
Drabik (PAF) [12]Fibrinogen, tPA, PAI, and vWFFibrinogen: AF: 3.25±0.25 vs. SR: 3.12±0.32tPA: AF: 11.9±2.5 vs. SR: 9.4±2.1PAI: AF: 27.95±1.65 vs. SR: 24.07±3.12vWF: AF: 172.75±10.75 vs. SR: 121.75±5.25
Borgi [13]D-dimerD-dimer: AF: 590±506 vs. SR: 225.26±112.95
Oneal (with comorbidities) [14]FibrinogenFibrinogen: AF: 0.42±0.10 vs. SR: 0.41±0.11
Oneal (with comorbidities) [14]FibrinogenFibrinogen: AF: 0.41±0.07 vs. SR: 0.38±0.10
Erdogan [15]D-dimer and FibrinogenD-dimer: AF: 204.7±159.2 vs. SR: 186.2±105.6Fibrinogen: AF: 2.74±0.63 vs. SR: 2.27±0.51
Chen (without comorbidities) [16]D-dimer and FibrinogenD-dimer: AF: 660±60 vs. SR: 270±20Fibrinogen: AF: 2.63±0.07 vs. SR: 2.57±0.12
Chen (with comorbidities) [16]D-dimer and FibrinogenD-dimer: AF: 350±20 vs. SR: 270±20Fibrinogen: AF: 2.62±0.05 vs. SR: 2.57±0.12
Schnabel [17]FibrinogenFibrinogen: AF: 4.11±0.35 vs. SR: 3.47±0.23
Wei-Hong Ma [18]vWFvWF: AF: 166±46 vs. SR: 141±24
Xu (without comorbidities) [19]D-dimer and FibrinogenD-dimer: AF: 379.5±48 vs. SR: 98.5±5Fibrinogen: AF: 3.64±0.89 vs. SR: 2.62±0.5
Xu (with comorbidities) [19]D-dimer and FibrinogenD-dimer: AF: 398.25±54.75 vs. SR: 98.5±5Fibrinogen: AF: 3.68±0.62 vs. SR: 2.62±0.5
Distelmaier [20]FibrinogenFibrinogen: AF: 4±0.27 vs. SR: 4.11±0.23
Scridon (PAF) [21]vWFvWF: AF: 107.5±9.4 vs. SR: 86.8±14
Scridon (persistent) [21]vWFvWF: AF: 125.2±10.4 vs. SR: 86.8±14
Berge [22]tPAtPA: AF: 15.2±1.8 vs. SR: 15.2±1
Acevedo [23]TAT and sTMTAT: AF: 0.054±0.23 vs. SR: 0.002±0.003sTM: AF: 52.2±111 vs. 44±13
Zorlu [24]D-dimerD-dimer: AF: 1351.75±497.75 vs. SR: 644.25±113.8
Alonso (White) [25]Fibrinogen and vWFFibrinogen: AF: 3.19±0.64 vs. SR: 2.95±0.61vWF: AF: 124.5±46.4 vs. SR: 111.3±42.6
Alonso (African-American) [25]Fibrinogen and vWFFibrinogen: AF: 3.32±0.76 vs. SR: 3.18±0.71vWF: AF: 148.9±67.5 vs. SR: 132.4±55.6
Adamsson Eryd [26]FibrinogenFibrinogen: AF: 3.6±0.8 vs. SR: 3.5±0.8
Fu [27]Fibrinogen and vWFFibrinogen: AF: 3.3±0.9 vs. SR: 3±0.6vWF: AF: 116.5±37.4 vs. SR: 105.6±29.8
Hou (disease control) [28]D-dimer and vWFD-dimer: AF: 327±96 vs. SR: 231±83vWF: AF: 132±38 vs. SR: 126±36
Hou (healthy control) [28]D-dimer and vWFD-dimer: AF: 327±96 vs. SR: 208±80vWF: AF: 132±38 vs. SR: 113±37
Schnabel [29]D-dimer and FibrinogenD-dimer: AF: 451.5±56 vs. SR: 321±43.6Fibrinogen: AF: 3.52±0.15 vs. SR: 3.31±0.15
Letsas (PAF) [30]FibrinogenFibrinogen: AF: 3.74±1.03 vs. SR: 3.6±0.89
Letsas (permanent) [30]FibrinogenFibrinogen: AF: 4.12±0.99 vs. SR: 3.6±0.89
Gartner [31]D-dimerD-dimer: AF: 929.3±105.1 vs. SR: 457.3±108.8
Targonski (PAF and PeAF) [32]FibrinogenFibrinogen: AF: 3.39±0.67 vs. SR: 3.6±0.76
Targonski (Permanent) [32]FibrinogenFibrinogen: AF: 3.91±0.77 vs. SR: 3.6±0.76
Marcus [33]D-dimerD-dimer: AF: 392±91 vs. SR: 408±72
Blann [34]vWFvWF: AF: 180±86 vs. SR: 109±62
Topaloglu (disease control) [35]D-dimer, Fibrinogen, AT-III, tPA, PAI and vWFD-dimer: AF: 384±130 vs. SR: 372±160Fibrinogen: AF: 2.89±0.71 vs. SR: 2.82±0.37AT-III: AF: 98.6±11.1 vs. SR: 97.9±21.2tPA: AF: 8.89±3.5 vs. SR: 5.82±1.79PAI: AF: 1.05±0.97 vs. SR: 1.16±0.7vWF: AF: 134.9±68 vs. SR: 115.7±53.4
Topaloglu (healthy control) [35]D-dimer, Fibrinogen, AT-III, tPA, PAI and vWFD-dimer: AF: 384±130 vs. SR: 19±8.3Fibrinogen: AF: 2.89±0.71 vs. SR: 2.3±0.47AT-III: AF: 98.6±11.1 vs. SR: 82.8±8.6tPA: AF: 8.89±3.5 vs. SR: 7.3±3.7PAI: AF: 1.05±0.97 vs. SR: 1.24±0.65vWF: AF: 134.9±68 vs. SR: 75.1±17
Cecchi (with cerebral ischemic) [36]FibrinogenFibrinogen: AF: 3.68±1.04 vs. SR: 3.07±0.3
Cecchi (without cerebral ischemic) [36]FibrinogenFibrinogen: AF: 4.36±1.22 vs. SR: 3.07±0.3
Turgut (disease control) [37]Fibrinogen and PF1–2Fibrinogen: AF: 3.64±0.86 vs. SR: 3.47±1.1PF1–2: AF: 2.83±0.89 vs. SR: 2.33±0.8
Turgut (healthy control) [37]Fibrinogen and PF1–2Fibrinogen: AF: 3.64±0.86 vs. SR: 2.51±0.61PF1–2: AF: 2.83±0.89 vs. SR: 1.94±0.64
Heeringa [38]Fibrinogen and vWFFibrinogen: AF: 2.32±0.7 vs. SR: 2.32±0.9vWF: AF: 144±32 vs. SR: 138±40.2
Roldan [39]PF1–2PF1–2: AF: 1.41±0.15 vs. SR: 1.05±0.09
Marin (acute AF) [40]D-dimer, vWF and sTMD-dimer: AF: 2350±2680 vs. SR: 390±280vWF: AF: 137±36.9 vs. SR: 86.7±33.2sTM: AF: 12.1±4.1 vs. 5.9±2.7
Marin (chronic AF) [40]D-dimer, vWF and sTMD-dimer: AF: 1120±650 vs. SR: 390±280vWF: AF: 133.1±25 vs. SR: 86.7±33.2sTM: AF: 11.8±4.6 vs. 5.9±2.7
Inoue (with comorbidities) [41]D-dimer and PF1–2D-dimer: AF: 158.6±9.2 vs. SR: 79.1±10.3PF1–2: AF: 0.98±0.05 vs. SR: 1.04±0.04
Inoue (Lone AF) [41]D-dimer and PF1–2D-dimer: AF: 92.1±6.7 vs. SR: 31±7.4PF1–2: AF: 0.79±0.06 vs. SR: 0.82±0.05
Conway [42]Fibrinogen and vWFFibrinogen: AF: 2.65±0.17 vs. SR: 2.72±0.28vWF: AF: 132±26 vs. SR: 125±21
Hatzinikolaou-Kotsakou (PAF) [43]Fibrinogen and vWFFibrinogen: AF: 3.3±0.9 vs. SR: 2.4±0.8vWF: AF: 119±0.9 vs. SR: 104±22
Hatzinikolaou-Kotsakou (persistent) [43]Fibrinogen and vWFFibrinogen: AF: 3.8±0.4 vs. SR: 2.4±0.8vWF: AF: 129±19 vs. SR: 104±22
Hatzinikolaou-Kotsakou (permanent) [43]Fibrinogen and vWFFibrinogen: AF: 4.5±0.6 vs. SR: 2.4±0.8vWF: AF: 158±15 vs. SR: 104±22
Conway [44]Fibrinogen and vWFFibrinogen: AF: 2.83±0.25 vs. SR: 2.67±0.27vWF: AF: 130±25 vs. SR: 126±21
Kamath (PAF and PeAF) [45]D-dimer and FibrinogenD-dimer: AF: 760±195 vs. SR: 637.5±202.5Fibrinogen: AF: 2.9±0.7 vs. SR: 2.6±0.4
Kamath (permanent AF) [45]D-dimer and FibrinogenD-dimer: AF: 1497.5±368.3 vs. SR: 637.5±202.5Fibrinogen: AF: 2.7±0.6 vs. SR: 2.6±0.4
Marin [46]PF1–2PF1–2: AF: 1.61±0.31 vs. SR: 0.94±0.1
Conway [47]Fibrinogen and vWFFibrinogen: AF: 0.8±0.29 vs. SR: 0.79±0.3vWF: AF: 144±32 vs. SR: 138±32
Kamath (PAF) [48]D-dimer and FibrinogenD-dimer: AF: 675.75±151.75 vs. SR: 659.5±185.5Fibrinogen: AF: 2.9±0.7 vs. SR: 2.6±0.5
Kamath (permanent AF) [48]D-dimer and FibrinogenD-dimer: AF: 1552.5±398.3 vs. SR: 659.5±185.5Fibrinogen: AF: 2.7±0.6 vs. SR: 2.6±0.5
Kamath [49]D-dimer and FibrinogenD-dimer: AF: 1085±176.6 vs. SR: 724.25±240.75Fibrinogen: AF: 2.8±0.7 vs. SR: 2.6±0.4
Wang [50]Fibrinogen, tPA and PAIFibrinogen: AF: 3.15±0.76 vs. SR: 3.03±0.63tPA: AF: 12.05±1.85 vs. SR: 8.25±0.96PAI: AF: 23.95±8.1 vs. SR: 19.05±4.1
Li-saw-Hee (PAF) [51]Fibrinogen and vWFFibrinogen: AF: 3.3±0.7 vs. SR: 2.5±0.6vWF: AF: 130±34 vs. SR: 101±30
Li-saw-Hee (PeAF) [51]Fibrinogen and vWFFibrinogen: AF: 2.7±0.8 vs. SR: 2.5±0.6vWF: AF: 106±26 vs. SR: 101±30
Li-saw-Hee (permanent) [51]Fibrinogen and vWFFibrinogen: AF: 3.1±0.9 vs. SR: 2.5±0.6vWF: AF: 143±47 vs. SR: 101±30
Feng [52]Fibrinogen, tPA, PAI and vWFFibrinogen: AF: 3.33±0.53 vs. SR: 3.28±0.65tPA: AF: 11.8±4 vs. SR: 10.5±3.9PAI: AF: 24.2±10.7 vs. SR: 25.7±17.3vWF: AF: 142±46.2 vs. SR: 137±43.4
Topcuoglu [53]PF1–2, TAT, tPA and PAIPF1–2: AF: 2.29±1.25 vs. SR: 1.37±0.87TAT: AF: 10.07±6.04 vs. SR: 6.59±5.12tPA: AF: 23.93±10.17 vs. SR: 21.16±12.72PAI: AF: 37.05±22.32 vs. SR: 31.36±21.5
Mondillo [54]D-dimer, Fibrinogen, AT-III, tPA, PAI, vWF and sTMD-dimer: AF: 458.5±175 vs. SR: 170.25±23.75Fibrinogen: AF: 3.81±1.09 vs. SR: 2.68±0.8AT-III: AF: 99.9±15.8 vs. SR: 103.7±7.1tPA: AF: 20.37±7.8 vs. SR: 9.8±3.21PAI: AF: 15.2±6.2 vs. SR: 9.3±4.8vWF: AF: 164.04±43.8 vs. SR: 93.44±33.04sTM: AF: 39.14±13.2 vs. SR: 26.86±14.6
Giansante [55]D-dimer and Fibrinopeptide-AD-dimer: AF: 347±54 vs. SR: 323.75±46.75Fibrinopeptide-A: AF: 12.9±2 vs. SR: 2.85±0.57
Li-saw-Hee [56]Fibrinogen, vWF and sTMFibrinogen: AF: 2.9±0.9 vs. SR: 2.6±0.8vWF: AF: 137±27 vs. SR: 103±33sTM: AF: 52±17 vs. SR: 44±13
Marin (disease control) [57]D-dimer, AT-III, tPA and PAID-dimer: AF: 533±111.25 vs. SR: 542.02±147.4AT-III: AF: 58.4±32.75 vs. SR: 14.85±4.8tPA: AF: 1.94±0.34 vs. SR: 2.34±0.14PAI: AF: 43.77±8.62 vs. SR: 31.37±9.3
Marin (healthy control) [57]D-dimer, AT-III, tPA and PAID-dimer: AF: 533±111.25 vs. SR: 15.92±6.07AT-III: AF: 58.4±32.75 vs. SR: 10.25±1.1tPA: AF: 1.94±0.34 vs. SR: 3.01±0.8PAI: AF: 43.77±8.62 vs. SR: 7.35±0.9
Li-saw-Hee [58]D-dimer, Fibrinogen, vWF and sTMD-dimer: AF: 54±26 vs. SR: 32±20Fibrinogen: AF: 4.2±0.6 vs. SR: 3.1±0.6vWF: AF: 149±24 vs. SR: 103±30sTM: AF: 27±10 vs. SR: 40±12
Roldan [59]D-dimer, Fibrinogen, AT-III, tPA, PAI and Plasmin-antiplasminD-dimer: AF: 549.38±311.16 vs. SR: 12.3±3.7Fibrinogen: AF: 3.69±0.81 vs. SR: 3.11±0.6AT-III: AF: 62.47±79.46 vs. SR: 10.35±2.9tPA: AF: 2.31±0.9 vs. SR: 2.88±1.58PAI: AF: 42.78±22.85 vs. SR: 8.8±5.04Plasmin-antiplasmin: AF: 275.31±151.69 vs. SR: 232.5±65.7
Tsai [50]PF1–2 and Fibrinopeptide-APF1–2: AF: 4.74±0.49 vs. SR: 2.99±0.24Fibrinopeptide-A: AF: 6±1.3 vs. SR: 1.4±0.3
Minamino [61]D-dimer, Fibrinogen, tPA and PAID-dimer: AF: 160±55 vs. SR: 90±21Fibrinogen: AF: 2.55±0.9 vs. SR: 1.93±0.71tPA: AF: 12.05±5.4 vs. SR: 8.4±1.85PAI: AF: 62.12±33.07 vs. SR: 52±17.4
Kahn [62]FibrinogenFibrinogen: AF: 3.7±0.8 vs. SR: 3.2±1.1
Sohara [63]D-dimer, Fibrinogen and TATD-dimer: AF: 141.7±208.6 vs. SR: 67.2±31.6Fibrinogen: AF: 2.62±0.65 vs. SR: 2.25±0.37TAT: AF: 6.68±5.11 vs. SR: 3.11±1.86
Lip (PAF) [64]D-dimer and FibrinogenD-dimer: AF: 96.75±21.75 vs. SR: 77.5±8.33Fibrinogen: AF: 3.15±0.24 vs. SR: 2.6±0.19
Lip (chronic) [64]D-dimer and FibrinogenD-dimer: AF: 149.5±37.5 vs. SR: 77.5±8.33Fibrinogen: AF: 3.82±0.28 vs. SR: 2.6±0.19
Lip [65]D-dimerD-dimer: AF: 241.25±56.75 vs. SR: 103±22
Mitusch [66]D-dimer, Fibrinogen, PF1–2, TAT, tPA and PAID-dimer: AF: 788±76 vs. SR: 405±46Fibrinogen: AF: 4.5±0.2 vs. SR: 3.1±0.3PF1–2: AF: 1.2±0.1 vs. SR: 1±0.1TAT: AF: 8.5±1.6 vs. SR: 2.5±0.3tPA: AF: 9.6±0.5 vs. SR: 7.2±0.5PAI: 57.9±4.3 vs. SR: 47.7±4.9
Nagao [67]D-dimer and TATD-dimer: AF: 366.3±211.3 vs. SR: 147.2±60.9TAT: AF: 13.81±14.51 vs. SR: 3.47±2.52
Lip [68]D-dimer, Fibrinogen and vWFD-dimer: AF: 105.25±23.8 vs. SR: 77±8.3Fibrinogen: AF: 3.71±0.28 vs. SR: 2.6±0.12vWF: AF: 157.5±14.3 vs. SR: 109.25±11.16
Sohara [69]D-dimer, Fibrinogen and TATD-dimer: AF: 78.6±48.2 vs. SR: 67.2±31.7Fibrinogen: AF: 2.4±0.31 vs. SR: 2.25±0.3TAT: AF: 4.7±3.2 vs. SR: 3.1±1.9
Kumagai [70]D-dimerD-dimer: AF: 150±19 vs. SR: 61±3
Gustafsson (with stroke) [71]D-dimer, Fibrinogen, Fibrinopeptide-A and vWFD-dimer: AF: 279.4±78.12 vs. SR: 169.12±34.3Fibrinogen: AF: 4.4±0.2 vs. SR: 3.82±0.22Fibrinopeptide-A: AF: 5.75±1.25 vs. SR: 4.25±0.7vWF: AF: 17.75±2.25 vs. SR: 14.75±1.27
Gustafsson (without stroke) [71]D-dimer, Fibrinogen, Fibrinopeptide-A and vWFD-dimer: AF: 258.25±67 vs. SR: 169.12±34.3Fibrinogen: AF: 4.5±0.35 vs. SR: 3.82±0.22Fibrinopeptide-A: AF: 4.67±0.5 vs. SR: 4.25±0.7vWF: AF: 17.87±2.62 vs. SR: 14.75±1.27
Occurrence of stroke in AF patients
Skov [72]D-dimer and FibrinogenD-dimer: Stroke: 240±135 vs. without stroke: 250±63Fibrinogen: Stroke: 3.63±0.34 vs. without stroke: 3.77±0.36
Zabczyk [73]D-dimer, Fibrinogen, PAI and sTMD-dimer: Stroke: 306±164.4 vs. without stroke: 234±106.5Fibrinogen: Stroke: 3.24±0.27 vs. without stroke: 3.32±0.22PAI: Stroke: 28.35±7.33 vs. without stroke: 20.3±6.1sTM: Stroke: 7.37±0.87 vs. without stroke: 3.27±0.32
Cecchi [36]FibrinogenFibrinogen: Stroke: 3.68±1.04 vs. without stroke: 4.36±1.22
Loffredo [74]FibrinogenFibrinogen: Stroke: 3.63±1.06 vs. without stroke: 3.14±0.78
Topcuoglu [53]PF1–2, TAT, tPA and PAIPF1–2: Stroke: 2.68±2.84 vs. without stroke: 2.29±1.25TAT: Stroke: 43.88±44.45 vs. without stroke: 10.07±6.04tPA: Stroke: 25.42±27.23 vs. without stroke: 23.93±10.17PAI: Stroke: 53.39±32.91 vs. without stroke: 37.05±22.32
Soncini [75]PF1–2 and TATPF1–2: Stroke: 2.65±0.53 vs. without stroke: 1.41±0.17TAT: Stroke: 26.05±9.22 vs. without stroke: 11.18±4.5
Kahn [62]Fibrinogen and AT-IIIFibrinogen: Stroke: 3.8±0.9 vs. without stroke: 3.7±0.8AT-III: Stroke: 1±0.14 vs. without stroke: 1±0.13
Gustafsson [71]D-dimer, Fibrinogen, AT-III, Fibrinopeptide-A and vWFD-dimer: Stroke: 291.5±156.3 vs. without stroke: 275.5±134Fibrinogen: Stroke: 4.4±0.2 vs. without stroke: 4.5±0.35AT-III: Stroke: 0.92±0.04 vs. without stroke: 0.91±0.01Fibrinopeptide-A: Stroke: 5.75±1.25 vs. without stroke: 4.67±0.57vWF: Stroke: 17.1±2.2 vs. without stroke: 15.6±2.6
Occurrence of Thromboembolism events in AF patients
Zabczyk [73]D-dimer, Fibrinogen and sTMD-dimer: TE: 311±134 vs. without TE: 234±105.5Fibrinogen: TE: 3.4±0.15 vs. without TE: 3.35±0.25sTM: TE: 6.05±1.25 vs. without TE: 3.20±0.35
Roldan [76]PF1–2PF1–2: TE: 1.37±0.4 vs. without TE: 1.31±0.33
Feinberg [77]PF1–2PF1–2: TE: 0.7±0.5 vs. without TE: 0.6±0.4
Pongratz [78]Fibrinogen and AT-IIIFibrinogen: TE: 4.1±1.3 vs. without TE: 3.7±1.5AT-III: TE: 99±13 vs. without TE: 105±22
Black [79]FibrinogenFibrinogen: TE: 6±1.32 vs. without TE: 4.56±1.64
Kumagi [70]D-dimerD-dimer: TE: 196±73 vs. without TE: 140±19
Figure 1

Forest plot of weighted mean difference (WMD) for association between level of D-dimer and occurrence of AF.

Fibrinogen

A total of 43174 cases were included from 58 studies. Patient populations of the included studies ranged from 22 to 11 107 patients. Of 43 174 cases, 5583 were allocated to AF group and 37 591 to the SR group. Mean level of fibrinogen was 3.24 g/L in the AF group and 2.78 g/L in the SR group (details in Tables 1 and 2). Pooled analysis showed that fibrinogen level was significantly higher in patients with AF compared to those with SR with WMD of 0.43 (95% CI: 0.36–0.51; p<0.001, Figure 2) using a random effect model. There was significant heterogeneity among the studies (I2=98.4%; heterogeneity p<0.001).
Figure 2

Forest plot of weighted mean difference (WMD) for association between level of fibrinogen and occurrence of AF.

Prothrombin fragment 1–2 (PF 1–2)

A total of 1047 cases were included from 9 studies, of which 694 cases were allocated to the AF group and 353 to the SR group. The mean level of PF 1–2 was 1.88 nmol/mL in the AF group and 1.35 nmol/mL in the SR group (details in Tables 1 and 2). Pooled analysis revealed that PF 1–2 was significantly higher in the AF group than SR with WMD of 0.53 nmol/mL (95% CI: 0.33–0.73; p<0.001, Figure 3) using a random effect model. There was significant heterogeneity among the studies (I2=99.5%; heterogeneity p<0.001)
Figure 3

Forest plot of weighted mean difference (WMD) for association between level of PF1–2 and occurrence of AF.

Antithrombin III (AT-3)

A total of 300 patients were included from 6 studies. Of them, 153 cases were allocated to the AF group and 147 cases to the SR group. The mean level of AT-III was 79.39 in AF and 53.30 in SR (details in Tables 1 and 2). Pooled analysis revealed that the mean level of AT-III was significantly higher in the AF group compared to the SR group with WMD of 23.90 (95% CI: 7.51–40.29; p=0.004, Supplementary Figure 1) with significant heterogeneity (I2=94.2%; heterogeneity p<0.001).

Thrombin-antithrombin (TAT)

A total of 501 cases were included from 8 studies, of which 335 cases were allocated to the AF group and 166 to the SR group. The mean level of TAT was 10.22 ng/mL in the AF group and 4.61 ng/mL in the SR group (details in Tables 1 and 2). Pooled analysis revealed that level of TAT was significantly higher in the AF group compared to the SR group with WMD of 5.47 ng/mL (95% CI: 1.77–9.18; p=0.004, Supplementary Figure 2) using a random effect model. There was significant heterogeneity among the studies (I2=99.7%; heterogeneity p<0.001).

Association of fibrinolytic markers with AF

Tissue-type plasminogen activator (t-PA)

A total of 4326 cases were included from 14 studies. Patient populations of the included studies ranged from 36 to 3212 patients. From 4326 cases, 533 were allocated to the AF group and 3793 to the SR group. Mean level of t-PA was 10.97 ng/mL in the AF group and 8.61 ng/mL in the SR group (details in Tables 1 and 2). Pooled assessment analysis indicated that t-PA in patients with AF was significantly higher compared to those with SR with WMD of 2.13 (95% CI: 1.04–3.21; p<0.001, Figure 4) using a random effect model. Significant heterogeneity was observed among the studies (I2=98.3%; heterogeneity p<0.001).
Figure 4

Forest plot of weighted mean difference (WMD) for association between level of t-PA and occurrence of AF.

Plasminogen activator inhibitor (PAI)

A total of 4267 cases were included from 15 studies, of which 540 cases were in the AF group and 3727 in the SR group. The mean level of PAI was 30.59 ng/mL in AF and 19.58 ng/mL in SR group (details in Tables 1 and 2). Pooled analysis revealed that the level of PAI was significantly higher in the AF group compared to the SR group with WMD of 11.44 ng/mL (95% CI: 6.83–16.05; p<0.001, Figure 5) with significant heterogeneity (I2=99.4%; heterogeneity p<0.001).
Figure 5

Forest plot of weighted mean difference (WMD) for association between level of PAI and occurrence of AF.

Fibrinopeptide-A

A total of 336 cases were included from 6 studies, whereas 148 cases were allocated to the AF group and 188 to the SR group. The mean level of fibrinopeptide-A was 7.33 ng/ml in AF and 3.18 ng/ml in SR (details in Tables 1 and 2). Pooled analysis showed that the level of fibrinopeptide-A was statistically higher in the AF group compared to SR with WMD of 4.13 ng/mL (95% CI: 0.67–7.60; p=0.01, Supplementary Figure 3) with significant heterogeneity (I2=99.6%; heterogeneity p<0.001).

Association of endothelial markers with AF

von Willebrand factor (vWF)

A total of 18 057 cases were enrolled to the analysis from 32 studies, of which 2607 cases were allocated to the AF group and 15450 to the SR group. The mean level of vWF was 132.38 IU/dL in the AF group and 104.27 IU/dL in the SR group (details in Tables 1 and 2). Pooled analysis revealed a higher level of vWF in patients with AF than in patients with SR with WMD of 27.01 (95% CI: 19.79–34.23; p<0.001, Figure 6) using a random effect model. There was significant heterogeneity among the studies (I2=98.7%; heterogeneity p<0.001).
Figure 6

Forest plot of weighted mean difference (WMD) for association between level of vWF and occurrence of AF.

Soluble thrombomodulin (sTM)

A total of 591 cases were included from 7 studies. From all cases, 351 were allocated to the AF group and 240 to the SR group. The mean level of sTM was 25.96 ng/mL in the AF group and 22.04 ng/mL in the SR group (details in Tables 1 and 2). Pooled analysis indicated that sTM was significantly higher in the AF group compared to the SR group with WMD of 3.92 (95% CI: 0.53–7.32; p<0.001, Supplementary Figure 4) using a random effect model. There was significant heterogeneity among the studies (I2=91.2%; heterogeneity p<0.001).

Related clinical adverse events of AF

Association of coagulation, fibrinolytic, and endothelial markers with thromboembolic events

Six studies reported the association of markers with thromboembolic events (Table 3). D-dimer, fibrinogen, and PF 1–2 levels were investigated in at least 2 studies and were included in the meta-analysis (Table 2). AT-III and sTM levels were reported in only 1 study and thus were not included in the analysis. Pooled analysis revealed that the level of D-dimer (number of studies=2, WMD of 60.67, 95% CI: 28.61 to 92.73; p<0.001 and I2=0%; heterogeneity p=0.59, Supplementary Figure 5) was significantly higher in patients with thromboembolic events than in patients without thromboembolic events. Pooled analysis showed that the level of fibrinogen (number of studies=3, WMD of 0.61, 95% CI: −0.30 to 1.53; p=0.19 and I2=92.5%; heterogeneity p<0.001, Supplementary Figure 6), and the level of PF1–2 (number of studies=2, WMD of 0.08, 95% CI: −0.06 to 0.22; p=0.18 and I2=0%; heterogeneity p=0.83, Supplementary Figure 7) were not significantly different whether they suffered from thromboembolic events or not.
Table 3

Characteristics of included studies for meta-analysis of association of biomarkers and clinical adverse events related to AF.

First AuthorCountry and yearStudy designNumberMean ageAC in patients with adverse eventsAC in patients without adverse eventsAdverse eventsNOS
Skov [72]Denmark-2014Case-control17971.6100%100%Stroke8
Zabczyk [73]Poland-2011Case-control627881.8%72.5%Stroke and thromboembolic event8
Cecchi [36]Italy-2006Case-control15674.4100%100%Stroke7
Loffredo [74]Italy-2005Case-control16372.370%63.4%Stroke8
Topcuoglu [53]Turkey-2001Case-control3963.6Stroke7
Soncini [75]Italy-1998Case-control3271.5Stroke7
Kahn [62]Canada-1997Case-control7572.7100%100%Stroke7
Gustafsson [71]Sweden-1990Case-control4070Stroke8
Roldan [76]Spain-2003Case-control19172.3100%100%Thromboembolic event8
Feinberg [77]UK-1999Cohort726Thromboembolic event8
Pongratz [78]Germany-1997Case-control6065.7Thromboembolic event6
Black [79]Australia-1993Case-control13550%28%Thromboembolic event8
Kumagi [70]Japan-1990Case-control49Thromboembolic event7

Association of coagulation, fibrinolytic, and endothelial markers with stroke

Eight studies investigated the association of hemostatic markers with stroke (Table 3). D-dimer, fibrinogen, PF1–2, TAT, PAI, and AT-III were examined in at least 2 studies and were included in the meta-analysis (Table 2). Fibrinopeptide-A, tPA, vWF, and sTM levels were reported in only 1 study and were not included in the analysis. Pooled assessment analysis indicated that the level of PF 1–2 (number of studies=2, WMD of 1.06, 95% CI: 0.39 to 1.74; p=0.002 and I2=36.4%%; heterogeneity p=0.21, Supplementary Figure 8), level of TAT (number of studies=2, WMD of 22.28, 95% CI: 4.16 to 40.39; p=0.016 and I2=74.5%; heterogeneity p<0.04, Supplementary Figure 9), and level of PAI (number of studies=2, WMD of 8.60, 95% CI: 4.12 to 13.09; p<0.001 and I2=0%; P-heterogeneity=0.36, Supplementary Figure 10) were significantly higher in patients with stoke as compared to patients without stroke. Pooled analysis showed that the levels of D-dimer (number of studies=3, WMD of 8.08, 95% CI: −32.80 to 48.96; p=0.69 and I2=4.7%%; heterogeneity p=0.35, Supplementary Figure 11), fibrinogen (number of studies=6, WMD of 0.02, 95% CI: −0.22 to 0.25; p=0.88 and I2=79.9%%; heterogeneity p<0.001, Supplementary Figure 12), and AT-III (number of studies=2, WMD of 0.01, 95% CI: −0.01 to 0.03; p=0.51 and I2=0%%; heterogeneity p=0.39, Supplementary Figure 13) did not significantly differ between patients with stroke and patients without stroke.

Publication bias, subgroup analysis, and meta-regression

Begg’s tests suggested that there might be publication bias for studies examining levels of D-dimer, fibrinogen, AT-III, and vWF (Supplementary Figures 14–23). Extra details of each study, subgroup analysis, and meta-regression are presented in Supplementary Tables 2 and 3, respectively.

Discussion

For years, finding the pathophysiological mechanisms involved in AF has been an important research area in cardiology and cardiac surgery [80-83]. A proposed mechanism leading to an increased incidence of AF is coagulation and prothrombotic state [80-83]. Investigators believe that procoagulant and prothrombotic states might be more expressed in patients with chronic AF as compared to those with SR [80-83]. In the present study, we investigated a set of coagulation biomarkers to closely examine this possible pathophysiology of AF. D-dimer is a byproduct of the degeneration of fibrin and reflects thrombin and fibrin turnover [84]. D-dimer is one of the surrogate markers for a hypercoagulable state which is one component of Virchow’s triad [84]. The results of the present study revealed that the level of D-dimer was significantly higher in AF patients compared to those with SR. Generally, increased level of D-dimer is directly associated with an increased incidence of AF; however, it should be noted that there is a significant heterogeneity in our results. The subgroup analysis based on the year of publication, geographic area, design of the studies, age, sex, risk factors of diabetes and hypertension, number of cases, and chronic or non-chronic AF indicated that D-dimer was always considerably higher in AF groups compared with SR groups, despite heterogeneity among studies. A subgroup analysis reported that both paroxysmal and permanent AF had higher levels of D-dimer and the type of AF was not considered a factor of heterogeneity. Fibrinogen is an acute-phase protein synthesized in the liver, and higher levels are associated with increased risk of cardiovascular diseases [85]. Our results also demonstrate that the level of fibrinogen was considerably higher in the AF group as compared to the SR group. A direct relationship between the level of fibrinogen and the incidence of AF was confirmed; however, this relationship was also associated with a justifiable heterogeneity. The analyses performed on coagulation markers PF1–2, TAT, and AT-III also indicated that the level of these markers was significantly higher in AF groups as compared to SR groups. The results of our study also showed that the type of AF could be a heterogeneity factor in the meta-analysis of D-dimer level. According to the analysis of the available data in our study, the level of D-dimer was strongly and directly related to the occurrence of thromboembolism in AF patients, while fibrinogen and PF1–2 were not. Other coagulation markers, in which no association with stroke and thromboembolism was reported, did not have sufficient data and thus no analysis was carried out. Another proposed mechanism for the incidence of AF is fibrinolytic activity. PAI is a direct inhibitor of the plasminogen activation system, whereas its interaction with the adhesive glycoprotein plays a role in tissue remodeling [86]. Increased levels of PAI have been associated with an increased risk for coronary artery stenosis and acute coronary syndrome [86]. Our findings suggest a significant direct association between increased level of PAI and the incidence of AF, as patients with AF showed higher levels of PAI compared to those with SR. Sorted analyses in terms of the year of publication, study design, number of cases, age, sex, diabetes, and hypertension indicated that the level of PAI in the AF group had constantly been higher than in the SR group. None of the above-mentioned criteria appeared to be a factor of heterogeneity. The results of this study predict that with the current heterogeneity in analysis on the level of PAI, history of MI and type of AF (chronic or non-chronic) could be considered factors of heterogeneity. Our results showed that the level of tPA in the AF group was considerably higher than in the SR group. There was a direct correlation between the incidence of AF and the level of tPA from laboratory and clinical studies, although statistically there was a notable heterogeneity. A subgroup analysis revealed that history of MI, type of AF, and geographical area may be considered factors of heterogeneity. Fibrinopeptide-A is also a marker of fibrinolytic activity, and we found that it was clearly higher in the AF group as compared to the SR group. However, we could not find factors of heterogeneity in the subgroup analysis. Owing to insufficient studies on alfa-2 antiplasmin, plasmin-antiplasmin, and urokinase-type plasminogen activator inhibitor, analyzing these markers was not feasible. Although based on the results, this fact is understandable and verifiable from laboratory and clinical studies, not finding a definite factor of heterogeneity of the results might be explained by the fact that other factors had affected the results of the published studies in recent years that have not been taken into account or not been reported on by their authors. Regarding the association of the level of PAI with stroke in AF patients, our results suggest a significant relationship between increased level of PAI and increased risk of stroke. Another mechanism which needs to be examined in AF patients is endothelial activity. Increased levels of vWF have been found in inflammatory and atherosclerotic vascular diseases that are usually associated with damaged endothelium [87]. The pooled results of our study indicate that the level of vWF was significantly higher in AF patients as compared with the SR group. The results of subgroup analysis suggested that in all types of AF, including paroxysmal, persistent, and permanent, and also in terms of chronic or non-chronic AF, the level of vWF was statistically and clinically higher in the AF group. According to the subgroup analysis, geographic area, design of the studies, and number of cases could be defined as factors of heterogeneity. The findings of this study affirmed that STM, as another marker of endothelial activity, had a significant influence on the incidence of AF, as the level of STM considerably higher in AF patients compared with SR patients. Generally, increased endothelial activity appears to be associated with higher incidence of AF, which is confirmed statistically and through laboratory studies. We conducted a subgroup analysis based on cardiovascular risk factors, whereas one of the most significant cardiac risk factors affecting our results was history of MI. Also, DM, HTN, and smoking were not considered factors of heterogeneity. Lip et al. argued that using anticoagulants could reduce the levels of D-dimer and PF1–2 in AF patients; therefore, differences in the use of anticoagulants in various studies might be considered confounding factors [68]. In this study, we defined codes for using anticoagulants. Performing a subgroup analysis, we found that on the levels of AT3, tPA, PAI, and STM, the available data about the status of using anticoagulants were confounding factors which possibly could play a part in the incidence of heterogeneity. Heterogeneity is higher in meta-analyses of non-experimental studies, which can be caused by several factors, such as: 1) many confounding factors, 2) less controlled bias, and 3) different definition of outcomes. Meta-regression was performed on the levels of D-dimer, fibrinogen, PAI, and vWF that had greater number of studies than other markers and could be analyzed based on regression. According to the results of meta-regression on the level of D-dimer, difference in the design of studies, type of AF, and difference in geographical area of the study appeared to be factors of heterogeneity. For the level of fibrinogen, the year of publication (before or after 2000) and geographical area of the study were factors. For the level of vWF, difference in the design of studies and geographical area of the study were factors. For the level of PAI, difference in using anticoagulants was a factor.

Conclusions

Generally, considering the results of this study, we can strongly claim that prothrombotic state has a critical role as a precipitating mechanism in the incidence of AF and clinical complications of thromboembolism and stroke. The levels of coagulation, fibrinolytic, and endothelial markers have been reported to be significantly higher in AF patients than in SR patients. We believe that several other interventions may affect the association of these biomarkers with the incidence of AF; however, they have not been taken into account or mentioned in the series of past and recent studies. High heterogeneity is not the end of trying to find the relation between effective markers in predicting AF, but definitely points out that in future the authors are required to converge the quality of performing studies by observing the factors of heterogeneity and other confounding factors as described in the present study. Finally, emphasizing the association of coagulation, fibrinolytic, and endothelial markers with the incidence of AF and its clinical outcomes, and defining the factors of heterogeneity using subgroup analysis and meta-regression, we believe that in meta-analysis of the relationship of the levels of biomarkers with the incidence of AF, there are real-world associations with heterogeneity. Efforts should be made to find and introduce these associations as well as factors of heterogeneity that affect the results. Forest plot of weighted mean difference (WMD) for association between level of AT-III and occurrence of AF. Forest plot of weighted mean difference (WMD) for association between level of TAT and occurrence of AF. Forest plot of weighted mean difference (WMD) for association between level of fibrinopeptide and occurrence of AF. Forest plot of weighted mean difference (WMD) for association between level of sTM and occurrence of AF. Forest plot of weighted mean difference (WMD) for association between level of D-dimer and occurrence of thromboembolism. Forest plot of weighted mean difference (WMD) for association between level of fibrinogen and occurrence of thromboembolism. Forest plot of weighted mean difference (WMD) for association between level of PF1–2 and occurrence of thromboembolism. Forest plot of weighted mean difference (WMD) for association between level of PF1–2 and occurrence of stroke. Forest plot of weighted mean difference (WMD) for association between level of TAT and occurrence of stroke. Forest plot of weighted mean difference (WMD) for association between level of PAI and occurrence of stroke. Forest plot of weighted mean difference (WMD) for association between level of D-dimer and occurrence of stroke. Forest plot of weighted mean difference (WMD) for association between level of fibrinogen and occurrence of stroke. Forest plot of weighted mean difference (WMD) for association between level of AT-III and occurrence of stroke. Funnel plot for publication bias of studies investigating D-dimer. Funnel plot for publication bias of studies investigating fibrinogen. Funnel plot for publication bias of studies investigating PF1–2. Funnel plot for publication bias of studies investigating of TAT. Funnel plot for publication bias of studies investigating AT-III. Funnel plot for publication bias of studies investigating fibrinopeptide-A. Funnel plot for publication bias of studies investigating t-PA. Funnel plot for publication bias of studies investigating PAI. Funnel plot for publication bias of studies investigating vWF. Funnel plot for publication bias of studies investigating sTM. Included, and excluded studies. Extra details of characteristics of each study for exploration of heterogeneity factors. Subgroup-analysis and meta-regression.
Supplementary Table 1

Included, and excluded studies.

Clinical outcomes and biomarkersStudies were identified and screened [n]Studies were excluded according to title, abstract or full text [n]Studies were included [n]
Fibrinogen31527540 approved articles with totally 58 enrolled data for meta-analysis
D-dimer23812130 approved articles with totally 40 enrolled data for meta-analysis
PF1–286797 approved articles with totally 9 enrolled data for meta-analysis
AT-III98944 approved articles with totally 6 enrolled data for meta-analysis
TAT1271207 approved articles with totally 8 enrolled data for meta-analysis
t-PA43742611 approved articles with totally 14 enrolled data for meta-analysis
PAI918011 approved articles with totally 15 enrolled data for meta-analysis
Alpha-2 antiplasmin1818
Fibrinopeptide-A21183 approved articles with totally 4 enrolled data for meta-analysis
u-PA2929
Plasmin-antiplasmin22211 approved articles with
vWF18521 approved articles with totally 32 enrolled data for meta-analysis
sTM37316 approved articles with totally 7 enrolled data for meta-analysis
Supplementary Table 2

Extra details of characteristics of each study for exploration of heterogeneity factors.

First AuthorGeographic areaTotal NTotal ageTotal maleTotal DMTotal HTNTotal MITotal diureticTotal ACEITotal. statinTotal BBAC-codeChronic or notCS
Negreva [9]European10359.6750.454.868.96NDND28.1656.80534.971Acute14.5
Amdur [10]North America376258.954.5549.886.7ND64.6569.85ND56.14No detectionND
Yusuf (disease control) [11]Asian6531.542.85NDNDNDNDNDNDND1No detectionND
Yusuf (healthy control) [11]Asian6530.05538.55NDNDNDNDNDNDND1No detectionND
Drabik (persistent) [12]European9760.164.952048.8517.35ND52.2553.1560.64Acute22.5
Drabik (PAF) [12]European916055.1516.446.0526.65ND54.0547.4557.254Acute20
Borgi [13]Africa69NDNDNDNDNDNDNDNDND5No detectionND
Oneal (with comorbidities) [14]North America64769.55432.570NDNDND29.5ND4No detection15
Oneal (with comorbidities) [14]North America88364.532.529.554.5NDNDND30ND4No detection14
Erdogan [15]European6769.5549.2751065ND1853.5ND43.33Chronic6
Chen (without comorbidities) [16]Asian16253.69561.031531.5NDNDNDNDND4AcuteND
Chen (with comorbidities) [16]Asian20755.84564.213.535.5NDNDNDNDND4AcuteND
Schnabel [17]European499860.0554.510.1561.958.3NDNDNDND5No detection15.3
Wei-Hong Ma [18]Asian1055872.250100NDNDNDNDND2No detectionND
Xu (without comorbidities) [19]Asian11566.8550.4537.453.1NDND42.629.5543.554Chronic38.5
Xu (with comorbidities) [19]Asian11567.97551.336.557.5NDND40.826.0540.954Chronic31.2
Distelmaier [20]North America19873.5612460.525NDNDNDND5AcuteND
Scridon (PAF) [21]European6955.578.5739.5NDND18.513.5ND3Acute13
Scridon (persistent) [21]European535578.5735.5NDND2415.5ND3Acute13
Berge [22]European1897571848ND192134.5284No detectionND
Acevedo [23]South America150NDNDNDNDNDNDNDNDND1No detectionND
Zorlu [24]European15069.5621633NDND75.5ND761No detectionND
Alonso (White) [25]North America1110755.752.2512.0534.856.6NDNDNDND1No detection26.7
Alonso (African-American) [25]North America375154.841.226.0563.65NDNDNDNDND1No detection32
Adamsson Eryd [26]European603147.251004.86NDNDNDND5No detection48
Fu [27]Asian16954.4563.5NDNDNDNDND12.96.14No detection42.5
Hou (disease control) [28]Asian5264.8557.60NDNDND40.35ND11.454Acute26.9
Hou (healthy control) [28]Asian5265.357.60NDNDND21.15ND7.654Acute26.9
Schnabel [29]North America312062.0552.5ND38NDNDNDNDND5No detectionND
Letsas (PAF) [30]European9364.459660.5NDND4315.5345acuteND
Letsas (permanent) [30]European8966.659.51163NDND52.513.535.55chronicND
Gartner [31]Australia25059.4565.5948.5NDNDNDNDND4No detectionND
Targonski (PAF and PeAF) [32]European5663.567.744.7569.6ND67.796.6587.385.4412.4
Targonski (Permanent) [32]European7369.366.433.372.2ND78.0590.8570.689.2411.3
Marcus [33]North America9717087.522.565.552ND5759.5ND5No detection15
Blann [34]European8264.562.75ND27ND16.519ND18.53No detection12.6
Topaloglu (disease control) [35]European4634.5ND00NDNDNDNDND5No detectionND
Topaloglu (healthy control) [35]European3836ND00NDNDNDNDND5No detectionND
Cecchi (with cerebral ischemic) [36]European19273.560.27.2545.95ND18.0527.36.856.83No detection30.1
Cecchi (without cerebral ischemic) [36]European2247359.356.447.5ND20.527.057.38.053No detection25.9
Turgut (disease control) [37]European5566.1144.717.467.6NDNDNDNDND4No detectionND
Turgut (healthy control) [37]European4666.5643.953.8536.55NDNDNDNDND4No detectionND
Heeringa [38]European48677.55117.52522.531.65NDND16.555No detection20.9
Roldan [39]European265NDNDNDNDNDNDNDNDND4No detectionND
Marin (acute AF) [40]European4863.55008.38.3ND10.4ND8.34AcuteND
Marin (chronic AF) [40]European4863.547.914.5512.56.25ND6.25ND4.154ChronicND
Inoue (with comorbidities) [41]Asian251NDNDNDNDNDNDNDNDND5No detectionND
Inoue (Lone AF) [41]Asian106NDNDNDNDNDNDNDNDND5No detectionND
Conway [42]European14768627.526.513.5NDNDNDND3chronic16
Hatzinikolaou-Kotsakou (PAF) [43]European355977.258.313.8513.85NDNDNDND5Acute20.5
Hatzinikolaou-Kotsakou (persistent) [43]European346073.55.8520.58517.6NDNDNDND5Acute20.8
Hatzinikolaou-Kotsakou (permanent) [43]European3761.576.15522.515NDNDNDND5Chronic24.2
Conway [44]European7467.570.29.45271.35NDNDNDND5Acute11.2
Kamath (PAF and PeAF) [45]European6263.551.6NDNDNDNDNDNDND1AcuteND
Kamath (permanent AF) [45]European1246652.65NDNDNDNDNDNDND1ChronicND
Marin [46]European8070.55519.5526.5NDNDND44ChronicND
Conway [47]European48677.551.058.310.5958.6NDNDNDND1No detection10.3
Kamath (PAF) [48]European586348.2356.8524.13.4NDNDNDND4Acute5.1
Kamath (permanent AF) [48]European1166552.255.1530.456.85NDNDNDND4Chronic5.1
Kamath [49]European1437063.2NDNDNDNDNDNDND1No detection5.9
Wang [50]Asian32126051.6523.6540.63.65NDNDNDND5No detection32.6
Li-saw-Hee (PAF) [51]European436477.32.1510.856.5NDNDNDND3Acute13.4
Li-saw-Hee (PeAF) [51]European436477.252.15134.3NDNDNDND3Acute11.5
Li-saw-Hee (permanent) [51]European436577.256.5223.915.2NDNDNDND3Chronic11.5
Feng [52]North America21462.1573.512.853623.25NDNDNDND6No detection16.1
Topcuoglu [53]European3662.3561.8713.542.5NDNDNDNDND1No detection20
Mondillo [54]European8066.9582.85NDNDNDNDNDNDND3Chronic33.7
Giansante [55]European10563.555.678.529.25NDNDNDNDND1Acute35.6
Li-saw-Hee [56]European1126777.53.8512.511.55NDNDNDND1Chronic13.3
Marin (disease control) [57]European4253.517.350NDNDNDNDNDND1No detectionND
Marin (healthy control) [57]European38NDND0NDNDNDNDNDND1No detectionND
Li-saw-Hee [58]European505920NDNDNDNDNDNDND5Chronic20
Roldan [59]European5662ND0NDNDNDNDNDND1ChronicND
Tsai [50]Asian1116474.45NDNDNDNDNDNDND4ChronicND
Minamino [61]Asian906373.312.523.5NDNDNDND14.55ChronicND
Kahn [62]North America81NDNDNDNDNDNDNDNDND1ChronicND
Sohara [63]Asian3059.1NDNDNDNDNDNDNDND1AcuteND
Lip (PAF)[64]European18859.8557.8NDNDNDNDNDNDND1Acute30
Lip (chronic) [64]European21461.856.37NDNDNDNDNDNDND1Chronic33
Lip [65]European77NDNDNDNDNDNDNDNDND1ChronicND
Mitusch [66]European977151.352567NDNDNDNDND1No detectionND
Nagao [67]Asian3679.9544.575NDNDNDNDNDNDND1No detectionND
Lip [68]European24561.1553.3NDNDNDNDNDNDND5ChronicND
Sohara [69]Asian22NDNDNDNDNDNDNDNDND1AcuteND
Kumagai [70]Asian9462.548.15NDNDNDNDNDNDND1ChronicND
Gustafsson (with stroke) [71]European6077NDNDNDNDNDNDNDND1No detection30
Gustafsson (without stroke) [71]European6077NDNDNDNDNDNDNDND1No detection25
Supplementary Table 3

Subgroup-analysis and meta-regression.

SubgroupStudies (N)WMD (95% CI)I-squared and P-value respectivelyP-value of meta-regression
D-dimer

Year of publication0.845
 >200025243.7 (209.1 to 278.2)99.8% and 0.001
 ≤200016137.3 (103.6 to 171.1)99.1% and 0.001

Geographic area0.008
 Asian13144.4 (108.8 to 180.1)99.7% and 0.001
 European24242.5 (199.4 to 285.7)99% and 0.001
 Africa10.83 (0.28 to 1.38)
 North American265.11 (−62.93 to 193.1)98.2% and 0.001
 South American
 Australia1472 (429.3 to 514.6)

Design of study0.001
 Cohort35176.1 (153.7 to 198.4)99.7% and 0.001
 Case-control6290.2 (189.5 to 390.8)99.8% and 0.001

Number of population0.49
 >300265.1 (−62.9 to 193.1)99.9% and 0.001
 ≤30039204.4 (179.9 to 229)99.4% and 0.001

Mean Age0.92
 >60 years26226.7 (188.6 to 264.8)99.7% and 0.001
 ≤60 years9160.7 (77 to 244.4)99.6% and 0.001

Male0.94
 >70%3113.7 (22.2 to 205.1)98.9% and 0.001
 ≤70%26227.8 (187.8 to 267.8)99.6% and 0.001

Diabetes mellitus0.47
 >30%2290 (271.6 to 308.4)73.3% and 0.001
 ≤30%20264.8 (205.7 to 323.8)99.7% and 0.001

Hypertension0.96
 >70%196.1 (47.2 to 144.7)
 ≤70%19258.6 (194.7 to 321.9)99.8% and 0.001

History of myocardial infarction0.95
 >20%1−0.16 (−0.42 to 0.107)
 ≤20%4761.7 (140.3 to 1383.2)98.2% and 0.001

Anti-coagulant status codes0.91
 118215.3 (172 to 258.6)98.9% and 0.001
 2
 32154 (−110.2 to418.4)97.6% and 0.001
 411331.3 (225.5 to 437.1)99.6% and 0.001
 51091.1 (56 to 126.3)99.9% and 0.001
 6

AF0.015
 Chronic14261.3 (208.9 to 313.8)99.6% and 0.001
 Non-chronic11104.7 (29.6 to 179.8)99.4% and 0.001

Type of AF0.254
 Paroxysmal519.6 (12.5 to 26.8)0.0% and 0.78
 Persistent
 Permanent4512.5 (135.3 to 889.8)99% and 0.001

Cigarette smoking0.132
 >30%7111.1 (106.1 to 116)99.7% and 0.001
 ≤30%8−0.136 (−0.403 to 0.131)98.3% and 0.001

Fibrinogen

Year of publication0.02
 >2000460.29 (0.24 to 0.35)96.1% and 0.001
 ≤2000120.75 (0.54 to 0.96)96.4% and 0.001

Geographic area0.04
 Asian90.35 (0.24 to 0.47)95% and 0.001
 European400.53 (0.38 to 0.68)97.9% and 0.001
 Africa
 North American90.10 (0.02 to 0.19)97.3% and 0.001
 South American
 Australia

Design of study0.44
 Cohort150.22 (0.15 to 0.29)98.2% and 0.001
 Case-control430.52 (0.36 to 0.69)97.4% and 0.001

Number of population0.053
 >300110.15 (0.05 to 0.25)98.4% and 0.001
 ≤300470.52 (0.39 to 0.64)98% and 0.001

Mean Age0.94
 >60 years430.48 (0.37 to 0.59)98.7% and 0.001
 ≤60 years130.26 (0.17 to 0.34)95% and 0.001

Male0.468
 >70%130.56 (0.35 to 0.77)93.9% and 0.001
 ≤70%370.40 (0.31 to 0.48)98.9% and 0.001

Diabetes mellitus0.97
 >30%60.40 (0.11 to 0.69)96.5% and 0.001
 ≤30%370.35 (0.28 to 0.43)97.3% and 0.001

Hypertension0.60
 >70%30.17 (0.004 to 0.35)87.1% and 0.001
 ≤70%400.36 (0.29 to 0.43)97.5% and 0.001

History of myocardial infarction0.58
 >20%40.01 (−0.11 to 0.13)75.6% and 0.006
 ≤20%160.42 (0.26 to 0.58)96.5% and 0.001

Anti-coagulant status codes0.26
 1160.45 (0.23 to 0.68)98.5% and 0.001
 2
 380.62 (0.19 to 1.05)95.3% and 0.001
 4160.20 (0.14 to 0.25)92.7% and 0.001
 5170.53 (0.33 to 0.73)98.6% and 0.001
 610.05 (−0.13 to 0.23)

AF0.23
 Chronic180.7 (0.42 to 0.97)97.6% and 0.001
 Non-chronic160.24 (0.16 to 0.33)92.6% and 0.001

Type of AF0.43
 Paroxysmal80.38 (0.18 to 0.58)83.9% and 0.78
 Persistent40.42 (0.11 to 0.74)90.2% and 0.001
 Permanent90.54 (0.21 to 0.87)93.6% and 0.001

Cigarette smoking0.47
 >30%110.51 (0.47 TO 0.56)98.3% and 0.001
 ≤30%260.09 (0.78 to 0.103)96.5% and 0.001

Prothrombotic Factor 1–2

Year of publication
 >200070.79 (−0.39 to 1.98)98.1% and 0.001
 ≤200020.97 (−0.54 to 2.49)99.8% and 0.001

Geographic area
 Asian30.52 (0.23 to 0.82)99.7% and 0.001
 European60.47 (0.34 to 0.64)94.8% and 0.001
 Africa
 North American
 South American
 Australia

Design of studyAll of them are case–control
 Cohort
 Case-control

Number of population
 >30010.36 (0.33 to 0.39)
 ≤30080.46 (0.29 to 0.62)99.2% and 0.001

Mean Age
 >60 years60.82 (0.26 to 1.37)99% and 0.001
 ≤60 years

Male
 >70%11.75 (1.61 to 1.88)
 ≤70%50.58 (0.25 to 0.91)95.5% and 0.001

Diabetes mellitus
 >30%
 ≤30%50.58 (0.25 to 0.91)95.5% and 0.001

Hypertension
 >70%
 ≤70%50.38 (0.17 to 0.59)99.7% and 0.001

History of myocardial infarction
 >20%
 ≤20%10.67 (0.57 to 0.76)

Anti-coagulant status codes
 120.46 (−0.21 to 1.42)72.9% and 0.05
 2
 3
 450.84 (0.31 to 1.36)99% and 0.001
 52−0.04 (−0.07 to 0.01)77.1% and 0.03
 6

AF
 Chronic21.20 (0.15 to 2.26)99.4% and 0.001
 Non-chronic

Type of AF
 Paroxysmal
 Persistent
 Permanent

Cigarette smokingNo Data
 >30%
 ≤30%

Thrombin anti thrombin

Year of publication
 >200045.80 (−1.006 to 12.78)99.7% and 0.001
 ≤200044.57 (1.77 to 7.36)85.4% and 0.001

Geographic area
 Asian56.93 (2.18 to 11.68)98.1% and 0.001
 European25.46 (3.43 to 7.48)41.4% and 0.19
 Africa
 North American10.05 (0.01 to 0.093)
 South American
 Australia

Design of studyAll of them are case–control
 Cohort
 Case-control

Number of populationAll of them are less than 300 cases
 >300
 ≤300

Mean Age
 >60 years35.79 (3.63 to 7.96)37.5% and 0.202
 ≤60 years37.89 (2.09 to 13.68)98.8% and 0.001

Male
 >70%
 ≤70%57.87 (4.43 to 11.32)98.3% and 0.001

Diabetes mellitus
 >30%
 ≤30%25.46 (3.43 to 7.48)41.4% and 0.191

Hypertension
 >70%
 ≤70%25.46 (3.43 to 7.48)41.4% and 0.191

History of myocardial infarctionNo Data
 >20%
 ≤20%

Anti-coagulant status codesAll of them are Code–1
 1
 2
 3
 4
 5
 6

AF
 Chronic
 Non-chronic22.47 (0.55 to 4.39)27.4% and 0.24

Type of AF
 Paroxysmal52.47 (0.55 to 4.39)27.4% and 0.24
 Persistent
 Permanent

Cigarette smokingNo sufficient data
 >30%
 ≤30%

Anti-thrombin III

Year of publication
 >200034.26 (−8.76 to 17.28)91% and 0.001
 ≤2000346.78 (36.8 to 56.70)0% and 0.833

Geographic areaAll of them are European
 Asian
 European
 Africa
 North American
 South American
 Australia

Design of studyAll of them are case–control
 Cohort
 Case-control

Number of populationAll of studies have less than 300 cases
 >300
 ≤300

Mean Age
 >60 years222.65 (−32.07 to 77.37)94.2% and 0.001
 ≤60 years318.96 (0.16 to 37.65)91.1% and 0.001

Male
 >70%1−3.80 (−8.98 to 1.38)
 ≤70%143.55 (28.29 to 58.80)

Diabetes mellitus
 >30%
 ≤30%530.21 (11.99 to 48.42)91.3% and 0.001

Hypertension
 >70%
 ≤70%28.65 (−6.11 to 23.43)85.3% and 0.009

History of myocardial infarctionNo data
>20%
≤20%

Anti-coagulant status codes
 1346.78 (36.85 to 56.70)0.0% and 0.833
 2
 31−3.80 (−8.98 to 1.38)
 4
 528.65 (−6.11 to 23.43)85.3% and 0.009
 6

AF
 Chronic222.65 (−32.07 to 77.37)94.2% and 0.001
 Non-chronic

Type of AF
 Paroxysmal19.6 (12.5 to 26.8)
 Persistent
 Permanent1−3.80 (−8.98 to 1.38)

Cigarette smokingNo sufficient data
 >30%
 ≤30%

Fibrinopeptide-A

Year of publication
 >2000110.05 (9.37 to 10.72)
 ≤200032.17 (−0.72 to 5.07)99.4% and 0.001

Geographic area
 Asian14.60 (4.28 o 4.91)
 European33.98 (−1.33 to 9.30)99.7% and 0.001
 Africa
 North American
 South American
 Australia

Design of studyAll of studies are case–control
 Cohort
 Case-control

Number of populationAll of studies have less than 300 cases
 >300
 ≤300

Mean AgeAll of studies have total age higher than 60 years
 >60 years
 ≤60 years

Male
 >70%14.60 (4.28 o 4.91)
 ≤70%110.05 (9.37 to 10.72)

Diabetes mellitus
 >30%
 ≤30%110.05 (9.37 to 10.72)

Hypertension
 >70%
 ≤70%110.05 (9.37 to 10.72)

History of myocardial infarctionNo data
 >20%
 ≤20%

Anti-coagulant status codes
 133.98 (−1.33 to 9.30)99.7% and 0.001
 2
 3
 414.60 (4.28 to 4.97)
 5
 6

AF
 Chronic14.60 (4.28 to 4.97)
 Non-chronic110.05 (9.37 to 10.72)

Type of AF
 Paroxysmal110.05 (9.37 to 10.72)–
 Persistent
 Permanent

Cigarette smoking
 >30%25.19 (4.78 to 5.63)99.7% and 0.001
 ≤30%10.42 (0.11 to 0.72)

Tissue plasminogen activator

Year of publication
 >200093.095 (1.52 to 4.66)95.5% and 0.001
 ≤200050.709 (−0.908 to 2.32)99.2% and 0.001

Geographic area
 Asian23.78 (3.30 to 4.26)0.0% and 0.86
 European111.86 (0.69 to 3.03)98.4% and 0.001
 Africa
 North American11.30 (0.013 to 2.58)
 South American
 Australia

Design of study
 Cohort21.89 (−1.82 to 5.62)98.2% and 0.001
 Case-control122.16 (0.98 to 3.34)98.2% and 0.001

Number of population
 >30013.80 (3.30 to 4.29)
 ≤300131.95 (0.88 to 3.02)98.1% and 0.001

Mean Age
 >60 years102.69 (1.56 to 3.83)96.1% and 0.001
 ≤60 years31.29 (−1.14 to 3.74)88.8% and 0.001

Male
 >70%43.67 (0.40 to 6.94)96.3% and 0.001
 ≤70%62.34 (0.56 to 4.13)99.2% and 0.001

Diabetes mellitus
 >30%
 ≤30%131.60 (0.52 to 2.68)98.3% and 0.001

Hypertension
 >70%
 ≤70%102.41 (1.47 to 3.51)93.5% and 0.001

History of myocardial infarction
 >20%21.98 (0.81 to 3.14)53.3% and 0.143
 ≤20%23.68 (3.26 to 4.10)0.0% and 0.396

Anti-coagulant status codes
 150.21 (−1.50 to 1.93)99.1% and 0.001
 2
 3110.57 (8.055 to 13.085)
 431.94 (−0.36 to 4.26)96.8% and 0.001
 543.48 (2.76 to 4.19)22.6% and 0.275
 611.30 (0.013 to 2.58)

AF
 Chronic34.43 (−1.25 to 10.12)97.6% and 0.001
 Non-chronic22.99 (2.11 to 3.87)51% and 0.154

Type of AF
 Paroxysmal12.50 (1.53 to 3.46)
 Persistent13.40 (2.62 to 4.17)
 Permanent110.57 (8.055 to 13.085)

Cigarette smoking
 >30%24.05 (3.56 to 4.56)96.3% and 0.001
 ≤30%42.73 (2.18 to 3.27)61.6% and 0.051

Plasminogen activator inhibitor

Year of publication0.28
 >2000106.69 (1.79 to 11.59)99.5% and 0.001
 ≤2000520.72 (7.68 to 33.75)97.4% and 0.001

Geographic area0.30
 Asian415.82 (0.49 to 31.14)99.5% and 0.001
 European1010.07 (6.93 to 13.21)98.4% and 0.001
 Africa
 North American11.009 (−3.05 to 5.07)
 South American
 Australia

Design of study0.97
 Cohort14.490 (2.71 to 7.08)
 Case-control1411.28 (6.70 to 15.86)99.4% and 0.001

Number of population0.98
 >30014.490 (2.71 to 7.08)
 ≤3001411.28 (6.70 to 15.86)99.4% and 0.001

Mean Age0.96
 >60 years96.99 (4.31 to 9.67)91.7% and 0.001
 ≤60 years510.36 (2.19 to 18.52)99.8% and 0.001

Male0.18
 >70%136.42 (32.41 to 40.42)
 ≤70%811.28 (3.14 to 19.42)99.5% and 0.001

Diabetes mellitus
 >30%
 ≤30%128.93 (6.03 to 11.88)98.1% and 0.001

Hypertension
 >70%
 ≤70%93.34 (1.30 to 5.39)96% and 0.001

History of myocardial infarction0.97
 >20%21.55 (−3.66 to 6.78)84.5% and 0.011
 ≤20%24.16 (3.29 to 5.03)0.0% and 0.474

Anti-coagulant status codes0.014
 1721.28 (11.09 to 31.47)98.9% and 0.001
 2
 314.20 (1.09 to 7.31)
 423.95 (3.27 to 4.64)0.0% and 0.831
 541.08 (−0.357 to 2.534)87.1% and 0.001
 61−1.50 (−5.53 to 2.53)

AF0.97
 Chronic316.58 (−1.97 to 35.14)95.6% and 0.001
 Non-chronic23.80 (3.16 to 4.44)0.0% and 0.448

Type of AF0.26
 Paroxysmal13.88 (2.87 to 4.88)
 Persistent14.03 (3.08 to 4.97)
 Permanent15.90 (3.49 to 8.31)

Cigarette smoking0.95
 >30%25.35 (3.73 to 6.97)0.0% and 0.568
 ≤30%43.80 (3.13 to 4.48)56.9% and 0.07

von Willebrand Factor

Year of publication0.98
 >20002827.50 (19.43 to 35.56)96.3% and 0.001
 ≤2000423.67 (9.80 to 37.53)99.5% and 0.001

Geographic area0.01
 Asian415.19 (7.19 to 23.19)15.4% and 0.315
 European2530.91 (22.26 to 39.56)99% and 0.001
 Africa
 North American313.23 (10.42 to 16.04)0.0% and 0.423
 South American
 Australia

Design of study0.05
 Cohort511.70 (6.62 to 16.78)66.4% and 0.018
 Case-control2729.97 (21.49 to 38.44)98.9% and 0.001

Number of population0.10
 >300410.32 (5.54 to 15.09)63.8% and 0.041
 ≤3002829.78 (21.48 to 38.08)98.8% and 0.001

Mean Age0.703
 >60 years2227.88 (18.70 to 37.07)99.1% and 0.001
 ≤60 years1023.95 (16.11 to 31.79)85.4% and 0.001

Male0.44
 >70%1327.82 (18.23 to 37.41)87.9% and 0.001
 ≤70%1528.74 (17.73 to 39.74)98% and 0.001

Diabetes mellitus
 >30%
 ≤30%2525.34 (16.93 to 33.76)95.6% and 0.001

Hypertension0.48
 >70%216.95 (−1.44 to 35.35)57% and 0.127
 ≤70%2427.42 (18.17 to 36.13)96.7% and 0.001

History of myocardial infarction0.97
 >20%320.98 (−14.49 to 0.56.4)98.7% and 0.001
 ≤20%1426.61 (14.62 to 38.60)97.2% and 0.001

Anti-coagulant status codes0.81
 169.66 (5.59 to 13.74)93.5% and 0.001
 2125 (11.14 to 38.85)
 3833.09 (18.72 to 47.47)90.9% and 0.001
 4734.96 (24.55 to 45.38)92.4% and 0.001
 5930.16 (13.83 to 46.49)95.9% and 0.001
 615.0 (−9.75 to 19.75)

AF0.65
 Chronic843 (29.03 to 56.97)93% and 0.001
 Non-chronic1226.73 (16.88 to 36.58)94.7% and 0.001

Type of AF0.75
 Paroxysmal429.17 (7.99 to 50.34)96.5% and 0.001
 Persistent525.02 (6.51 to 43.52)96.1% and 0.001
 Permanent443.01 (10.43 to 75.59)95.6% and 0.001

Cigarette smoking0.98
 >30%43.53 (2.48 to 4.58)95.8% and 0.001
 ≤30%2114.60 (13.67 to 15.53)98.7% and 0.001

Soluble thrombomodulin

Year of Publication
 >200064.36 (2.79 to 5.93)86.8% and 0.001
 ≤20001−13.0 (−19.12 to −6.87)

Geographic area
 Asian
 European63.81 (0.35 to 7.27)92.6% and 0.001
 Africa
 North American
 South American11.81 (1.03 to 2.58)
 Australia

Design of study
 Cohort12.02 (1.88 to 2.15)
 Case-control63.87 (0.31 to 7.43)90.6% and 0.001

Number of populationAll of studies have less than 300 cases
 >300
 ≤300

Mean Age
 >60 years46.04 (2.88 to 9.21)89.5% and 0.001
 ≤60 years2−5.16 (−19.87 to 9.54)95.7% and 0.001

Male
 >70%26.84 (0.02 to 13.65)86.8% and 0.001
 ≤70%41.68 (−2.13 to 5.50)94.3% and 0.001

Diabetes mellitus
 >30%
 ≤30%45.10 (2.03 to 8.17)91.2% and 0.001

Hypertension
 >70%
 ≤70%45.10 (2.03 to 8.17)91.2% and 0.001

History of myocardial infarction
 >20%
 ≤20%36.18 (4.78 to 7.58)0.0% and 0.794

Anti-coagulant status codes
 134.36 (−0.52 to 9.25)56.9% and 0.09
 2
 3112.28 (6.09 to 18.46)
 426.02 (4.61 to 7.50)0.0% and 0.839
 51−5.27 (−19.76 to 9.21)
 6

AF
 Chronic43.38 (−5.27 to 12.04)92.6% and 0.001
 Non-chronic22.85 (1.52 to 4.17)88.7% and 0.001

Type of AF
 Paroxysmal12.02 (1.88 to 2.15)
 Persistent
 Permanent112.28 (6.09 to 18.46)

Cigarette smoking
 >30%112.28 (6.09 to 18.46)
 ≤30%32.01 (1.88 to 2.14)56.3% and 0.101
  86 in total

1.  Biochemical predictors of cardiac rhythm at 1 year follow-up in patients with non-valvular atrial fibrillation.

Authors:  Mónica Acevedo; Ramón Corbalán; Sandra Braun; Jaime Pereira; Ilse González; Carlos Navarrete
Journal:  J Thromb Thrombolysis       Date:  2012-02-03       Impact factor: 2.300

Review 2.  Yin and yang of the plasminogen activator inhibitor.

Authors:  Jerzy Jankun; Ewa Skrzypczak-Jankun
Journal:  Pol Arch Med Wewn       Date:  2009-06

3.  Hemostatic state and atrial fibrillation (the Framingham Offspring Study).

Authors:  D Feng; R B D'Agostino; H Silbershatz; I Lipinska; J Massaro; D Levy; E J Benjamin; P A Wolf; G H Tofler
Journal:  Am J Cardiol       Date:  2001-01-15       Impact factor: 2.778

4.  Effect of heart rate control on coagulation status in patients of rheumatic mitral stenosis with atrial fibrillation--A pilot study.

Authors:  Jamal Yusuf; Mayank Goyal; Saibal Mukhopadhyay; Vimal Mehta; Sunil Dhaiya; Renu Saxena; Vijay Trehan
Journal:  Indian Heart J       Date:  2015-11-23

5.  Plasma levels of coagulation and fibrinolysis markers in acute ischemic stroke patients with lone atrial fibrillation.

Authors:  M A Topcuoglu; D Haydari; S Ozturk; O I Ozcebe; O Saribas
Journal:  Neurol Sci       Date:  2000-08       Impact factor: 3.307

6.  Progressive endothelial damage revealed by multilevel von Willebrand factor plasma concentrations in atrial fibrillation patients.

Authors:  Alina Scridon; Nicolas Girerd; Lucia Rugeri; Emilie Nonin-Babary; Philippe Chevalier
Journal:  Europace       Date:  2013-05-19       Impact factor: 5.214

7.  Plasma von Willebrand factor, soluble thrombomodulin, and fibrin D-dimer concentrations in acute onset non-rheumatic atrial fibrillation.

Authors:  F Marín; V Roldán; V E Climent; A Ibáñez; A García; P Marco; F Sogorb; G Y H Lip
Journal:  Heart       Date:  2004-10       Impact factor: 5.994

8.  Platelet activation is not involved in acceleration of the coagulation system in acute cardioembolic stroke with nonvalvular atrial fibrillation.

Authors:  T Nagao; M Hamamoto; A Kanda; T Tsuganesawa; M Ueda; K Kobayashi; T Miyazaki; A Terashi
Journal:  Stroke       Date:  1995-08       Impact factor: 7.914

9.  Blood count in new onset atrial fibrillation after acute myocardial infarction - a hypothesis generating study.

Authors:  Klaus Distelmaier; Gerald Maurer; Georg Goliasch
Journal:  Indian J Med Res       Date:  2014-04       Impact factor: 2.375

10.  Multiple biomarkers and atrial fibrillation in the general population.

Authors:  Renate B Schnabel; Philipp S Wild; Sandra Wilde; Francisco M Ojeda; Andreas Schulz; Tanja Zeller; Christoph R Sinning; Jan Kunde; Karl J Lackner; Thomas Munzel; Stefan Blankenberg
Journal:  PLoS One       Date:  2014-11-17       Impact factor: 3.240

View more
  17 in total

1.  Cardiovascular resistance to thrombosis in 13-lined ground squirrels.

Authors:  Alison Bonis; Leah Anderson; Gaëlle Talhouarne; Emily Schueller; Jenna Unke; Catherine Krus; Jordan Stokka; Anna Koepke; Brittany Lehrer; Anthony Schuh; Jeremiah J Andersen; Scott Cooper
Journal:  J Comp Physiol B       Date:  2018-10-13       Impact factor: 2.200

2.  Optimum Risk Assessment for Stroke in Atrial Fibrillation: Should We Hold the Status Quo or Consider Magnitude Synergism and Left Atrial Appendage Anatomy?

Authors:  James A Reiffel
Journal:  Arrhythm Electrophysiol Rev       Date:  2017-12

Review 3.  Prediction of New-Onset and Recurrent Atrial Fibrillation by Complete Blood Count Tests: A Comprehensive Systematic Review with Meta-Analysis.

Authors:  Alexander Weymann; Sadeq Ali-Hasan-Al-Saegh; Anton Sabashnikov; Aron-Frederik Popov; Seyed Jalil Mirhosseini; Tong Liu; Mohammadreza Lotfaliani; Michel Pompeu Barros de Oliveira Sá; William L L Baker; Senol Yavuz; Mohamed Zeriouh; Jae-Sik Jang; Hamidreza Dehghan; Lei Meng; Luca Testa; Fabrizio D'Ascenzo; Umberto Benedetto; Gary Tse; Luis Nombela-Franco; Pascal M Dohmen; Abhishek J Deshmukh; Cecilia Linde; Giuseppe Biondi-Zoccai; Gregg W Stone; Hugh Calkins; Integrated Meta-Analysis Of Cardiac Surgery And Cardiology-Group Imcsc-Group
Journal:  Med Sci Monit Basic Res       Date:  2017-05-12

4.  Combinational Biomarkers for Atrial Fibrillation Derived from Atrial Appendage and Plasma Metabolomics Analysis.

Authors:  Songqing Lai; Xiumeng Hua; Ran Gao; Liang Zeng; Jiangping Song; Jichun Liu; Jing Zhang
Journal:  Sci Rep       Date:  2018-11-16       Impact factor: 4.379

5.  The association of high D-dimer level with high risk of ischemic stroke in nonvalvular atrial fibrillation patients: A retrospective study.

Authors:  Li-Rui You; Mei Tang
Journal:  Medicine (Baltimore)       Date:  2018-10       Impact factor: 1.817

Review 6.  A Review of Biomarkers for Ischemic Stroke Evaluation in Patients With Non-valvular Atrial Fibrillation.

Authors:  Luxiang Shang; Ling Zhang; Yankai Guo; Huaxin Sun; Xiaoxue Zhang; Yakun Bo; Xianhui Zhou; Baopeng Tang
Journal:  Front Cardiovasc Med       Date:  2021-07-01

7.  Comprehensive Assessment of the Psychological Burden for Students in Physical Education Classes in Chinese Universities.

Authors:  Xuemei Wei; Zhen Liu
Journal:  Med Sci Monit Basic Res       Date:  2018-05-15

Review 8.  Evidence for Inflammation as a Driver of Atrial Fibrillation.

Authors:  Xiaoxu Zhou; Samuel C Dudley
Journal:  Front Cardiovasc Med       Date:  2020-04-29

9.  Preventive Effect of Preoperative Vitamin D Supplementation on Postoperative Atrial Fibrillation.

Authors:  Levent Cerit; Barçın Özcem; Zeynep Cerit; Hamza Duygu
Journal:  Braz J Cardiovasc Surg       Date:  2018 Jul-Aug

Review 10.  Inflammation and atrial fibrillation: A comprehensive review.

Authors:  Panagiotis Korantzopoulos; Konstantinos P Letsas; Gary Tse; Nikolaos Fragakis; Christos A Goudis; Tong Liu
Journal:  J Arrhythm       Date:  2018-06-04
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