Literature DB >> 28496093

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

Alexander Weymann1, Sadeq Ali-Hasan-Al-Saegh2, Anton Sabashnikov3,4, Aron-Frederik Popov3,5, Seyed Jalil Mirhosseini6, Tong Liu7, Mohammadreza Lotfaliani6, Michel Pompeu Barros de Oliveira Sá8,9, William L L Baker10, Senol Yavuz11, Mohamed Zeriouh3,4, Jae-Sik Jang12, Hamidreza Dehghan13, Lei Meng7, Luca Testa14, Fabrizio D'Ascenzo15, Umberto Benedetto16, Gary Tse17, Luis Nombela-Franco18, Pascal M Dohmen1,19, Abhishek J Deshmukh20, Cecilia Linde21, Giuseppe Biondi-Zoccai22,23, Gregg W Stone24, Hugh Calkins25, Integrated Meta-Analysis Of Cardiac Surgery And Cardiology-Group Imcsc-Group26.   

Abstract

BACKGROUND Atrial fibrillation (AF) is one of the most critical and frequent arrhythmias precipitating morbidities and mortalities. The complete blood count (CBC) test is an important blood test in clinical practice and is routinely used in the workup of cardiovascular diseases. This systematic review with meta-analysis aimed to determine the strength of evidence for evaluating the association of hematological parameters in the CBC test with new-onset and recurrent AF. MATERIAL AND METHODS We conducted a meta-analysis of observational studies evaluating hematologic parameters in patients with new-onset AF and recurrent AF. A comprehensive subgroup analysis was performed to explore potential sources of heterogeneity. RESULTS The literature search of all major databases retrieved 2150 studies. After screening, 70 studies were analyzed in the meta-analysis on new-onset AF and 23 studies on recurrent AF. Pooled analysis on new-onset AF showed platelet count (PC) (weighted mean difference (WMD)=WMD of -26.39×10^9/L and p<0.001), mean platelet volume (MPV) (WMD=0.42 FL and p<0.001), white blood cell (WBC) (WMD=-0.005×10^9/L and p=0.83), neutrophil to lymphocyte ratio (NLR) (WMD=0.89 and p<0.001), and red blood cell distribution width (RDW) (WMD=0.61% and p<0.001) as associated factors. Pooled analysis on recurrent AF revealed PC (WMD=-2.71×109/L and p=0.59), WBC (WMD=0.20×10^9/L (95% CI: 0.08 to 0.32; p=0.002), NLR (WMD=0.37 and p<0.001), and RDW (WMD=0.28% and p<0.001). CONCLUSIONS Hematological parameters have significant ability to predict occurrence and recurrence of AF. Therefore, emphasizing the potential predictive role of hematological parameters for new-onset and recurrent AF, we recommend adding the CBC test to the diagnostic modalities of AF in clinical practice.

Entities:  

Mesh:

Year:  2017        PMID: 28496093      PMCID: PMC5439535          DOI: 10.12659/msmbr.903320

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


Background

Atrial fibrillation (AF) is one of the most critical and frequent arrhythmias precipitating morbidities and mortalities such as hemodynamic instability, thromboembolism, and stroke, increasing hospital re-admissions and, consequently, health care costs. In general, AF negatively affects patient quality of life [1]. AF alone is associated with 1.5% to 1.9% increase in risk of mortality in a wide spectrum of ages in both genders [2]. Moreover, the situation is likely to worsen since the number of people with AF is expected to double by 2050 [2,3]. The pathophysiological mechanism in AF is highly complex and multifactorial [3]. Prothrombotic state, inflammation, and oxidative stress may play important roles in the occurrence of supraventricular arrhythmia [4]. Introduction of practical and available diagnostic methods and their wider use allows for better identification of patients with new-onset or recurrent AF [3,4]. Traditionally, the major focus in diagnosis and management of AF has been patient medical history, examination, and detection of AF and paroxysmal AF (PAF) using cardiac monitoring. Complete blood count (CBC) is an important blood test routinely used in clinical practice for workup of cardiovascular diseases [5]. The relationship between blood parameters in CBC tests and clinical outcomes in patients with ST-segment elevation myocardial infarction has been well documented [5]. However, the diagnostic performance of blood parameters for AF, alone and in combination with other diseases, is still unknown. Various studies have reported the association of hematological parameters with new-onset and recurrent AF, but the data have been largely inconclusive. This systematic review with meta-analysis sought to determine the strength of evidence in terms of the potential association between a large number of hematologic parameters that can be easily obtained using the CBC test and new-onset and recurrent AF.

Material and Methods

Literature search

A comprehensive literature search was conducted in electronic scientific databases (Medline/PubMed, Embase, Web of Science, and Google Scholar) from their inception through November 30, 2016 to identify relevant studies on the association between blood parameters in CBC tests and new-onset and recurrent AF. Predefined search terms were as follows: “white blood cell count”, “WBC”, “leucocyte”, “neutrophil to lymphocyte ratio”, “NLR”, “platelet count”, “mean platelet volume”, “MPV”, “platelet distribution width” “PDW”, “red blood cell count”, “RBC count”, “red blood cell distribution width”, “RDW”, and “atrial fibrillation” or “supraventricular arrhythmia”. No restrictions were applied regarding sample size of studies, language, and time of publication. To assess additional studies not indexed in common databases, all retrieved references of the enrolled studies, recent published review articles, and meta-analyses were also checked.

Study selection

Studies were included in the analysis when they met the following criteria: 1) human subjects; 2) cohort or case-control studies; 3) comparative studies between AF and non-AF-cohorts in terms of blood parameters; 4) studies comparing patients with recurrent AF (re-occurrence of AF in patients with history of treatment with anti-arrhythmic or electrophysiological interventions for AF) with those with non-recurrent AF focusing on blood parameters. Manuscripts that did not undergo peer-review, abstracts from congress presentations only, and gray literature were not included.

Primary and secondary blood parameters

Platelet count, MPV, PDW, WBC count, NLR, RBC count, and RDW were considered primary blood parameters. MCV, MCHC, HCT, and Hb were defined as secondary parameters.

Data extraction and outcome measures

Six investigators (S.A-H-S, A.S, S.Y, T.L, M-P. S, and J-S. J) independently extracted the data. Discrepancies were resolved by a consensus standardized abstraction checklist used for recording data in each included study. Disagreements were discussed and resolved by senior authors (A.W, A.F-P, G.B.Z, G.D.S and H.C). The following items were extracted from the included studies: author name; publication year; country; study design; sample size; mean age; gender; coexistent cardiovascular diseases, and risk factors, such as diabetes mellitus, hypertension, and history of myocardial infarction; percentage of used anticoagulants; AF type; and details of blood parameters. In order to examine heterogeneity among trials, subgroup analyses of disparities in patients’ characteristics were carried out for: (1) the era of publication (pre-2000 vs. post-2000); (2) geographical area (Asia, Europe, Africa, North-America, South-America, and Oceania); (3) study design (case-control vs. cohort); (4) sample size of studies (≤300 vs. >300); (5) mean age (≤60 vs. >60 years); (6) percentage of male patients (≤70% vs. >70%); (7) presence of diabetes (≤30% vs. >30%); (8) presence of hypertension (≤70% vs. >70%); (9) cigarette smoking (≤30% vs. >30%); (10) presence of myocardial infarction (≤20% vs. >20%); (11) use of cardiovascular drugs, such as diuretics, angiotensin converting enzyme inhibitors, statins and beta-blockers (for each: ≤70% vs. >70%); (12) AF-classification (chronic vs. non-chronic); (13) type of AF (paroxysmal, persistent, permanent); and (12) anticoagulation (code-1: not receiving anticoagulants in both groups; code-2: all participants receiving anticoagulants in both groups; code-3: range of percentages between both groups >50%; code-4: range of percentages between both groups <50%; code-5: no information available about anticoagulation in both groups; and code-6: anticoagulation information not available for 1 group only).

Homogenization of extracted data

Continuous data are expressed as mean ± standard deviation (SD). For studies reporting interquartile ranges, the mean was estimated according to the formula [minimum+maximum+2(median)]/4 and SD was calculated based on the formula (maximum–minimum)/4 for groups with sample sizes of n ≤70 and (maximum–minimum)/6 for sample sizes of >70 [6].

Quality assessment and statistical analysis

The Newcastle-Ottawa scale was independently used by 3 investigators (S.A-H-S, M.G, and L.M) to assess the quality of studies [7]. Total scores ranged from 0 (worst quality) to 9 (best quality) for case-control or cohort studies. Data were analyzed by STATA 11.0 using METAN and METABIAS modules. For non-categorical data, pooled effect size measured was the weighted mean difference (WMD) with 95% CI. P value of <0.1 for Q test or I2 >50% showed significant heterogeneity among the studies. Heterogeneity among trials was examined by applying a random-effects model when indicated. Publication bias was assessed using the Begg tests. P value of <0.05 was considered statistically significant.

Results

Literature search strategy and included studies

Overall, 2150 studies were retrieved from the literature search and screened databases. We excluded 1179 studies (63.55%) after detailed evaluation during the first review due to unnecessary information (n=750), inadequate report of endpoints of interest (n=370), or report of non-matched data based on mean ±SD or median [minimum–maximum] (n=59). In total, 971 potentially relevant full-text articles were screened, with 70 studies being analyzed in the meta-analysis on new-onset AF and 23 studies on recurrent AF (Supplementary Table 1) [8-77].

Association of hematologic parameters with new-onset AF

Platelet count

A total of 6468 cases were selected from 48 studies, of which 3098 were allocated to the AF group and 3370 to the SR group. Mean platelet count was 236.9×109/L in the AF group and 239.9×109/L in the SR group (details in Tables 1 and 2). Using a random-effects model, pooled analysis revealed that the mean platelet count was considerably lower in patients with AF than in patients with SR, with a WMD of −26.39×109/L (95% CI: −27.80 to −24.99; p<0.001, Figure 1). Significant heterogeneity was observed among the studies (I2=92.9%; heterogeneity p<0.001).
Table 1

Characteristics of included studies for meta-analysis of association of hematologic parameters with AF.

First AuthorYearCountryDesignN-AFN-SRAge-AFAge-SRMale-AFMale-SRAC-AFAC-SRType of AFNOS
Occurrence of AF
Balci (Male subjects) [8]2016TurkeyCase-control1817NDND100100NDNDND8
Balci (Female subjects) [8]2016TurkeyCase-control6588NDND00NDNDND8
Gurses [9]2016TurkeyCase-control868656.656.451.253.5NDNDCombined types9
Karatas [10]2016TurkeyCase-control4058165.756.47075100100ND8
Korantzopoulos [11]2016GreeceCase-control326978754746600Combined types9
Akdag [12]2015TurkeyCase-control965263.664.5645654.16NDCombined types9
Akyuz [13]2015TurkeyCase-control40506361.572.5722014Combined types7
Chavaria [14]2015USACohort4025070.660.76584NDNDND6
Drabik (Persistent AF) [15]2015PolandCase-control475060.859.465.956438.326Persistent9
Drabik (Paroxysmal AF) [15]2015PolandCase-control415060.659.446.36451.226Paroxysmal9
Acet (Paroxysmal AF) [16]2014TurkeyCase-control71636361.14246NDNDParoxysmal9
Acet (Persistent and permanent AF) [16]2014TurkeyCase-control636364.661.14146NDNDCombined types9
Arik (effective INR) [17]2014TurkeyCase-control12512370.468.941.639.8NDNDPermanent8
Arik (ineffective INR) [17]2014TurkeyCase-control1251237068.93639.8NDNDPermanent8
Distelmaier [18]2014USACase-control6613273.573.56161NDNDND7
Erdogan (with normal ventricular rate) [19]2014TurkeyCase-control343370.568.647.0551.5166.60Permanent10
Erdogan (with high ventricular rate) [19]2014TurkeyCase-control30336968.646.651.5183.30Permanent10
Zheng [20]2014ChinaCase-control11710064.3759.157.2660NDNDND8
Xu (without thrombotic events) [21]2014ChinaCohort575865.196750.95050.915.5ND7
Xu (with thrombotic events) [21]2014ChinaCohort575868.956752.65049.115.5ND7
Gungor [22]2014TurkeyCase-control1176048.346.160.65575.28.3Combined types9
Liu [23]2014ChinaCase-control133101NDNDNDNDNDNDParoxysmal8
Sarikaya [24]2014TurkeyCase-control636371.0970.9747.852.2NDNDND8
Sonmez [25]2014TurkeyCase-control5233707034.6139.3959.6136.36Persistent8
Ulu [26]2014TurkeyCase-control2532NDNDNDNDNDNDND7
Berge [27]2013NorwayCohort63126757571.4270.63833Combined types9
Ertas (without stroke) [28]2013TurkeyCase-control872469384458580ND6
Ertas (with stroke) [28]2013TurkeyCase-control392471383658510ND6
Gungor [29]2013TurkeyCase-control707042.242.968.564.3NDNDCombined types7
Turgut [30]2013TurkeyCase-control8181646251532820ND7
Jaremo (healthy control) [31]2013SwedenCohort5824696679.354.1612.060ND8
Jaremo (disease control) [31]2013SwedenCohort5872697479.356.912.0641.66ND8
Sahin [32]2013TurkeyCase-control727265.0164.7248.251.3NDNDPersistent7
Tekin [33]2013TurkeyCase-control10711274733140NDNDND7
Turfan (without stroke) [34]2013TurkeyCohort7758635657.451.744.30ND7
Turfan (with stroke) [34]2013TurkeyCohort6358695652.451.741.30ND7
Feng [35]2012ChinaCase-control18518965.965.762.760.876.883.1Combined types8
Liu (Paroxysmal AF) [36]2012ChinaCohort505164.364.464611000Paroxysmal8
Liu (Persistent AF) [36]2012ChinaCohort565167.264.461611000Persistent8
Yoshizaki [37]2012JapanCohort2415274667577NDNDND8
Hayashi (Paroxysmal AF) [38]2011JapanCase-control141353.162.89392100100Paroxysmal7
Hayashi (Chronic AF) [38]2011JapanCase-control141360.162.89392100100ND7
Fu [39]2011ChinaCase-control907954.154.87057220Combined types8
Liu [40]2011ChinaCase-control5040161.854.95448.87NDNDCombined types8
Letsas (Paroxysmal AF) [41]2010GreeceCase-control454867.461.36256NDNDParoxysmal9
Letsas (Permanent AF) [41]2010GreeceCase-control414871.961.36356NDNDPermanent9
Luan (Persistent AF) [42]2010ChinaCase-control272662.0444.4655.5646.15NDNDPersistent8
Luan (Paroxysmal AF) [42]2010ChinaCase-control292657.5244.4658.6246.15NDNDParoxysmal8
Alberti [43]2009ItalyCase-control173468.160.847.0547.0500Persistent7
Dai [44]2009ChinaCase-control24228056.0950.0479.869.6NDNDCombined types8
Ichiki [45]2009JapanCase-control4824544981.2579.16NDNDParoxysmal9
Yao (Persistent AF) [46]2009ChinaCase-control727855.452.879.274.415.37.7Persistent7
Yao (Paroxysmal AF) [46]2009ChinaCase-control2617853.952.875.574.412.37.7Paroxysmal7
Colkesen [47]2008TurkeyCase-control10387634555215014Paroxysmal8
Choudhury (disease control) [48]2008UKcase-control1217162.5864.04767237.247.4ND6
Choudhury (healthy control) [48]2008UKcase-control1215662.5862.03766837.20ND6
Pirat [49]2007TurkeyCase-control182153465548NDNDND7
Yip [50]2006TaiwanCase-control622066.265.366.16058.10ND9
Kamath (Paroxysmal and persistent AF) [51]2003UKCase-control3131616661.341.900Combined types6
Kamath (Permanent AF) [51]2003UKCase-control9331666663.441.900Permanent6
Kamath (Paroxysmal AF) [52]2002UKCase-control2929616555.1741.3737.90Paroxysmal7
Kamath (Permanent AF) [52]2002UKCase-control8729656563.2141.3737.90Permanent7
Kamath [53]2002UKCase-control9350707062.364600ND6
Kamath [54]2002UKCase-control342373ND50ND00ND6
Peverill [55]2001AustraliaCase-control7984634783.585.7NDNDND8
Kahn (without stroke) [56]1997CanadaCase-control5031ND65ND38.700ND7
Kahn (with stroke) [56]1997CanadaCase-control2511ND65ND63.600ND7
Lip [57]1996UKCase-control512670.4NDNDND00ND6
Gustafsson (without stroke) [58]1990SwedenCase-control20207777NDND00ND8
Gustafsson (with stroke) [58]1990SwedenCase-control20207777NDND00ND8
Recurrence of AF
Gurses [9]2016TurkeyCase-control127457.556.166.748.7NDNDCombined types9
Hongliang Li [59]2016ChinaCase-control356962634047.851.452.2Paroxysmal7
Yanagisawa (without heart failure) [60]2016JapanCohort26940961.161.17775NDNDCombined types7
Yanagisawa (with heart failure) [60]2016JapanCohort423764.2636287NDNDCombined types7
Aksu [61]2015TurkeyCohort74265.0154.295748NDNDParoxysmal9
Gurses [62]2015TurkeyCohort7022956.355.158.643.748.5734.11Combined types9
Karavelioglu [63]2015TurkeyCohort8713165.86335.6346.56NDNDParoxysmal7
Wen [64]2015ChinaCohort156063.6763.57NDNDNDNDCombined types9
Guo Xueyuan [65]2014ChinaCohort12425549.649.7372.974.2NDNDND9
Aribas [66]2013TurkeyCohort461036159NDND100100Persistent9
Bing Li [67]2013ChinaCohort80208565872.569.7NDNDParoxysmal9
Canpolat [68]2013TurkeyCohort6019157.353.16049.7NDNDND8
Im [69]2013South KoreaCohort10739256.556.373.873.5NDNDCombined types9
Xiao-nan HE [70]2013ChinaCohort106224605962.470.2NDNDParoxysmal6
Ferro [71]2012ItalyCohort509470.371.65261100100Persistent8
Smit [72]2012NetherlandCohort3070636573.374.3NDNDPersistent7
Wang (Paroxysmal AF) [73]2012ChinaCohort4162585732.537.1NDNDParoxysmal7
Wang (Persistent AF) [73]2012ChinaCohort3025535273.376NDNDPersistent7
Liu (Paroxysmal AF) [74]2011ChinaCohort1958555784.267100100Paroxysmal8
Liu (Persistent AF) [74]2011ChinaCohort172755.250.988.281.5100100Persistent8
Vizzardi [75]2009ItalyCohort466069695963NDNDPersistent7
Letsas [76]2009GermanyCohort284453.355.88677NDNDCombined types7
Korantzopoulos [77]2005GreeceCohort921677044.452.38NDNDPersistent8
Table 2

Information about markers and these levels in each study

First authorMarkersLevels
Occurrence of AF
Balci (Male subjects) [8]MPVMPV [AF: 9.3±0.4 vs. SR: 8.65±0.3]
Balci (Female subjects) [8]MPVMPV [AF: 8.9±0.3 vs. SR: 9±0.2]
Gurses [9]WBCWBC [AF: 7.6±3.3 vs. SR: 7.1±0.9]
Karatas [10]PC, MPV, WBC, NLR, RDW, HbPC [AF: 230±69.3 vs. SR: 240±77.5]MPV [AF: 9.5±1.7 vs. SR: 8.7±1]WBC [AF: 12.8±5.6 vs. SR: 11.9±4.4]NLR [AF: 6.3±6.3 vs. SR: 5.1±4.7]RDW [AF: 13.9±1.7 vs. SR: 13.4±1.4]Hb [AF: 13.8±1.7 vs. SR: 13.9±1.6]
Korantzopoulos [11]WBC, RDW, HbWBC [AF: 6.46±0.35 vs. SR: 7.21±0.8]RDW [AF: 14.6±0.45 vs. SR: 13.77±0.22]Hb [AF: 13.05±0.50 vs. SR: 13.35±0.60]
Akdag [12]PC, MPV, WBC, NLR, HbPC [AF: 265.6±73.4 vs. SR: 248.2±67.2]MPV [AF: 8.9±1.1 vs. SR: 7.8±1]WBC [AF: 7.3±1.9 vs. SR: 6.9 ±1.8]NLR [AF: 3.6±1.5 vs. SR: 2.9±1.3]Hb [AF: 14.3±1.1 vs. SR: 14.5±1]
Akyuz [13]PC, MPV, HbPC [AF: 277±79 vs. SR: 264±82]MPV [AF: 9.8±0.6 vs. SR: 8.4±0.6]Hb [AF: 12.7±1.3 vs. SR: 13.1±1.4]
Chavaria [14]PC, WBC, NLR, HbPC [AF: 242.2±54.1 vs. SR: 243.2±66.2]WBC [AF: 12.4±3.9 vs. SR: 11±3.59]NLR [AF: 3.55±3.15 vs. SR: 4.19±3.55]Hb [AF: 14±1.7 vs. SR: 14.3±1.7]
Drabik (Persistent AF) [15]PC, WBCPC [AF: 202±20.5 vs. SR: 219±16.5]WBC [AF: 7.3±0.6 vs. SR: 6.45±0.7]
Drabik (Paroxysmal AF) [15]PC, WBCPC [AF: 210.25±15.75 vs. SR: 219±16.5]WBC [AF: 6.07±0.42 vs. SR: 6.45±0.7]
Acet (Paroxysmal AF) [16]PC, WBC, NLR, HbPC [AF: 248.9±59 vs. SR: 259.8±95.9]WBC [AF: 11.5±2.5 vs. SR: 9.8±2]NLR [AF: 2.5 ±0.6 vs. SR: 1.8±0.4]Hb [AF: 13.8±1.7 vs. SR: 13.3±1.6]
Acet (Persistent and permanent AF) [16]PC, WBC, NLR, HbPC [AF: 268.6±98 vs. SR: 259.8±95.9]WBC [AF: 10.9±2 vs. SR: 9.8±2]NLR [AF: 3.4±0.6 vs. SR: 1.8±0.4]Hb [AF: 13.9±1.7 vs. SR: 13.3±1.6]
Arik (effective INR) [17]PC, MPV, PDW, WBC, HbPC [AF: 258.25±53.83 vs. SR: 255.75±41.5]MPV [AF: 7.56±0.63 vs. SR: 7.63±0.68]PDW [AF: 17.05±0.86 vs. SR: 17.52±0.71]WBC [AF: 7.47±1.23 vs. SR: 7.38±1.11]Hb [AF: 12.95±0.96 vs. SR: 13.47±0.75]
Arik (ineffective INR) [17]PC, MPV, PDW, WBC, HbPC [AF: 238.75±41.16 vs. SR: 255.75±41.5]MPV [AF: 8.26±0.63 vs. SR: 7.63±0.68]PDW [AF: 17.50±1.13 vs. SR: 17.52±0.71]WBC [AF: 7.49±1.21 vs. SR: 7.38±1.11]Hb [AF: 12.95±0.81 vs. SR: 13.47±0.75]
Distelmaier [18]PC, WBC, RBC, RDW, MCV, MCHC, HCT, HbPC [AF: 202±14.75 vs. SR: 215±14.16]WBC [AF: 9.96±1.42 vs. SR: 9.18±0.88]RBC [AF: 4.57±0.22 vs. SR: 4.23±0.12]RDW [AF: 13.9±0.3 vs. SR: 13.62±0.25]MCV [AF: 90.5±1.67 vs. SR: 90.78±0.82]MCHC [AF: 33.87±0.35 vs. SR: 33.47±0.28]HCT [AF: 41.07±1.92 vs. SR: 38.4±1.13]Hb [AF: 13.95±0.65 vs. SR: 12.85±0.35]
Erdogan (with normal ventricular rate) [19]PC, MPV, WBC, HCT, HbPC [AF: 245.6±114.9 vs. SR: 238.4±66.6]MPV [AF: 7.82±1.2 vs. SR: 7.68±0.70]WBC [AF: 7.52±2.06 vs. SR: 7.55±1.89]HCT [AF: 39.7±5.2 vs. SR: 40.3±3.4]Hb [AF: 14±1.9 vs. SR: 13.9±1.3]
Erdogan (with high ventricular rate) [19]PC, MPV, WBC, HCT, HbPC [AF: 225.5±76.3 vs. SR: 238.4±66.6]MPV [AF: 8.05±0.6 vs. SR: 7.68±0.70]WBC [AF: 7.47±1.47 vs. SR: 7.55±1.89]HCT [AF: 40.7±3.8 vs. SR: 40.3±3.4]Hb [AF: 14.3±1.3 vs. SR: 13.9±1.3]
Zheng [20]WBCWBC [AF: 5.6±1.14 vs. SR: 5.46±1.21]
Xu (without thrombotic events) [21]PC, MPV, HbPC [AF: 205±31 vs. SR: 209±41]MPV [AF: 10.6±1.9 vs. SR: 8.7±0.8]Hb [AF: 14.5±1.4 vs. SR: 14.6±1.1]
Xu (with thrombotic events) [21]PC, MPV, HbPC [AF: 206±42 vs. SR: 209±41]MPV [AF: 11.7±2 vs. SR: 8.7±0.8]Hb [AF: 14.6±1.3 vs. SR: 14.6±1.1]
Gungor [22]PC, MPV, WBC, NLR, RDW, MCV, HbPC [AF: 249.4±59.4 vs. SR: 253.4±61.1]MPV [AF: 8.99±0.65 vs. 9.14±0.98]WBC [AF: 7.21±1.62 vs. SR: 6.81±1.17]NLR [AF: 2.04±0.94 vs. SR: 1.93±0.64]RDW [AF: 13.45±0.2 vs. SR: 12.57±0.27]MCV [AF: 90.2±5.4 vs. SR: 89.2±3.6]Hb [AF: 14.5±1.4 vs. SR: 14.2±1.2]
Liu [23]RDWRDW [AF: 12.71±0.9 vs. SR: 12.45±0.62]
Sarikaya [24]RDW, HbRDW [AF: 15.13±1.58 vs. 14.05±1.15]Hb [AF: 13.74±1.38 vs. SR: 13.88±1.62]
Sonmez [25]PC, NLR, HbPC [AF: 231±60 vs. 247±67]NLR [AF: 2.7±1.1 vs. SR: 2.1±1]Hb [AF: 13.3±1.6 vs. SR: 13.1±1.8]
Ulu [26]PC, PDW, MPVPC [AF: 236.44±63.92 vs. SR: 233.32±86.24]PDW [AF: 12.64±1.43 vs. SR: 11.76±1.41]MPV [AF: 11.47±0.93 vs. SR: 10.37±1.07]
Berge [27]PC, HbPC [AF: 230±7.5 vs. SR: 261.25±4.16]Hb [AF: 14.6±0.2 vs. SR: 14.7±0.06]
Ertas (without stroke) [28]PC, WBC, NLR, RDW, HbPC [AF: 232±55 vs. SR: 258±54]WBC [AF: 7.8±1.8 vs. SR: 7±1.4]NLR [AF: 3.1±2.1 vs. SR: 2.05±0.9]RDW [AF: 14.3±1.8 vs. SR: 13.2±0.9]Hb [AF: 13±1.4 vs. SR: 14±1.7]
Ertas (with stroke) [28]PC, WBC, NLR, RDW, HbPC [AF: 240±82 vs. SR: 258±54]WBC [AF: 8.6±2.8 vs. SR: 7±1.4]NLR [AF: 5.6±3.4 vs. SR: 2.05±0.9]RDW [AF: 14.1±1.7 vs. SR: 13.2±0.9]Hb [AF: 13±1.6 vs. SR: 14±1.7]
Gungor [29]WBC, HbWBC [AF: 6.5±1.5 vs. SR: 6.2±1.1]Hb [AF: 14.7±1.5 vs. SR: 14.9±1.3]
Turgut [30]PC, MPVPC [AF: 274±82 vs. SR: 253±83]MPV [AF: 9±0.2 vs. SR: 8.4±0.2]
Jaremo (healthy control) [31]PCPC [AF: 241±64 vs. 260±78]
Jaremo (disease control) [31]PCPC [AF: 241±64 vs. 265±84]
Sahin [32]MPV, WBC, NLRMPV [AF: 8.31±1.12 vs. SR: 7.99±1.39]WBC [AF: 7.86±2.04 vs. 7.67±2.03]NLR [AF: 2.87±1.3 vs. 2.2±1.56]
Tekin [33]PC, MPV, WBC, HCTPC [AF: 242±90 vs. 243±67]MPV [AF: 9.49±1.08 vs. 9.09±1.13]WBC [AF: 7.48±2.15 vs. 6.94±1.68]HCT [AF: 40.22±4.8 vs. 41.45±4.79]
Turfan (without stroke) [34]PC, MPV, HbPC [AF: 264±94 vs. 213±72]MPV [AF: 9.1±1 vs. 8.6±1.3]Hb [AF: 12.8±1.1 vs. 12.7±1.2]
Turfan (with stroke) [34]PC, MPV, HbPC [AF: 245±73 vs. 213±72]MPV [AF: 9.7±0.9 vs. 8.6±1.3]Hb [AF: 13±1.4 vs. 12.7±1.2]
Feng [35]PC, MPV, WBC, RBC, MCVPC [AF: 213.3±82.5 vs. SR: 217.6±81.9]MPV [AF: 9.95±1.32 vs. SR: 9.02±1.16]WBC [AF: 6.91±3.24 vs. SR: 6.88±3.35]RBC [AF: 4.47±0.68 vs. 4.56±0.71]MCV [AF: 93.8±5.2 vs. 94.1±5.3]
Liu (Paroxysmal AF) [36]WBCWBC [AF: 6.76±1.85 vs. SR: 6.34±1.89]
Liu (Persistent AF) [36]WBCWBC [AF: 6.37±1.66 vs. SR: 6.34±1.89]
Yoshizaki [37]WBCWBC [AF: 11.1±5.2 vs. SR: 10.6±4]
Hayashi (Paroxysmal AF) [38]PC, WBCPC [AF: 260±83 vs. SR: 190±77]WBC [AF: 5.8±4.2 vs. SR: 5.3±3]
Hayashi (Chronic AF) [38]PC, WBCPC [AF: 200±14 vs. SR: 190±77]WBC [AF: 5.6±3.8 vs. SR: 5.3±3]
Fu [39]PCPC [AF: 210±55.5 vs. SR: 221.1±51.1]
Liu [40]WBCWBC [AF: 6.5±1.9 vs. SR: 7.2±2.2]
Letsas (Paroxysmal AF) [41]WBCWBC [AF: 7.7±2.19 vs. SR: 7.15±1.87]
Letsas (Permanent AF) [41]WBCWBC [AF: 6.97±1.9 vs. SR: 7.15±1.87]
Luan (Persistent AF) [42]WBCWBC [AF: 6.13±1.66 vs. SR: 6.13±1.95]
Luan (Paroxysmal AF) [42]WBCWBC [AF: 6.9±1.28 vs. SR: 6.13±1.95]
Alberti [43]PC, WBCPC [AF: 185.6±10 vs. SR: 243.3±9.4]WBC [AF: 5.6±0.3 vs. SR: 6.3±0.3]
Dai [44]WBCWBC [AF: 7.32±1.89 vs. SR: 6.57±1.91]
Ichiki [45]WBCWBC [AF: 4.6±0.3 vs. SR: 5.3±0.5]
Yao (Persistent AF) [46]WBCWBC [AF: 5.76±0.28 vs. SR: 5.69±0.35]
Yao (Paroxysmal AF) [46]WBCWBC [AF: 5.69±0.31 vs. SR: 5.69±0.35]
Colkesen [47]PC, MPV, WBCPC [AF: 242±13 vs. SR: 236±53]MPV [AF: 10±2 vs. SR: 8.3±1.50]WBC [AF: 7.58±2.35 vs. SR: 7.47±2.08]
Choudhury (disease control) [48]PC, MPV, WBC, HCT, HbPC [AF: 259.9±66.3 vs. SR: 261.1±63.4]MPV [AF: 7.6±1.4 vs. SR: 7.8±1.9]WBC [AF: 7.1±1.8 vs. SR: 7.1±2.2]HCT [AF: 42.3±4.3 vs. SR: 41.6±3.9]Hb [AF: 14.6±1.6 vs. SR: 13.9±1.5]
Choudhury (healthy control) [48]PC, MPV, WBC, HCT, HbPC [AF: 259.9±66.3 vs. SR: 266.9±56.1]MPV [AF: 7.6±1.4 vs. SR: 7.4±0.97]WBC [AF: 7.1±1.8 vs. SR: 6.4±1.8]HCT [AF: 42.3±4.3 vs. SR: 40.6±33.7]Hb [AF: 14.6±1.6 vs. SR: 14.1±1.2]
Pirat [49]WBCWBC [AF: 7.45±1.59 vs. SR: 6.7±0.98]
Yip [50]PC, WBCPC [AF: 204±57 vs. SR: 209±49]WBC [AF: 6.7±1.5 vs. SR: 6.6±1.7]
Kamath (Paroxysmal and persistent AF) [51]PC, HCTPC [AF: 280±81 vs. SR: 253±51]HCT [AF: 45±4 vs. SR: 42±3]
Kamath (Permanent AF) [51]PC, HCTPC [AF: 264±75 vs. SR: 253±51]HCT [AF: 43±5 vs. SR: 42±3]
Kamath (Paroxysmal AF) [52]PC, HCTPC [AF: 279±73 vs. SR: 252±53]HCT [AF: 43±5 vs. SR: 42±3]
Kamath (Permanent AF) [52]PC, HCTPC [AF: 266±76 vs. SR: 252±53]HCT [AF: 43±5 vs. SR: 42±3]
Kamath [53]PCPC [AF: 253±77 vs. SR: 261±62]
Kamath [54]PCPC [AF: 253±67 vs. SR: 270±49]
Peverill [55]PC, MPV, MCV, HCTPC [AF: 218±55 vs. SR: 241±59]MPV [AF: 9.7±1.4 vs. SR: 9.9±1.4]MCV [AF: 89±6 vs. SR: 88±7]HCT [AF: 42±5 vs. SR: 39±4]
Kahn (without stroke) [56]PC, HbPC [AF: 230±98 vs. SR: 233±49]Hb [AF: 14.9±1.3 vs. SR: 13.4±1.5]
Kahn (with stroke) [56]PC, HbPC [AF: 253±82 vs. SR: 242±77]Hb [AF: 14.1±1.2 vs. SR: 14.3±1.7]
Lip [57]PCPC [AF: 242±67 vs. SR: 224±63]
Gustafsson (without stroke) [58]PCPC [AF: 172.25±8.75 vs. SR: 234.75±10.75]
Gustafsson (with stroke) [58]PCPC [AF: 179±18.5 vs. SR: 234.75±10.75]
Recurrence of AF
Gurses [9]WBCWBC [AF: 7.5±3.9 vs. SR: 7.6±3.2]
Hongliang Li [59]PC, WBC, RDW, HbPC [AF: 219.77±44.15 vs. SR: 199.32±52.58]WBC [AF: 6.51±1.84 vs. SR: 7.41±14.65]RDW [AF: 12.81±0.94 vs. SR: 12.37±0.56]Hb [AF: 14.11±1.85 vs. SR: 13.94±1.21]
Yanagisawa (without heart failure) [60]WBC, RDW, MCV, HbWBC [AF: 5.5±1.4 vs. SR: 5.3±1.6]RDW [AF: 13.3±0.8 vs. SR: 13.2±0.8]MCV [AF: 92.3±4.4 vs. SR: 92±4.2]Hb [AF: 14±1.5 vs. SR: 14±1.5]
Yanagisawa (with heart failure) [60]WBC, RDW, MCV, HbWBC [AF: 5.7±1.5 vs. SR: 6.1±1.6]RDW [AF: 14.5±2 vs. SR: 13.5±0.9]MCV [AF: 91.3±6.4 vs. SR: 92.3±4.6]Hb [AF: 13.3±2.3 vs. SR: 14.1±1.8]
Aksu [61]MPV [AF: 8.81±1.4 vs. SR: 8.7±1.88]WBC [AF: 6.97±1.6 vs. SR: 7.38±1.7]NLR [AF: 2.5±0.78 vs. SR: 1.83±0.63]RDW [AF: 16.1±1.44 vs. SR: 14.87±0.48]WBC [AF: 13.3±1.34 vs. SR: 13.72±1.17]
Gurses [62]PC, WBC, RDW, HbPC [AF: 221.8±56.3 vs. SR: 228.4±68.8]WBC [AF: 7.82±2.43 vs. SR: 7.44±1.89]RDW [AF: 14.3±0.93 vs. SR: 13.52±0.93]Hb [AF: 14.19±1.85 vs. SR: 13.92±1.76]
Karavelioglu [63]PC, WBC, NLR, HCT, HbPC [AF: 234±65.1 vs. SR: 258.1±93.4]WBC [AF: 7.6±2.64 vs. SR: 7.93±2.42]NLR [AF: 2.8±1.59 vs. SR: 2.13±1.04]HCT [AF: 40.1±5.1 vs. SR: 41.1±5.2]Hb [AF: 13.6±2.9 vs. SR: 13.8±2.9]
Wen [64]PC, WBC, NLR, HbPC [AF: 196±59 vs. SR: 198±44]WBC [AF: 6.36±1.56 vs. SR: 5.63±1.2]NLR [AF: 2.16±1.23 vs. SR: 1.94±0.94]Hb [AF: 12.6±1.8 vs. SR: 13.1±1.7]
Guo Xueyuan [65]WBC, NLR, HbWBC [AF: 8.17±1.7 vs. SR: 7.84±1.6]NLR [AF: 1.9±1.19 vs. SR: 1.81±0.1]Hb [AF: 14.84±1.57 vs. SR: 14.52±1.82]
Aribas [66]WBC, NLRWBC [AF: 7.4±2 vs. SR: 7.6±2]NLR [AF: 2.38±2.09 vs. SR: 2.23±1.23]
Bing Li [67]WBCWBC [AF: 6.7±2.2 vs. SR: 6.1±2]
Canpolat [68]WBC, NLR, HbWBC [AF: 8.94±2.08 vs. SR: 7.46±2.34]NLR [AF: 3.53±0.95 vs. SR: 2.65±0.23]Hb [AF: 13.5±1.8 vs. SR: 13.6±1.9]
Im [69]NLRNLR [AF: 1.9±1.2 vs. SR: 2±2.14]
Xiao-nan HE [70]WBCWBC [AF: 6.2±1.8 vs. SR: 6.5±1.9]
Ferro [71]WBCWBC [AF: 7.44±1.45 vs. SR: 7.47±1.71]
Smit [72]WBCWBC [AF: 7.7±1.5 vs. SR: 7.6±2]
Wang (Paroxysmal AF) [73]WBCWBC [AF: 6.1±1.4 vs. SR: 6.1±1.4]
Wang (Persistent AF) [73]WBCWBC [AF: 6.2±1.9 vs. SR: 6.6±1.5]
Liu (Paroxysmal AF) [74]WBCWBC [AF: 6.2±2.9 vs. SR: 5.9±1.4]
Liu (Persistent AF) [74]WBCWBC [AF: 5.6±1.4 vs. SR: 6±2.4]
Vizzardi [75]WBCWBC [AF: 6.9±1.4 vs. SR: 7±5.4]
Letsas [76]WBCWBC [AF: 6.86±1.21 vs. SR: 5.79±1.39]
Korantzopoulos [77]WBCWBC [AF: 7.29±1.84 vs. SR: 6.64±1.39]
Figure 1

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

MPV

A total of 4014 cases were included from 23 studies, of which 1838 were allocated to the AF group and 2176 to the SR group. The mean level of MPV was 9.18 FL in the AF group and 8.48 FL in the SR group (details in Tables 1 and 2). Pooled analysis revealed that MPV level was significantly higher in patients with AF compared to those with SR, with a WMD of 0.42 FL (95% CI: 0.39 to 0.46; p<0.001, Figure 2) using a random-effects model. There was significant heterogeneity among the studies (I2=95.7%; heterogeneity p<0.001).
Figure 2

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

PDW

A total of 553 cases were included from 3 studies, of which 275 and 278 were allocated to the AF group and the SR group, respectively. The mean level of PDW was 15.73% in the AF group and 15.60% in the SR group (details in Tables 1 and 2). Using a random-effects model, pooled analysis indicated that PDW was statistically lower in the AF group than in the SR group, with a WMD of −0.24% (95% CI: −0.39 to −0.09; p=0.001). There was significant heterogeneity among the studies (I2=88.5%; heterogeneity p<0.001)

WBC

A total of 7042 patients were included from 42 studies, of which 3105 were allocated to the AF group and 3937 to the SR group. The mean WBC count was 7.49×109/L in patients with AF and 7.16×109/L in those with SR (details in Tables 1 and 2). Pooled analysis indicated that the mean count of WBC was similar in AF patients and those with SR, with a WMD of −0.005×109/L (95% CI: −0.052 to 0.042; p=0.83, Figure 3), with considerable heterogeneity among the studies (I2=87.2%; heterogeneity p<0.001).
Figure 3

Forest plot of weighted mean difference (WMD) for association between white blood cell count and occurrence of AF.

NLR

A total of 1899 cases were selected from 10 studies, of which 677 were allocated to the AF group and 1222 to the SR group. The mean NLR was 3.56 in the AF group and 2.61 in the SR group (details in Tables 1 and 2). Pooled analysis showed that the NLR was remarkably higher in patients with AF compared to controls, with a WMD of 0.89 (95% CI: 0.79 to 0.99; p<0.001, Figure 4) using a random-effects model. There was significant heterogeneity among the studies (I2=93.6%; heterogeneity p<0.001).
Figure 4

Forest plot of weighted mean difference (WMD) for association between neutrophil to lymphocyte ratio and occurrence of AF.

RBC count

A total of 572 cases were included from 2 studies, of which 251 were allocated to the AF group and 321 to the SR group. The mean RBC count was 4.52×1012/L in the AF group and 4.39×1012/L in the SR group (details in Tables 1 and 2). Using a random-effects model, pooled analysis showed that the mean count of RBC was statistically higher in the AF group compared to the SR group, with a WMD of 0.28×1012/L (95% CI: 0.23 to 0.33; p<0.001). Significant heterogeneity was observed among the studies (I2=96.8%; heterogeneity p<0.001).

RDW

A total of 1631 cases were included from 8 studies, of which 577 were allocated to the AF group and 1054 to the SR group. The mean of RDW was 14.01% in the AF group and 13.28% in the SR group (details in Tables 1 and 2). Using a random-effects model, pooled analysis revealed that RDW was significantly higher in the AF group than in the SR group, with a WMD of 0.61% (95% CI: 0.56 to 0.66; p<0.001, Figure 5). There was significant heterogeneity among the studies (I2=94.7%; heterogeneity p<0.001)
Figure 5

Forest plot of weighted mean difference (WMD) for association between red blood cell distribution width and occurrence of AF.

Secondary hematological parameters

MCHC was reported in 1 study, which was not included in the meta-analysis. According to pooled assessment analysis, the level of MCV (number of studies=4, WMD of −0.14 FL, 95% CI: −0.51 to 0.23; p=0.46 and I2=34%; heterogeneity p=0.2) and Hb (number of studies=27, WMD of 0.04 g/dL, 95% CI: −0.02 to 0.10; p=0.23 and I2=91.1%; heterogeneity p<0.001) were similar in both groups. Pooled analysis showed that HCT (number of studies=11, WMD of 1.79%, 95% CI: 1.43 to 2.15; p<0.001 and I2=80.6%%; heterogeneity p<0.001) was significantly higher in the AF group compared to the SR group.

Association of hematologic parameters with recurrent AF

A total of 696 cases were selected from 4 studies, of which 207 were allocated to recurrent AF group and 489 to the non-recurrent AF group (details in Tables 1 and 2). Pooled effects analysis showed that the mean platelet count did not differ between groups, with a WMD of −2.71×109/L (95% CI: −12.75 to 7.34; p=0.59). Significant heterogeneity was observed among the studies (I2=69.4%; heterogeneity p=0.02). A total of 3716 patients were included from 22 studies, of which 1223 were allocated to the recurrent AF group and 2493 to the non-recurrent AF group (details in Tables 1 and 2). The mean WBC count was 6.89×109/L in patients with recurrent AF and 6.79×109/L in those with non-recurrent AF. Pooled analysis revealed that the mean count of WBC was statistically higher in the recurrent group compared to the non-recurrent group, with a WMD of 0.20×109/L (95% CI: 0.08 to 0.32; p=0.002, Figure 6), with considerable heterogeneity among the studies (I2=54.7%; heterogeneity p=0.001).
Figure 6

Forest plot of weighted mean difference (WMD) for association between white blood cell count and recurrence of AF.

A total of 1620 cases were selected from 7 studies, of which 446 were allocated to the recurrent AF group and 1174 to the non-recurrent AF group (details in Tables 1 and 2). Pooled assessment analysis indicated that the NLR was significantly higher in patients suffering from recurrent AF compared to the non-recurrent group, with a WMD of 0.37 (95% CI: 0.24 to 0.50; p<0.001, Figure 7). There was significant heterogeneity among the studies (I2=83.2%; heterogeneity p<0.001).
Figure 7

Forest plot of weighted mean difference (WMD) for association between neutrophil to lymphocyte ratio and recurrence of AF.

A total of 1209 cases were included from 5 studies, of which 423 were allocated to the recurrent AF group and 786 to the non-recurrent AF group (details in Tables 1 and 2). Using a random-effects model, pooled analysis revealed that RDW was considerably higher in the recurrent AF group than in the non-recurrent group, with a WMD of 0.28% (95% CI: 0.18 to 0.38; p<0.001, Figure 8). There was significant heterogeneity among the studies (I2=87.5%; heterogeneity p<0.001).
Figure 8

Forest plot of weighted mean difference (WMD) for association between red blood cell distribution width and recurrence of AF.

MCV and Hb were investigated in at least 2 studies, which were included in the meta-analysis. According to pooled assessment analysis, the levels of MCV (number of studies=2, WMD of 0.21, 95% CI: −0.43 to 0.85; p=0.52 and I2=1.6%; heterogeneity p=0.31) and Hb (number of studies=9, WMD of 0.04 g/dL, 95% CI: −0.12 to −0.19; p=0.64 and I2=13.6%; heterogeneity p=0.32) were similar in both groups.

Other parameters

There was an insufficient number of studies for analysis on association between MPV, RBC count, and HCT and recurrent AF.

Publication bias and subgroup analysis

Begg tests suggested that all of the analyses were without publication bias except for association between Hb and recurrent AF. Extra details of characteristics of each study for exploration of heterogeneity factors are presented in Supplementary Table 2. Details of subgroup analysis are reported in detail in Supplementary Table 3.

Discussion

AF is one of the most common cardiac arrhythmias in developing and developed countries, precipitating morbidities and mortalities [78,79]. Various mechanisms are involved in AF, such as inflammation, oxidative stress, and prothrombotic state [79,80]. Therefore, the complications of this arrhythmia and their negative effects on quality of life can be decreased by more accurate recognition of mechanisms, timely diagnosis, and appropriate treatment. Although taking patient history, considering the history of cardiac arrhythmia, clinical examinations, ECG, and Holter monitoring can assist in diagnosis and control of AF, some routine diagnostic actions which are performed daily in clinical practice might be of higher value than previously thought [81]. CBC is a routine lab test for most patients, particularly those with cardiovascular diseases hospitalized in cardiology and cardiac surgery wards, as well as CCUs or ICUs [81]. Hematological parameters in CBC tests can indicate hemodynamic status and are appropriate predictors for clinical outcomes of these patients [81]. Varastehravan et al. reported that hematological parameters had considerable ability in prognosis of ST-segment resolution in patients with ST-segment elevation myocardial infarction receiving streptokinase therapy [5]. In the present study, we investigated the association of hematological parameters with new-onset and recurrent AF in order to understand which hematological parameters could be reliable predictors of each type of AF. Although the majority of physicians and researchers have believed that platelet count in cases with new-onset AF is higher than in patients with SR, our findings revealed that the number of platelets was significantly lower in cases with new-onset AF compared to those with SR, resulting in the likelihood of lower platelet count to predict new-onset AF. Our subgroup analysis showed an inverse relationship between platelet count and new-onset AF in cases of persistent AF, but this relationship was not found in cases of paroxysmal and permanent AF. On the other hand, there was no significant relationship between platelet count and new-onset AF in patients with chronic AF. According to our findings, sample size of the studies, age, diabetes mellitus, differences regarding treatment with anticoagulants, and type of AF are factors of heterogeneity. The present study found no remarkable relationship between platelet count and recurrent AF; therefore, platelet count could be a potential predictor for new-onset AF, but it does not appear to be a significant factor associated with recurrent AF. Regarding the results of this study, PDW was considerably lower in cases with new-onset AF compared to those with SR. Thus, PDW and platelet count both had an inverse relationship with the new-onset AF. MPV is known as an important biomarker of platelet activity. Large platelets secrete many critical mediators of coagulation, inflammation, thrombosis, and atherosclerosis. Evidence shows a close relationship between MPV and cardiovascular risk factors, such as diabetes mellitus, hypertension, and hypercholesterolemia [82,83]. Interestingly, in a recent study, Sansanayudh et al. reported an association between MPV and coronary artery disease (CAD). Patients with CAD and slow coronary blood flow had larger MPV than in the control group. They concluded that MPV might be used for risk stratification or to raise diagnostic accuracy of the traditional risk stratification markers in CAD patients [84]. The results of our study showed that MPV was also considerably higher in cases with new-onset AF compared to those with SR. According to our subgroup analysis, there was also a direct relationship between MPV and new-onset AF in both chronic and non-chronic AF. Sample sizes of the studies, differences in treatment with anticoagulants, and type of AF appeared to be factors of heterogeneity. Owing to insufficient number of studies on the association between PDW and MPV with recurrent AF, no analysis was performed in this regard. There is a known relationship between inflammation and development of AF. Activities in hematopoietic tissues producing inflammatory leukocytes are closely associated with systemic inflammation, arterial inflammation, and cardiovascular events; however, their association with AF is unclear [85]. The findings of this study demonstrated that WBC count was not significantly different between cases of new-onset AF compared to those of SR; therefore, WBC is not proposed as a reliable predictor. The present study also confirmed that WBC count was not associated with new-onset AF for chronic and non-chronic AF. Our subgroup analysis indicated that risk factors such as diabetes mellitus, hypertension, and cigarette smoking could be factors of heterogeneity. On the other hand, our results revealed that WBC count was statistically higher in cases of recurrent AF compared to those with non-recurrent AF. Consequently, it can be stated that WBC count might be considered a predictor for recurrent AF, but not for new-onset AF. It also implies that possible inflammatory mechanisms are more active in patients who develop recurrent AF despite anti-arrhythmic therapy for AF. As a result, considering inflammatory markers as a valuable tool to detect the risk of recurrent AF after pharmacological interventions and electrophysiology could greatly help in terms of timely diagnosis of AF recurrence. The neutrophil to lymphocyte ratio is a new systemic inflammatory marker and a prognostic indicator of cardiovascular diseases [86,87]. The results of this study show that NLR is directly associated with new-onset and recurrent AF and generally could be an appropriate and efficient predictor for this disease. In our subgroup analysis, NLR also had this predictive ability for paroxysmal and persistent AF, while the association of NLR with permanent and chronic AF could not be detected due to the lack of relevant studies. RDW is a parameter used to measure variability in the size of circulatory red blood cells obtained in CBC tests. Higher RDW reflects the presence of anisocytosis, which is associated with impaired erythropoiesis and RBC degradation appearing as chronic inflammation and a high level of oxidative stress [88]. Several studies suggested that RDW can predict poor outcomes in patients with heart failure, stable CAD, and acute myocardial infarction [89-91]. Similarly, our study showed that RDW was clearly higher in cases with new-onset AF compared to cases with SR. However, RDW was significantly increased in patients with recurrent AF versus non-recurrent AF, providing strong evidence that RDW can predicting both new-onset and recurrent AF. Only 2 studies investigated RBC count and its impact on AF, in which pooled analysis showed that RBC count was statistically higher in the AF group than in the SR group. No study was found investigating the relationship between this hematological parameter and recurrent AF. Anemia increases the risk of cardiovascular complications, such as thromboembolic events, bleeding, and mortality in anticoagulated patients with AF. Patients with anemia and AF are supposed to be closely monitored while under treatment with all types of anticoagulants [92]. In the present study, Hb, HCT, MCV, and MCHC were examined as secondary hematological parameters. Pooled analysis found no significant differences in Hb levels comparing cases of new-onset AF with cases of SR. Notably, our subgroup analysis showed that the status of treatment with anticoagulants was not defined in a significant number of studies. Therefore, we had no information on whether patients enrolled in these studies had been receiving anticoagulant therapy. Concerning general findings, it appears that Hb is not a potential predictor for new-onset AF; however, this might change in the future by defining the therapeutic strategies with anticoagulants as well as the number of patients under treatment. On the other hand, there was an interesting finding about the type of AF. When the studies were sorted in terms of chronic and non-chronic AF, the level of Hb was considerably higher in non-chronic AF and significantly lower in chronic AF. This finding suggests that the type of AF in terms of acute or chronic pattern might have different effects on Hb changes. The merged results rejected any relationship between Hb and new-onset AF; however, based on our subgroup analysis, we believe that after categorizing the types of AF into chronic and non-chronic, Hb might be a predictor. The results also indicated that the level of Hb was similar in patients with recurrent AF and those with non-chronic AF. Performing subgroup analysis, we found that the lack of association of Hb changes with recurrent AF was not influenced by any factor. Therefore, we strongly corroborate the lack of association between this hematological parameter and recurrent AF. MCV is a measure of the average red blood cell. Based on our results, the level of MCV did not significantly differ between cases of new-onset AF versus SR cases, thus MCV could not be suggested as a predictor for new-onset AF. Also, our subgroup analysis strongly supported this finding. Only 2 studies investigated the association of MCV and recurrent AF, and the merged analysis showed that the level of MCV was not significantly related to new-onset AF. HCT is a test for measuring the volume of RBC in relation to the total volume of blood. In the present study, the percentage of HCT was notably higher in cases of new-onset AF versus SR cases. Our subgroup analysis revealed that HCT can predict new-onset AF in non-chronic AF, but this ability was not seen in chronic AF. Due to the insufficient number of studies, we were unable to evaluate the relationship between HCT and recurrent AF. Lip et al. reported that anticoagulants can reduce the level of hemostatic and hematologic factors in AF patients and, consequently, differences in treatment strategies with anticoagulants in various studies could be considered as a factor of heterogeneity [93-95]. Our subgroup analysis of platelet count, RDW, MCV, HCT, and WBC indicated that differences in using anticoagulants could play a considerable role in the existence of heterogeneity. It should also be noted that in the meta-analysis on non-experimental studies, more heterogeneity was found, which can be explained by the following: 1) less controlled biases; 2) more confounding factors; and 3) differences in defining outcomes. Millions of CBC tests are performed daily for a large number of hospitalized patients with cardiovascular diseases throughout the world. In the present study, we found that CBC tests, apart from their ability to show a number of various pathologies already well known in clinical practice, might also play a significant role in diagnosis of various types of cardiac arrhythmias. Therefore, in addition to taking patient history, ECG, and Holter monitoring, the information from CBC in terms of AF should also be taken into account as an important diagnostic parameter. Therefore, we should be aware that, despite being one the most routine laboratory tests, the usefulness of CBC should not be underestimated.

Conclusions

Indeed, according to the results of previous research on potential predictive role of various CBC tests on the occurrence of AF that were conglomerated in our meta-analysis, CBC tests are a relatively easy to use and inexpensive tool to provide additional information on potential AF. Although CBC testing cannot replace standard diagnostics, they may be a valuable method to get some additional information in clinical diagnostics. In general, considering the results of this study, we conclude that lower platelet count and PDW, as well as higher MPV, NLR, RBC, RDW, and HTC, could be associated with new-onset AF. We strongly emphasize that MPV, NLR, and RDW have better predictive value in clinical practice for AF. Patients with AF who are under treatment are at high risk of recurrent AF; as a result, CBC is of particular importance for these patients. Our results also indicated that WBC, NLR, and PDW are hematological parameters with significant ability to predict recurrent AF. Therefore, emphasizing the potential predictive role of hematological parameters for new-onset and recurrent AF, we strongly recommend adding CBC testing to the diagnostic modalities of AF in clinical practice. Included, and excluded studies according to primary hematological parameters. Extra details of characteristics of each study for exploration of heterogeneity factors. Subgroup-analysis.
Supplementary Table 1

Included, and excluded studies according to primary hematological parameters.

Clinical outcomes and biomarkersStudies were identified and screened [n]Studies were excluded according to title, abstract or full text (Secondary exclude) [n]Studies were included [n]Data for occurrence and recurrence [n]
Platelet count29225438 approved articles with totally 52 enrolled data for meta-analysis (48 studiesOccurrence: 48Recurrence: 4
Mean platelet volume14712918 approved articles with totally 24 enrolled data for meta-analysisOccurrence: 23Recurrence: 1
Platelet distribution width1192 approved articles with totally 3 enrolled data for meta-analysisOccurrence: 3Recurrence: 0
White blood cell34829949 approved articles with totally 64 enrolled data for meta-analysisOccurrence: 42Recurrence: 22
Neutrophil to lymphocyte ratio412615 approved articles with totally 17 enrolled data for meta-analysisOccurrence: 10Recurrence: 7
Red blood cell83812 approved articles with totally 2 enrolled data for meta-analysisOccurrence: 2Recurrence: 0
Red blood cell distribution width493811 approved articles with totally 13 enrolled data for meta-analysisOccurrence: 8Recurrence: 5
Supplementary Table 2

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

First AuthorGeographic AreaTotal NTotal ageTotal maleTotal DMTotal HTNTotal CSTotal DiureticTotal ACEITotal. StatinTotal BBAC-codeChronic or not
Occurrence of AF
Balci (Male subjects) [8]European35ND100NDNDNDNDNDNDND5ND
Balci (Female subjects) [8]European153ND0NDNDNDNDNDNDND5ND
Gurses [9]European17256.552.3513.9551.75NDNDNDNDND5Non-chronic
Karatas [10]European62161.0572.52345.564NDND0ND2Non-chronic
Korantzopoulos [11]European10176.546.527.588.5NDNDNDNDND3Non-chronic
Akdag [12]European14864.056016.52223.5NDNDNDND6Combined types
Akyuz [13]European9062.2572.252942.534.2514.520.7532.5234Combined types
Chavaria [14]North America29065.6574.529.0565.6555.05NDNDNDND5ND
Drabik (Persistent AF) [15]European9760.164.9752048.8522.85ND52.2553.1560.64Non-chronic
Drabik (Paroxysmal AF) [15]European916055.1516.446.0520ND54.0547.4557.254Non-chronic
Acet (Paroxysmal AF) [16]European13462.054416.51821.5NDNDNDND5Non-chronic
Acet (Persistent and permanent AF) [16]European12662.8543.521.52428.5NDNDNDND5Combined types
Arik (effective INR) [17]European24869.6540.76.0568.9513.72759.25ND59.75chronic
Arik (ineffective INR) [17]European24869.4537.96.8565.3512.124.255.65ND61.35chronic
Distelmaier [18]North America19873.5612460.5NDNDNDNDND5Non-chronic
Erdogan (with normal ventricular rate) [19]European6769.5549.28106561753.51043.33chronic
Erdogan (with high ventricular rate) [19]European6368.849.05513.356.5825523.543.33chronic
Zheng [20]Asian21761.73558.6310.8449.27532.74NDNDNDND5ND
Xu (without thrombotic events) [21]Asian11566.09550.4537.453.138.25ND42.629.5543.554chronic
Xu (with thrombotic events) [21]Asian11567.97551.336.557.531.25ND40.826.0540.954chronic
Gungor [22]European17747.257.83.3514.7523.15NDNDND10.63ND
Liu [23]Asian234NDNDNDNDNDNDNDNDND5Non-chronic
Sarikaya [24]European12671.035038100NDNDNDNDND5ND
Sonmez [25]European85703724.2163.255ND14.1647.1715.4135.64Non-chronic
Ulu [26]European57NDND00NDNDNDNDND5ND
Berge [27]European1897571.025848ND192134.5284Combined types
Ertas (without stroke) [28]European11153.5518.532.52ND17ND303ND
Ertas (with stroke) [28]European6354.54710475ND24ND16.53ND
Gungor [29]European14042.5566.40031NDNDNDND5ND
Turgut [30]European162635210065.541.56.523.51816.54chronic
Jaremo (healthy control) [31]European8267.566.735.1721.552.58518.913.7914.65541.34ND
Jaremo (disease control) [31]European13071.568.112.7543.759.48528.6526.2525.0555.924ND
Sahin [32]European14464.86549.7510066.544.5NDNDNDND5Non-chronic
Tekin [33]European21973.535.513.568.519NDNDNDND5chronic
Turfan (without stroke) [34]European13559.554.5515.633.155.5NDNDNDND4ND
Turfan (with stroke) [34]European12162.552.0524.62750.6NDNDNDND4ND
Feng [35]Asian37465.861.7517.6553.225.652341.9544.8542.54ND
Liu (Paroxysmal AF) [36]Asian10164.3562.5532.5NDND2115343Non-chronic
Liu (Persistent AF) [36]Asian10765.8616.535NDND2913.5353Non-chronic
Yoshizaki [37]Asian1767076326552.5ND37.5538.8510.65Non-chronic
Hayashi (Paroxysmal AF) [38]Asian2757.9592.514.548.5NDND40.526ND2Non-chronic
Hayashi (Chronic AF) [38]Asian2761.4592.511.0552NDND3726ND2chronic
Fu [39]Asian16954.4563.5NDND42.45NDND12.96.14Combined types
Liu [40]Asian45158.3551.435ND10023.714.8571.5561.1542.75Combined types
Letsas (Paroxysmal AF) [41]European9364.3559660.5NDND4315.5345Non-chronic
Letsas (Permanent AF) [41]European8966.659.51163NDND52.513.535.55chronic
Luan (Persistent AF) [42]Asian5353.2550.855026.2130.2NDNDNDND5Non-chronic
Luan (Paroxysmal AF) [42]Asian5550.9952.385024.9330.9NDNDNDND5Non-chronic
Alberti [43]European5164.4547.05NDNDNDNDNDNDND1Non-chronic
Dai [44]Asian52253.06574.76.117NDNDNDNDND5Non-chronic
Ichiki [45]Asian7251.580.2051637.5NDND815ND5Non-chronic
Yao (Persistent AF) [46]Asian15054.176.87.4042.4NDND8.113.24Non-chronic
Yao (Paroxysmal AF) [46]Asian33953.3574.954.25046.55NDND6.67.854Non-chronic
Colkesen [47]European190543818.541.5NDNDND28ND4Non-chronic
Choudhury (disease control) [48]European19263.317410.566.4ND33.1555.746.543.74ND
Choudhury (healthy control) [48]European17762.305724.131.8ND17.7526.8514.4521.94ND
Pirat [49]European3949.551.5826.532ND24.5ND385Non-chronic
Yip [50]Asian8265.7563.059.734.75.65ND23.415.3ND3chronic
Kamath (Paroxysmal and persistent AF) [51]European6263.551.6NDNDNDNDNDNDND1Non-chronic
Kamath (Permanent AF) [51]European1246652.65NDNDNDNDNDNDND1chronic
Kamath (Paroxysmal AF) [52]European586348.276.8524.1355.17NDNDNDND4Non-chronic
Kamath (Permanent AF) [52]European1166552.295.1530.455.17NDNDNDND4chronic
Kamath [53]European1437054.185.37529.565NDNDNDNDND1ND
Kamath [54]European57NDNDNDNDNDNDNDNDND1chronic
Peverill [55]Oceania1635584.6NDNDNDNDNDNDND5ND
Kahn (without stroke) [56]North America81NDNDNDNDNDNDNDNDND1chronic
Kahn (with stroke) [56]North America36NDNDNDNDNDNDNDNDND1chronic
Lip [57]European77NDNDNDNDNDNDNDNDND1chronic
Gustafsson (without stroke) [58]European4077ND102525NDNDNDND1ND
Gustafsson (with stroke) [58]European4077ND12.527.530NDNDNDND1ND
Recurrence of AF
Gurses [9]European8656.857.715.848.55NDND21.216.5ND5Non-chronic
Hongliang Li [59]Asian10462.543.924.4546.137.45ND4149.6542.44Non-chronic
Yanagisawa (without heart failure) [60]Asian67861.17612.546ND3.535ND31.55Non-chronic
Yanagisawa (with heart failure) [60]Asian7963.674.52038ND77.558ND81.55Non-chronic
Aksu [61]European4959.6552.516.548.547NDNDNDND5Non-chronic
Gurses [62]European29955.751.1513.242.431NDNDNDND4Non-chronic
Karavelioglu [63]European21864.441.0951858.521ND23.510.5675Non-chronic
Wen [64]Asian7563.62ND7.557.520NDND30ND5Non-chronic
Guo Xueyuan [65]Asian37949.66573.5500NDNDNDNDND5ND
Aribas [66]European14960ND2962.518.5NDNDNDND2Non-chronic
Bing Li [67]Asian2885771.128.6555.0538.15ND3814.227.75Non-chronic
Canpolat [68]European25155.254.8515.1544.3536.55ND51.2518.05ND5Non-chronic
Im [69]Asian49956.473.6515.5543.9NDNDNDNDND5Non-chronic
Xiao-nan HE [70]Asian33059.566.3ND48.65NDND5014525Non-chronic
Ferro [71]European14470.9556.51487.55ND46.522.5ND2Non-chronic
Smit [72]European1006473.811.965.951541.269.0536.6589.35Non-chronic
Wang (Paroxysmal AF) [73]Asian10357.534.8ND41.65NDNDNDND4.245Non-chronic
Wang (Persistent AF) [73]Asian5552.574.65ND50.35NDNDNDND5.655Non-chronic
Liu (Paroxysmal AF) [74]Asian775675.6ND37.3NDNDNDNDND2Non-chronic
Liu (Persistent AF) [74]Asian4453.0584.85ND51.2NDNDNDNDND2Non-chronic
Vizzardi [75]European106696112.05NDNDND8NDND5Non-chronic
Letsas [76]European7254.5581.521.521.5NDND2314.5ND5Non-chronic
Korantzopoulos [77]European3068.548.397.164.254.7530.9535.75.55ND5Non-chronic
Supplementary Table 3

Subgroup-analysis.

SubgroupStudies (N)WMD (95% CI)I-squared and Heterogeneity-P-value and Effect-P-value respectivelyIs this general item as heterogeneity factor?1.Yes, probably2. No
Occurrence of AF

Platelet count

Year of PublicationNo
>200043−23.75 (−25.22 to −22.29)91% and 0.001 and 0.001
≤20005−56.50 (−61.45 to −51.55)90.7% and 0.001 and 0.001

Geographic areaYes, probably
Asian7−3.88 (−10.98 to 3.22)13.8% and 0.324 and 0.284
European36−29.41 (−30.95 to −27.88)93.7% and 0.001 and 0.001
Africa
North American4−12.11 (−16.25 to −7.96)0.0% and 0.476 and 0.001
South American
Australia1−23 (−40.50 to −5.49)

Design of studyNo
Cohort8−29.09 (−31.01 to −27.16)92.4% and 0.001 and 0.001
Case-control40−23.30 (−25.36 to −21.25)93% and 0.001 and 0.001

Number of populationNo
>3002−6.33 (−19.68 to 7.03)0.0% and 0.689 and 0.353
≤30046−26.61 (−28.02 to −25.20)93.1% and 0.001 and 0.001

Mean ageNo
>60 years35−27.69 (−29.13 to −26.25)94% and 0.001 and 0.001
≤60 years8−2.68 (−9.46 to 4.10)78.4% and 0.001 and 0.438

MaleNo
>70%9−29.76 (−31.69 to −27.83)83.8% and 0.001 and 0.001
≤70%32−15.69 (−17.94 to −13.43)90.5% and 0.001 and 0.001

Diabetes mellitusYes, probably
>30%3−0.27 (−9.57 to 9.01)35.9% and 0.210 and 0.953
≤30%35−24.77 (−26.27 to −23.26)92.2% and 0.001 and 0.001

HypertensionNo
>70%
≤70%39−24.91 (−26.38 to −23.44)92.5% and 0.001 and 0.001

Cigarette smokingNo
>30%10−16.36 (−21.68 to −11.04)92.8% and 0.001 and 0.001
≤30%20−22.62 (−25.67 to −19.56)92.4% and 0.001 and 0.001

Medication: DiureticNo
>70%
≤70%13−28.39 (−30.26 to −26.52)85.7% and 0.001 and 0.001

Medication: ACEINo
>70%
≤70%22−25.47 (−27.18 to −23.76)86.5% and 0.001 and 0.001

Medication: StatinNo
>70%
≤70%21−25.33 (−27.06 to −23.61)88% and 0.001 and 0.001

Medication: Beta-BlockerNo
>70%
≤70%21−25.36 (−27.06 to −23.66)86.6% and 0.001 and 0.001

Anti-coagulant status codesYes, probably
110−52.72 (−56.32 to −49.12)92.3% and 0.001 and 0.001
231.69 (−17.11 to 20.53)67.3% and 0.047 and 0.860
36−10.36 (−21.43 to 0.69)0.0% and 0.703 and 0.066
419−24.85 (−26.58 to −23.13)91.6% and 0.001 and 0.001
59−11.38 (−14.88 to −7.88)36.4% and 0.127 and 0.001
6117.40 (−6.03 to 40.83)

AFYes, probably
Chronic16−2.80 (−7.77 to 2.16)18.1% and 0.246 and 0.268
Non-chronic11−20.88 (−23.55 to −18.20)95.7% and 0.001 and 0.001

Type of AFYes, probably
Paroxysmal5−3.72 (−9.24 to 1.79)72.1% and 0.006 and 0.186
Persistent3−41.93 (−46.40 to −37.46)97.4% and 0.001 and 0.001
Permanent6−5.09 (−11.96 to 1.78)55.3% and 0.048 and 0.147

Mean platelet volume

Year of publication
>2000All of studies: after 2000
≤2000

Geographic areaNo
Asian31.37 (1.16 to 1.58)95.9% and 0.001 and 0.001
European190.39 (0.35 to 0.43)95.2% and 0.001 and 0.001
Africa
North American
South American
Australia1−0.20 (−0.63 to 0.23)

Design of studyNo
Cohort41.37 (1.14 to 1.60)94.7% and 0.001 and 0.001
Case-control190.39 (0.35 to 0.43)95.4% and 0.001 and 0.001

Number of populationYes, probably
>30020.90 (0.67 to 1.13)0.0% and 0.666 and 0.001
≤300210.41 (0.36 to 0.45)96% and 0.001 and 0.001

Mean ageNo
>60 years160.58 (0.54 to 0.63)94.1and 0.001 and 0.001
≤60 years40.23 (0.05 to 0.42)93.5% and 0.001 and 0.012

MaleNo
>70%60.59 (0.46 to 0.71)93.9% and 0.001 and 0.001
≤70%160.40 (0.36 to 0.44)96.4% and 0.001 and 0.001

Diabetes mellitusNo
>30%40.63 (0.57 to 0.69)96.8% and 0.001 and 0.001
≤30%160.49 (0.42 to 0.57)92.7% and 0.001 and 0.001

HypertensionNo
>70%
≤70%200.58 (0.53 to 0.62)93.8% and 0.001 and 0.001

Cigarette smokingNo
>30%80.68 (0.62 to 0.74)94.7% and 0.001 and 0.001
≤30%80.37 (0.28 to 0.45)92.1% and 0.001 and 0.001

Medication: DiureticNo
>70%
≤70%90.54 (0.49 to 0.59)94.3% and 0.001 and 0.001

Medication: ACEINo
>70%
≤70%110.57 (0.52 to 0.62)95.8% and 0.001 and 0.001

Medication: StatinNo
>70%
≤70%110.66 (0.60 to 0.71)94.7% and 0.001 and 0.001

Medication: Beta-BlockerNo
>70%
≤70%120.55 (0.50 to 0.60)95.8% and 0.001 and 0.001

Anti-coagulant status codesYes, probably
1
210.80 (0.26 to 1.33)
330.081 (−0.109 to 0.272)66.1% and 0.053 and 0.404
4100.67 (0.62 to 0.73)95.1% and 0.001 and 0.001
580.108 (0.046 to 0.17)93.6% and 0.001 and 0.001
611.10 (0.75 to 1.45)

AFNo
Chronic80.55 (0.49 to 0.60)95.7% and 0.001 and 0.001
Non-chronic30.85 (0.58 to 1.13)88.6% and 0.001 and 0.001

Type of AFNo
Paroxysmal11.70 (1.20. to 2.19)
Persistent10.32 (−0.09 to 0.73)
Permanent40.28 (0.17 to 0.38)91.7% and 0.001 and 0.001

WBC

Year of publication
>2000All of studies: after 2000
≤2000

Geographic areaNo
Asian150.001 (−0.058 to 0.06)80.8% and 0.001 and 0.973
European25−0.05 (−0.13 to 0.023)89.3% and 0.001 and 0.159
Africa
North American20.828 (0.46 to 1.187)0.0% and 0.365 and 0.001
South American
Australia

Design of studyYes, probably
Cohort40.370 (−0.083 to 0.823)13.2% and 0.326 and 0.109
Case-control38−0.009 (−0.057 to 0.039)88.2% and 0.001 and 0.708

Number of populationNo
>30050.035 (−0.047 to 0.117)84.8% and 0.001 and 0.403
≤30037−0.025 (−0.083 to 0.033)87.7% and 0.001 and 0.398

Mean ageNo
>60 years27−0.060 (−0.140 to 0.019)88.3% and 0.001 and 0.136
≤60 years150.025 (−0.033 to 0.084)85.2% and 0.001 and 0.397

MaleNo
>70%110.009 (−0.051 to 0.070)86.4% and 0.001 and 0.761
≤70%31−0.027 (−0.102 to 0.048)87.8% and 0.001 and 0.481

Diabetes mellitusYes, probably
>30%20.216 (−0.419 to 0.852)0.0% and 0.789 and 0.505
≤30%380.055 (0.005 to 0.104)85% and 0.001 and 0.030

HypertensionYes, probably
>70%2−0.743 (−0.952 to −0.535)0.0% and 0.873 and 0.001
≤70%390.097 (0.046 to 0.147)80.5% and 0.001 and 0.001

Cigarette smokingYes, probably
>30%110.053 (−0.010 to 0.115)26.4% and 0.193 and 0.102
≤30%160.231 (0.123 to 0.339)83.9% and 0.001 and 0.001

Medication: DiureticNo
>70%
≤70%80.061 (−0.102 to 0.224)41.9% and 0.099 and 0.464

Medication: ACEINo
>70%1−0.70 (−1.269 to −0.131)
≤70%210.012 (−0.086 to 0.111)83.2% and 0.001 and 0.804

Medication: StatinNo
>70%
≤70%21−0.00 (−0.057 to 0.506)81.8% and 0.001 and 0.990

Medication: Beta-BlockerNo
>70%
≤70%210.071 (0.015 to 0.127)76.2% and 0.001 and 0.012

Anti-coagulant status codesYes, Probably
11−0.70 (−0.875 to −0.525)
230.661 (−0.627 to 1.949)0.0% and 0.924 and 0.314
39−0.232 (−0.397 to −0.067)85.4% and 0.001 and 0.006
480.054 (−0.006 to 0.115)87.6% and 0.001 and 0.077
5200.132 (0.030 to 0.233)85% and 0.001 and 0.011
610.400 (−0.220 to 1.020)

AFYes, probably
Chronic80.125 (−0.048 to 0.299)0.0% and 0.833 and 0.156
Non-chronic22−0.050 (−0.102 to 0.001)92% and 0.001 and 0.056

Type of AFYes, probably
Paroxysmal9−0.087 (−0.161 to −0.014)88.6% and 0.001 and 0.020
Persistent6−0.019 (−0.101 to 0.062)95.2% and 0.001 and 0.641
Permanent50.069 (−0.120 to 0.259)0.0% and 0.958 and 0.473

NLR

Year of publication
>2000All of studies: after 2000
≤2000

Geographic areaNo
Asian
European90.901 (0.802 to 1.000)94% and 0.001 and 0.001
Africa
North American1−0.640 (−1.711 to 0.431)
South American
Australia

Design of studyNo
Cohort1−0.640 (−1.711 to 0.431)
Case-control90.901 (0.802 to 1.000)94% and 0.001 and 0.001

Number of populationNo
>30011.200 (−0.789 to 3.189)
≤30090.887 (0.789 to 0.986)94.3% and 0.001 and 0.001

Mean ageNo
>60 years71.030 (0.919 to 1.141)91.5% and 0.001 and 0.001
≤60 years30.365 (0.152 to 0.579)95.1% and 0.001 and 0.001

MaleYes, probably
>70%2−0.277 (−1.170 to 0.716)60.8% and 0.110 and 0.637
≤70%80.901 (0.801 to 1.00)94.7% and 0.001 and 0.001

Diabetes mellitusNo
>30%10.670 (0.201 to 1.139)
≤30%90.898 (0.797 to 0.999)94.3% and 0.001 and 0.001

Hypertension
>70%All of studies: ≤70%
≤70%

Cigarette smokingNo
>30%30.492 (0.072 to 0.912)62.5% and 0.069 and 0.022
≤30%60.928 (0.824 to 1.032)96.2% and 0.001 and 0.001

Medication: DiureticNo
>70%
≤70%10.600 (0.146 to 1.054)

Medication: ACEINo
>70%
≤70%31.025 (0.687 to 1.364)91.2% and 0.001 and 0.001

Medication: StatinNo
>70%
≤70%20.630 (0.187 to 1.072)0.0% and 0.564 and 0.005

Medication: Beta-BlockerNo
>70%
≤70%40.408 (0.215 to 0.601)92.8% and 0.001 and 0.001

Anti-coagulant status codesNo
1
211.200 (−0.789 to 3.189)
330.365 (0.152 to 0.579)95.1% and 0.001 and 0.001
410.600 (0.146 to 1.054)
541.081 (0.962 to 1.199)95.4% and 0.001 and 0.001
610.700 (0.236 to 1.164)

AFNo
Chronic
Non-chronic40.689 (0.538 to 0.840)0.0% and 0.935 and 0.001

Type of AFNo
Paroxysmal10.700 (0.529 to 0.871)
Persistent20.634 (0.308 to 0.960)0.0% and 0.833 and 0.001
Permanent

RDW

Year of publication
>2000All of studies: after 2000
≤2000

Geographic areaYes, probably
Asian10.260 (0.065 to 0.455)
European60.873 (0.806 to 0.941)0.0% and 0.613 and 0.001
Africa-
North American10.280 (0.196 to 0.364)
South American-
Australia-

Design of study
CohortAll of studies: case-control
Case-control

Number of populationNo
>30010.500 (−0.039 to 1.039)
≤30070.615 (0.564 to 0.666)95.5% and 0.001 and 0.001

Mean ageYes, probably
>60 years40.412 (0.338 to 0.485)92.8% and 0.001 and 0.001
≤60 years30.885 (0.809 to 0.961)0.0% and 0.716 and 0.001

MaleNo
>70%10.500 (−0.039 to 1.039)
≤70%60.641 (0.588 to 0.694)95.8% and 0.001 and 0.001

Diabetes mellitusNo
>30%-
≤30%70.640 (0.587 to 0.692)95% and 0.001 and 0.001

HypertensionYes, probably
>70%20.856 (0.700 to 1.011)0.0% and 0.337 and 0.001
≤70%50.612 (0.556 to 0.668)96.4% and 0.001 and 0.001

Cigarette smokingNo
>30%10.500 (−0.039 to 1.039)
≤30%30.885 (0.809 to 0.961)0.0% and 0.716 and 0.001

Medication: Diuretic
>70%No Data
≤70%

Medication: ACEINo
>70%-
≤70%21.021 (0.615 to 1.426)0.0% and 0.636 and 0.001

Medication: StatinNo
>70%-
≤70%10.500 (−0.039 to 1.039)

Medication: Beta-BlockerNo
>70%-
≤70%30.885 (0.809 to 0.961)0.0% and 0.716 and 0.001

Anti-coagulant status codesYes, probably
1-
210.500 (−0.039 to 1.039)
340.875 (0.806 to 0.944)0.0% and 0.796 and 0.001
4-
530.297 (0.221 to 0.373)80.7% and 0.006 and 0.001
6-

AFNo
Chronic-
Non-chronic40.379 (0.310 to 0.448)91.6% and 0.001 and 0.001

Type of AFNo
Paroxysmal10.260 (0.065 to 0.455)
Persistent-
Permanent-

MCV

Year of publication
>2000All of studies: after 2000
≤2000

Geographic areaNo
Asian1−0.300 (−1.364 to 0.764)
European11.000 (−0.337 to 2.337)
Africa-
North American1−0.280 (−0.706 to 0.146)
South American-
Australia11.000 (−0.998 to 2.998)

Design of study
CohortAll of studies: Case-control
Case-control

Number of populationNo
>3001−0.300 (−1.364 to 0.764)
≤3003−0.116 (−0.514 to 0.283)55% and 0.108 and 0.569

Mean ageNo
>60 years2−0.283 (−0.679 to 0.113)0.0% and 0.162 and 0.973
≤60 years21.000 (−0.111 to 2.111)0.0% and 1.000 and 0.078

MaleNo
>70%11.000 (−0.998 to 2.998)
≤70%3−0.179 (−0.559 to 0.200)38.5% and 0.197 and 0.354

Diabetes mellitusNo
>30%-
≤30%3−0.179 (−0.559 to 0.200)38.5% and 0.197 and 0.354

HypertensionNo
>70%-
≤70%3−0.179 (−0.559 to 0.200)38.5% and 0.197 and 0.354

Cigarette smokingNo
>30%-
≤30%20.204 (−0.628 to 1.037)55% and 0.136 and 0.631

Medication: DiureticNo
>70%-
≤70%1−0.300 (−1.364 to 0.764)

Medication: ACEINo
>70%-
≤70%1−0.300 (−1.364 to 0.764)

Medication: StatinNo
>70%-
≤70%1−0.300 (−1.364 to 0.764)

Medication: Beta-BlockerNo
>70%-
≤70%20.204 (−0.628 to 1.037)55% and 0.136 and 0.631

Anti-coagulant status codesNo
1
2
311.000 (−0.337 to 2.337)
41−0.300 (−1.364 to 0.764)
52−0.224 (−0.641 to 0.193)33.7% and 0.219 and 0.292
6

AFNo
Chronic
Non-chronic1−0.280 (−0.706 to 0.146)

Type of AFNo
Paroxysmal
Persistent
Permanent

HCT

Year of publication
>2000All of studies: after 2000
≤2000

Geographic areaNo
Asian
European90.552 (0.004 to 1.100)53.4% and 0.028 and 0.048
Africa
North American12.670 (2.168 to 3.172)
South American
Australia13.000 (1.605 to 4.395)

Design of study
CohortAll of studies: Case-control
Case-control

Number of population
>300All of studies: ≤300
≤300

Mean ageNo
>60 years101.704 (1.334 to 2.075)81.4% and 0.001 and 0.001
≤60 years13.000 (1.605 to 4.395)

MaleNo
>70%31.666 (0.767 to 2.566)67% and 0.048 and 0.001
≤70%81.813 (1.423 to 2.203)84.6% and 0.001 and 0.001

Diabetes mellitusNo
>30%
≤30%81.691 (1.299 to 2.083)84.6% and 0.001 and 0.001

HypertensionNo
>70%
≤70%81.691 (1.299 to 2.083)84.6% and 0.001 and 0.001

Cigarette smokingNo
>30%
≤30%5−0.064 (−0.805 to 0.678)39.4% and 0.158 and 0.867

Medication: DiureticNo
>70%
≤70%40.402 (−0.488 to 1.292)0.0% and 0.753 and 0.376

Medication: ACEINo
>70%
≤70%40.402 (−0.488 to 1.292)0.0% and 0.753 and 0.376

Medication: StatinNo
>70%
≤70%40.402 (−0.488 to 1.292)0.0% and 0.753 and 0.376

Medication: Beta-BlockerNo
>70%
≤70%40.402 (−0.488 to 1.292)0.0% and 0.753 and 0.376

Anti-coagulant status codesYes, probably
121.819 (0.693 to 2.945)65.9% and 0.087 and 0.002
2
32−0.021 (−1.381 to 1.340)0.0% and 0.477 and 0.976
440.852 (0.001 to 1.704)0.0% and 0.985 and 0.050
532.230 (1.787 to 2.673)93.9% and 0.001 and 0.001
6

AFNo
Chronic50.062 (−0.635 to 0.759)46.9% and 0.110 and 0.861
Non-chronic32.611 (2.141 to 3.082)18.5% and 0.293 and 0.001

Type of AFNo
Paroxysmal11.000 (−1.122 to 3.122)
Persistent
Permanent40.617 (−0.215 to 1.450)0.0% and 0.603 and 0.146

Hb

Year of publicationNo
>2000250.024 (−0.038 to 0.087)91.1% and 0.001 and 0.444
≤200021.076 (0.522 to 1.630)85.2% and 0.009 and 0.001

Geographic areaYes, probably
Asian2−0.048 (−0.366 to 0.271)0.0% and 0.758 and 0.769
European21−0.150 (−0.219 to −0.081)76.8% and 0.001 and 0.001
Africa
North American40.994 (0.840 to 1.149)89.4% and 0.001 and 0.001
South American
Australia

Design of studyYes, probably
Cohort6−0.093 (−0.142 to −0.044)0.0% and 0.488 and 0.001
Case-control210.102 (0.024 to 0.181)92.8% and 0.001 and 0.011

Number of populationNo
>3001−0.100 (−0.643 to 0.443)
≤300260.039 (−0.023 to 0.102)91.4% and 0.001 and 0.216

Mean ageNo
>60 years200.033 (−0.032 to 0.098)92.5% and 0.001 and 0.317
≤60 years5−0.077 (−0.297 to 0.143)73.5% and 0.005 and 0.494

MaleNo
>70%6−0.040 (−0.143 to 0.063)75.1% and 0.001 and 0.447
≤70%190.062 (−0.017 to 0.140)92.7% and 0.001 and 0.123

Diabetes mellitusYes, probably
>30%2−0.048 (−0.366 to 0.271)0.0% and 0.758 and 0.769
≤30%230.027 (−0.036 to 0.091)91.8% and 0.001 and 0.401

HypertensionYes, probably
>70%2−0.275 (−0.481 to 0.070)0.0% and 0.583 and 0.009
≤70%230.055 (−0.011 to 0.120)91.6% and 0.001 and 0.102

Cigarette smokingYes, probably
>30%8−0.054 (−0.223 to 0.114)0.0% and 0.597 and 0.529
≤30%10−0.308 (−0.422 to −0.193)80.8% and 0.001 and 0.001

Medication: DiureticNo
>70%
≤70%9−0.184 (−0.267 to −0.100)84.9% and 0.001 and 0.001

Medication: ACEINo
>70%
≤70%13−0.192 (−0.272 to −0.112)80.6% and 0.001 and 0.001

Medication: StatinNo
>70%
≤70%10−0.017 (−0.114 to 0.079)58% and 0.011 and 0.729

Medication: Beta-BlockerNo
>70%
≤70%14−0.172 (−0.251 to −0.094)80.8% and 0.001 and 0.001

Anti-coagulant status codesNo
121.076 (0.522 to 1.630)85.2% and 0.009 and 0.001
21−0.100 (−0.643 to 0.443)
36−0.183 (−0.355 to −0.011)73.3% and 0.002 and 0.037
49−0.005 (−0.100 to 0.090)63.2% and 0.005 and 0.913
580.148 (0.049 to 0.247)96.8% and 0.001 and 0.004
61−0.200 (−0.550 to 0.150)

AFNo
Chronic8−0.320 (−0.443 to −0.196)85.2% and 0.001 and 0.001
Non-chronic50.543 (0.418 to 0.668)96.1% and 0.001 and 0.001

Type of AFNo
Paroxysmal10.500 (−0.059 to 1.059)
Persistent10.200 (−0.553 to 0.953)
Permanent4−0.458 (−0.596 to −0.320)68.5% and 0.023 and 0.001

Occurrence of AF

Platelet count

Year of publication
>2000All of studies: after 2000
≤2000

Geographic areaYes, probably
Asian214.48 (−1.95 to 30.91)28.6% and 0.237 and 0.084
European2−12.96 (−25.66 to −0.272)40.8% and 0.194 and 0.045
Africa
North American
South American
Australia

Design of studyNo
Cohort30.217 (−0.188 to 0.622)50.9% and 0.130 and 0.294
Case-control120.45 (1.27 to 39.63)

Number of population
>300All of studies: ≤300
≤300

Mean ageNo
>60 years3−0.132 (−13.084 to 12.82)78.8% and 0.009 and 0.984
≤60 years1−6.60 (−22.517 to 9.317)

MaleNo
>70%
≤70%3−2.78 (−13.37 to 7.79)79.6% and 0.007 and 0.606

Diabetes mellitus
>30%All of studies: ≤30%
≤30%

Hypertension
>70%All of studies: ≤70%
≤70%

Cigarette smokingYes, probably
>30%24.43 (−7.81 to 16.80)77.9% and 0.033 and 0.478
≤30%2−17.38 (−34.94 to 0.174)22.3% and 0.257 and 0.052

Medication: Diuretic
>70%No Data
≤70%

Medication: ACEINo
>70%
≤70%20.238 (−13.93 to 14.41)89.4% and 0.002 and 0.974

Medication: StatinNo
>70%
≤70%3−0.132 (−13.08 to 12.82)78.8% and 0.009 and 0.984

Medication: Beta-BlockerNo
>70%
≤70%20.238 (−13.93 to 14.41)89.4% and 0.002 and 0.974

Anti-coagulant status codesYes, probably
1
2
3
424.432 (−7.817 to 16.68)77.9% and 0.033 and 0.478
52−17.38 (−34.94 to 0.174)22.3% and 0.257 and 0.052
6

AF
ChronicAll of studies: non–chronic
Non-chronic

Type of AFNo
Paroxysmal20.238 (−13.93 to 14.41)89.4% and 0.002 and 0.974
Persistent
Permanent

WBC

Year of publication
>2000All of studies: after 2000
≤2000

Geographic areaYes, probably
Asian110.136 (−0.013 to 0.284)34.7% and 0.121 and 0.073
European110.347 (0.120 to 0.574)65.1% and 0.001 and 0.003
Africa
North American
South American
Australia

Design of studyYes, probably
Cohort200.202 (0.077 to 0.326)58.6% and 0.001 and 0.002
Case-control2−0.344 (−2.282 to 1.594)0.0% and 0.710 and 0.728

Number of populationNo
>30030.146 (−0.030 to 0.321)63.6% and 0.064 and 0.103
≤300190.254 (0.077 to 0.430)55.1% and 0.002 and 0.005

Mean ageYes, probably
>60 years100.097 (−0.076 to 0.269)0.0% and 0.498 and 0.272
≤60 years120.310 (0.131 to 0.489)68.7% and 0.001 and 0.001

MaleNo
>70%90.251 (0.093 to 0.410)49.4% and 0.045 and 0.002
≤70%110.107 (−0.108 to 0.323)62.4% and 0.003 and 0.328

Diabetes mellitusNo
>30%
≤30%170.286 (0.149 to 0.423)55.7% and 0.003 and 0.001

HypertensionNo
>70%1−0.030 (−0.560 to 0.50)
≤70%200.215 (0.087 to 0.344)58.1% and 0.001 and 0.001

Cigarette smokingYes, probably
>30%50.707 (0.376 to 1.037)63% and 0.029 and 0.001
≤30%60.032 (−0.261 to 0.325)0.0% and 0.416 and 0.832

Medication: DiureticNo
>70%1−0.40 (−1.087 to 0.287)
≤70%30.202 (−0.012 to 0.417)0.0% and 0.776 and 0.064

Medication: ACEINo
>70%
≤70%130.217 (0.067 to 0.367)68.8% and 0.001 and 0.005

Medication: StatinNo
>70%
≤70%110.321 (0.117 to 0.525)71.9% and 0.001 and 0.002

Medication: Beta-BlockerNo
>70%2−0.159 (−0.654 to 0.335)0.0% and 0.322 and 0.528
≤70%70.083 (−0.087 to 0.252)42.1% and 0.110 and 0.339

Anti-coagulant status codesYes, probably
1
24−0.097 (−0.476 to 0.282)0.0% and 0.860 and 0.617
3
420.341 (−0.269 to 0.952)0.0% and 0.482 and 0.273
5160.230 (0.095 to 0.365)64.5% and 0.001 and 0.001
6

AFNo
Chronic
Non-chronic210.181 (0.049 to 0.314)56.3% and 0.001 and 0.007

Type of AFNo
Paroxysmal7−0.036 (−0.291 to 0.218)25.6% and 0.233 and 0.781
Persistent7−0.077 (−0.383 to 0.229)0.0% and 0.887 and 0.621
Permanent

NLR

Year of publication
>2000All of studies: after 2000
≤2000

Geographic areaYes, probably
Asian30.047 (−0.124 to 0.218)0.0% and 0.552 and 0.588
European40.750 (0.565 to 0.936)35.1% and 0.201 and 0.001
Africa
North American
South American
Australia

Design of study
CohortAll of studies: cohort
Case-control

Number of populationNo
>30020.035 (−0.142 to 0.212)0.0% and 0.340 and 0.698
≤30050.712 (0.533 to 0.891)41.9% and 0.142 and 0.001

Mean ageYes, probably
>60 years30.476 (0.183 to 0.770)21.4% and 0.280 and 0.001
≤60 years40.346 (0.207 to 0.485)90.8% and 0.001 and 0.001

MaleNo
>70%20.035 (−0.142 to 0.212)0.0% and 0.340 and 0.698
≤70%30.804 (0.610 to 0.997)0.0% and 0.593 and 0.001

Diabetes mellitus
>30%All of studies: ≤30%
≤30%

Hypertension
>70%All of studies: ≤70%
≤70%

Cigarette smokingNo
>30%20.851 (0.626 to 1.077)0.0% and 0.530 and 0.001
≤30%30.476 (0.183 to 0.770)21.4% and 0.280 and 0.001

Medication: Diuretic
>70%No data
≤70%

Medication: ACEINo
>70%
≤70%20.819 (0.615 to 1.023)0.0% and 0.360 and 0.001

Medication: StatinNo
>70%
≤70%30.767 (0.572 to 0.963)45.6% and 0.159 and 0.001

Medication: Beta-BlockerNo
>70%0.670 (0.291 to 1.049)
≤70%1

Anti-coagulant status codesNo
1
210.150 (−0.499 to 0.799)
3
4
560.379 (0.250 to 0.507)
6

AFNo
Chronic
Non-chronic60.527 (0.370 to 0.684)80% and 0.001 and 0.001

Type of AFNo
Paroxysmal20.670 (0.349 to 0.991)0.0% and 1.000 and 0.001
Persistent10.150 (−0.499 to 0.799)
Permanent

RDW

Year of publication
>2000All of studies: after 2000
≤2000

Geographic areaYes, probably
Asian30.165 (0.051 to 0.279)79.1% and 0.008 and 0.005
European20.803 (0.560 to 1.045)0.0% and 0.425 and 0.001
Africa
North American
South American
Australia

Design of studyNo
Cohort40.264 (0.155 to 0.372)90.3% and 0.001 and 0.001
Case-control10.440 (0.102 to 0.778)

Number of populationNo
>30010.100 (−0.023 to 0.223)
≤30040.705 (0.516 to 0.894)31.2% and 0.225 and 0.001

Mean ageYes, probably
>60 years30.165 (0.051 to 0.279)79.1% and 0.008 and 0.005
≤60 years20.803 (0.560 to 1.045)0.0% and 0.425 and 0.001

MaleYes, probably
>70%20.129 (0.008 to 0.250)85.1% and 0.010 and 0.036
≤70%30.680 (0.483 to 0.877)43.8% and 0.169 and 0.001

Diabetes mellitus
>30%All of studies: ≤30%
≤30%

Hypertension
>70%≤70%
≤70%

Cigarette smokingNo
>30%30.680 (0.483 to 0.877)43.8% and 0.169 and 0.001
≤30%

Medication: DiureticNo
>70%1(0.329 to 1.671)
≤70%10.100 (−0.023 to 0.223)

Medication: ACEINo
>70%
≤70%30.165 (0.051 to 0.279)79.1% and 0.008 and 0.005

Medication: StatinNo
>70%
≤70%10.440 (0.102 to 0.778)

Medication: Beta-BlockerNo
>70%11.000 (0.329 to 1.671)
≤70%20.140 (0.024 to 0.255)70.8% and 0.064 and 0.018

Anti-coagulant status codesNo
1
2
3
420.661 (0.460 to 0.861)60.3% and 0.113 and 0.001
530.143 (0.023 to 0.263)81.2% and 0.005 and 0.020
6

AF
ChronicAll of studies: non–chronic
Non-chronic

Type of AFNo
Paroxysmal20.511 (0.188 to 0.834)46.9% and 0.170 to 0.002
Persistent
Permanent

Hb

Year of publication
>2000All of studies: after 2000
≤2000

Geographic areaNo
Asian50.046 (−0.133 to 0.226)43.2% and 0.133 and 0.613
European40.007 (−0.306 to 0.319)0.0% and 0.539 and 0.967
Africa
North American
South American
Australia

Design of studyNo
Cohort80.029 (−0.131 to 0.189)23.1% and 0.246 and 0.723
Case-control10.170 (−0.506 to 0.846)

Number of populationNo
>30020.095 (−0.099 to 0.288)54.4% and 0.139 and 0.336
≤3007−0.070 (−0.331 to 0.191)1.2% and 0.451 and 0.598

Mean AgeNo
>60 years5−0.057 (−0.258 to 0.144)3.0% and 0.390 and 0.576
≤60 years40.177 (−0.069 to 0.422)1.5% and 0.385 and 0.159

MaleNo
>70%30.056 (−0.133 to 0.245)65.4% and 0.056 and 0.563
≤70%50.035 (−0.248 to 0.319)0.0% and 0.672 and 0.807

Diabetes mellitus
>30%All of studies: ≤30%
≤30%

Hypertension
>70%All of studies: ≤70%
≤70%

Cigarette smokingNo
>30%40.070 (−0.233 to 0.374)0.0% and 0.582 and 0.650
≤30%2−0.314 (−0.933 to 0.306)0.0% and 0.645 and 0.321

Medication: DiureticNo
>70%1−0.800 (−1.706 to 0.106)
≤70%10.00 (−0.231 to 0.231)

Medication: ACEINo
>70%
≤70%5−0.047 (−0.238 to 0.144)0.0% and 0.494 and 0.630

Medication: StatinNo
>70%
≤70%4−0.096 (−0.442 to 0.250)0.0% and 0.734 and 0.587

Medication: Beta-BlockerNo
>70%1−0.800 (−1.706 to 0.106)
≤70%30.002 (−0.208 to 0.213)0.0% and 0.782 and 0.984

Anti-coagulant status codesNo
1
2
3
420.236 (−0.161 to 0.632)0.0% and 0.814 and 0.244
570.00 (−0.169 to 0.169)25.5% and 0.234 and 0.998
6

AFNo
Chronic
Non-chronic8−0.031 (−0.204 to 0.142)0.0% and 0.513 and 0.727

Type of AFNo
Paroxysmal3−0.070 (−0.531 to 0.391)0.0% and 0.603 and 0.766
Persistent
Permanent
  93 in total

1.  Activated inflammation is related to the incidence of atrial fibrillation in patients with acute myocardial infarction.

Authors:  Tohru Yoshizaki; Ken Umetani; Yuri Ino; Souichirou Takahashi; Masahiko Nakamura; Toshikuni Seto; Kazunori Aizawa
Journal:  Intern Med       Date:  2012-06-15       Impact factor: 1.271

2.  Monocyte Toll-Like Receptor Expression in Patients With Atrial Fibrillation.

Authors:  Kadri Murat Gurses; Duygu Kocyigit; Muhammed Ulvi Yalcin; Hande Canpinar; Hikmet Yorgun; Mehmet Levent Sahiner; Ergun Baris Kaya; Mehmet Ali Oto; Necla Ozer; Dicle Guc; Kudret Aytemir
Journal:  Am J Cardiol       Date:  2016-02-17       Impact factor: 2.778

3.  Can neutrophil/lymphocyte ratio predict recurrence of non-valvular atrial fibrillation after cardioversion?

Authors:  Alpay Arıbaş; Hakan Akıllı; Enes Elvin Gül; Mehmet Kayrak; Kenan Demir; Cetin Duman; Hajrudin Alibasiç; Mehmet Yazıcı; Kurtuluş Ozdemir; Hasan Gök
Journal:  Anadolu Kardiyol Derg       Date:  2012-12-07

4.  Red blood cell distribution width and atrial fibrillation in patients with sick sinus syndrome.

Authors:  Panagiotis Korantzopoulos; Konstantinos Kyrlas; Tong Liu; Guangping Li; John A Goudevenos
Journal:  J Cardiol       Date:  2015-08-25       Impact factor: 3.159

5.  Relationship between mean platelet volume and coronary blood flow in patients with atrial fibrillation.

Authors:  Chong Feng; Weiyi Mei; Chufan Luo; Ming Long; Xun Hu; Yong Huang; Yuantao Hao; Zhimin Du
Journal:  Heart Lung Circ       Date:  2012-09-13       Impact factor: 2.975

6.  C-reactive protein and atrial fibrillation in idiopathic dilated cardiomyopathy.

Authors:  Shimo Dai; Shu Zhang; Ying hua Guo; Jianmin Chu; Wei Hua; Fang zheng Wang
Journal:  Clin Cardiol       Date:  2009-09       Impact factor: 2.882

Review 7.  Mean platelet volume and coronary artery disease: a systematic review and meta-analysis.

Authors:  Nakarin Sansanayudh; Thunyarat Anothaisintawee; Dittaphol Muntham; Mark McEvoy; John Attia; Ammarin Thakkinstian
Journal:  Int J Cardiol       Date:  2014-06-28       Impact factor: 4.164

8.  Pre-ablative predictors of atrial fibrillation recurrence following pulmonary vein isolation: the potential role of inflammation.

Authors:  Konstantinos P Letsas; Reinhold Weber; Gerd Bürkle; Constantinos C Mihas; Jan Minners; Dietrich Kalusche; Thomas Arentz
Journal:  Europace       Date:  2008-11-13       Impact factor: 5.214

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.  The association between mean platelet volume and spontaneous echocardiographic contrast or left atrial thrombus in patients with mitral stenosis.

Authors:  Kevser Gülcihan Balcı; Orhan Maden; Mustafa Mücahit Balcı; Fatih Şen; Sefa Ünal; Serdar Kuyumcu; Meryem Kara; Hatice Selçuk; Mehmet Timur Selcuk; Ahmet Temizhan
Journal:  Anatol J Cardiol       Date:  2016-04-25       Impact factor: 1.596

View more
  15 in total

Review 1.  The role of red blood cell distribution width (RDW) in cardiovascular risk assessment: useful or hype?

Authors:  Cristiano Fava; Filippo Cattazzo; Zhi-De Hu; Giuseppe Lippi; Martina Montagnana
Journal:  Ann Transl Med       Date:  2019-10

2.  Systemic immune-inflammation index as a novel predictor of atrial fibrillation after off-pump coronary artery bypass grafting.

Authors:  Dursun Topal; Ufuk Turan Kursat Korkmaz; Yusuf Velioglu; Ahmet Yuksel; Ibrahim Donmez; Erhan Renan Uçaroğlu; Seyit Ali Kayis
Journal:  Rev Assoc Med Bras (1992)       Date:  2022-09       Impact factor: 1.712

3.  Association between Neutrophil-Lymphocyte and Platelet-Lymphocyte Ratios and Coronary Artery Calcification Score among Asymptomatic Patients: Data from a Cross-Sectional Study.

Authors:  Carlos V Serrano; Fernando R de Mattos; Fábio G Pitta; Cesar H Nomura; James de Lemos; José Antonio F Ramires; Roberto Kalil-Filho
Journal:  Mediators Inflamm       Date:  2019-03-26       Impact factor: 4.711

4.  Red cell distribution width associations with clinical outcomes: A population-based cohort study.

Authors:  Marcello Tonelli; Natasha Wiebe; Matthew T James; Christopher Naugler; Braden J Manns; Scott W Klarenbach; Brenda R Hemmelgarn
Journal:  PLoS One       Date:  2019-03-13       Impact factor: 3.240

5.  Simple hematological predictors of AF recurrence in patients undergoing atrial fibrillation ablation.

Authors:  George Bazoukis; Konstantinos P Letsas; Konstantinos Vlachos; Athanasios Saplaouras; Dimitrios Asvestas; Konstantinos Tyrovolas; Aikaterini Rokiza; Eirini Pagkalidou; Gary Tse; Stavros Stavrakis; Antonios Sideris; Michael Efremidis
Journal:  J Geriatr Cardiol       Date:  2019-09       Impact factor: 3.327

6.  Utility of platelet-to-lymphocyte ratio to support the diagnosis of acute deep vein thrombosis.

Authors:  Yusuf Velioğlu; Ahmet Yüksel
Journal:  Turk Gogus Kalp Damar Cerrahisi Derg       Date:  2019-10-23       Impact factor: 0.332

7.  Early Mortality of Brain Infarction Patients and Red Blood Cell Distribution Width.

Authors:  Leonardo Lorente; María M Martín; Pedro Abreu-González; Antonia Pérez-Cejas; Agustín F González-Rivero; Luis Ramos-Gómez; Mónica Argueso; Jordi Solé-Violán; Juan J Cáceres; Alejandro Jiménez; Victor García-Marín
Journal:  Brain Sci       Date:  2020-03-26

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
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.