Literature DB >> 35145683

Impact of thyroid disease in patients with atrial fibrillation: Analysis from the JoFib registry.

Hanna Al-Makhamreh1,2, Abdallah Al-Ani2, Dana Alkhulaifat2, Liza Shaban2, Neveen Salah2, Rusul Almarayaty2, Yazan Al-Huneidy2, Ayman Hammoudeh3.   

Abstract

BACKGROUND: Thyroid disease is a well-established risk factor for atrial fibrillation (AF). However, only a handful of studies examined its impact on treatment. This study aims to report the prevalence rate of thyroid disease in patients with AF and to demonstrate the effect of thyroid disease on AF treatment.
MATERIALS AND METHODS: We retrospectively analyzed the Jordanian Atrial Fibrillation Study (JoFib). Among Jordan and Palestine, patients with AF were evaluated for their sociodemographic, clinical, and pharmacological characteristics.
RESULTS: A total of 2000 patients with AF (53.3% males, mean age 67.6 ± 13.1 years) were enrolled in the JoFib registry from May 2019 to November 2020. Thyroid disease was present in 210 (10.5%) patients. Hypertension, diabetes mellitus, and dyslipidemia were the most common comorbidities among patients with thyroid history (75.2%, 51.0%, and 45.7%, respectively). Diabetes mellitus (p = .04), pulmonary hypertension (p = .01), and chronic kidney disease (p = .01) were significantly higher in this particular subgroup. Patients with thyroid disease demonstrated significantly higher usage of anticoagulants (p = .02).
CONCLUSION: Despite having similar stroke and bleeding risks, patients with thyroid disease demonstrated meaningful differences in their baseline characteristics. Prospective studies are required to assess the influence of thyroid hormone fluctuations on the progression of AF.
© 2022 The Authors.

Entities:  

Keywords:  Anticoagulation; Atrial fibrillation; Middle east; Prevalence; Thyroid disorders

Year:  2022        PMID: 35145683      PMCID: PMC8818533          DOI: 10.1016/j.amsu.2022.103325

Source DB:  PubMed          Journal:  Ann Med Surg (Lond)        ISSN: 2049-0801


Introduction

Atrial fibrillation (AF) is the most common cardiac arrhythmia worldwide, affecting more than 30 million persons all over the globe [1]. Characterized by ever increasing prevalence and incidence rates, AF contributes significantly to morbidity and mortality through increased risk of stroke, heart failure and hospitalizations [2]. In particular, AF increases the risk of stroke by 5 folds; these strokes are of greater severity and lethality than those of their non-AF counterparts [2]. Despite its slightly increased prevalence in men, AF's adverse complications are more pronounced in women [3]. A multitude of clinical conditions predispose to AF including but not limited to hypertension, obesity, metabolic syndrome, diabetes, obstructive sleep apnea, ischemic heart disease, congestive heart failure, and thyroid disease [[1], [2], [3], [4]]. Overt and occult hyperthyroidism is a documented risk factor of AF [1,2,4,5]. The prevalence rate of AF in patients with hyperthyroidism is 10–15%, while its incidence is 1.41 per 1,000 patients [5,6]. On the other end of the spectrum, hypothyroidism is associated with an increased risk of cardiovascular events, even though its direct association with AF is still conflicting [1]. Data from large cohorts suggest that variations in thyroid hormones within their normal reference range is associated with cardiac complications. In particular, higher free thyroxine (T4) is associated with higher risk of heart failure, sudden cardiac death, and AF [[7], [8], [9]]. Nevertheless, the impact of thyroid hormone imbalance on risk of AF is still underestimated [6,9]. The burden of thyroid disease on patients with AF could be anticipated from the systematic effects of thyroid hormone as it contributes to increased vascular resistance, cardiac contractility, heart rate and left ventricular mass [1]. In addition, high levels of thyroid hormones lead to increased rates of arrythmia, increased frequency of atrial premature beats, and are prothrombotic [1,4]. These mechanisms may clarify the impact of hyperthyroidism but not that of hypothyroidism, despite the overlapping risk factors for both disease entities [4]. Furthermore, since thyroid dysfunction impacts response to anticoagulants, the safety and efficacy of traditional anticoagulation regimens in AF patients with thyroid disease are yet to be elucidated [4,10]. Such observations imply risk-assessment and therapeutic concerns about the feasibility of including T4 as part of thyroid screening for patients with AF, and the risks associated with thyroid replacement therapy. While AF is on a rising trend in Asia, epidemiological data on Middle Eastern patients with AF are severely lacking, which leads to ambiguous treatment regimens in terms of safety and efficacy [11]. Furthermore, global reviews and local registries fail to account for thyroid disease as a risk factor for patients with AF [[12], [13], [14], [15]]. Therefore, this paper aims to determine the prevalence of thyroid disorders in patients with AF among a Middle Eastern cohort and predict the cardiovascular-oriented characteristics and risk factors associated with the development of thyroid disease in AF patients.

Materials and Methods

Study population

We performed a retrospective analysis on AF patients recruited as part of the Jordanian Atrial Fibrillation Study (JoFib) (NCT03917992) [16]. JoFib is a prospective, observational, multi-center study registry aimed to explore the characteristics, treatment patterns and outcomes of patients with AF recruited from 19 Jordanian hospitals, 30 out-patient clinics and one hospital in the Palestinian territories from May 2019 to November 2020. The registry enrolled 2000 patients who were either newly diagnosed with AF or have existing AF, and are older than 18 years of age. The manuscript fully complies with the STROCSS criteria for reporting [17].

Data collection

We collected patients' data through standardized forms at time of enrollment, and at 1, 6, and 12 months of follow up. Baseline data, with which this study was conducted, were sociodemographic characteristics, baseline clinical features, co-morbidities, and medication history. The CHA2DS2-VASc [18] and HAS-BLED [19] scores, which estimate the risk of stroke and major bleeding in patients with non-rheumatic AF, were calculated for all patients. In addition, patients’ echocardiographic data were extracted when applicable and/or available. Demographic data included age (in years), gender, and BMI (kg/cm2). Baseline clinical characteristics included presence of comorbidities, smoking status, AF characteristics (symptoms, frequency, type), history of AF complications (frequency of cerebrovascular strokes in the past year, type of old strokes, stroke recurrence rate and presence, site and recurrence rate of systemic embolization), and history of procedures (ablation, presence of occluder device, electric cardioversion, permanent pacemaker implantation). In addition, the study extracted medications history (e.g., anticoagulants, anti-platelets, anti-arrhythmics). Presence or absence of thyroid disease was determined based on (1) prior diagnosis made by a physician or (2) prescription of thyroid replacement therapy. Diagnosis of AF is confirmed by (1) 12-lead EKG, (2) rhythm strip, lasting >30 seconds, (3) one or more episodes of AF on Holter monitor, or (4) a diagnosis by a treating cardiologist. The definitions of AF types, namely first attack of AF, paroxysmal AF, persistent AF, and permanent AF, were based according to the American College of Cardiology/American Heart Association/European Society of Cardiology (ACC/AHA/ESC) 2019 Guidelines for the Treatment of patients with AF [20].

Statistical analysis

All statistical analysis was conducted on the statistical package for social sciences (SPSS) version 23.0 (SPSS Inc., Chicago, IL, USA). Frequencies were reported for categorical data [n (%)] while continuous data were reported as means ± standard deviation (n ± SD). Associations between presence of thyroid disease and various categorical variables were evaluated through Chi-Square testing. ANOVA and student's t-test were utilized to detect significant mean differences between categories of thyroid disease and age and left ventricular ejection fraction. A p-value equal or less than 0.05 is considered statistically significant.

Ethical approval

The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by institutional/regional/national ethics/committee/ethics board of the University of Jordan (NO.: 10/2021/416) and individual consent for this retrospective analysis was waived.

Results

Baseline characteristics

Among the 2000 AF patients included in the study, the mean age of participants was 67.6 ± 13.1 with 1067 (53.3%) being males. Thyroid disease was present in 210 (10.5%) patients. Of those with thyroid disease, 20.4% had normal weight, 30.6% were overweight, and 49.0% were obese. In terms of comorbidities, hypertension, diabetes mellitus, and dyslipidemia were present in 75.2%, 51.0%, and 45.7% in AF patients with thyroid disease, respectively. In addition, about 8% of those patients were active smokers. However, active smokers with more likely not to have thyroid disease (p = .025). The most common type of AF in patients with thyroid disease was non-paroxysmal AF (65.2%). In addition, the most prevalent etiology of AF in this group was non-valvular AF (89.0%). Associated symptoms included palpitations (42.4%), shortness of breath (41.0%), fatigue (28.6%), dizziness (15.2%), syncope (3.8%), and chest pain (1.9%), of which only fatigue (p = .005) and shortness of breath (p = .020) were significantly different in comparison to their non-thyroid counterparts. Out of the recorded comorbidities, pulmonary hypertension (p = .017) and chronic kidney disease (p = .015) were significantly higher in patients with thyroid disorders, while the prevalence of coronary artery disease was significantly higher in their non-thyroid counterparts (p = .028). Risks of stroke and of major bleeding were not significantly different between groups with or without thyroid disease as evident from the relative distributions of the CHA2DS2-VASc (p = .179) and HAS-BLED (p = .731) scores (see Table 1).
Table 1

Demographic and clinical characteristics of AF patients with/out thyroid disorders.

Clinical featureTotal n (%)AF/Thyroid disease n (%)AF/no Thyroid disease n (%)p-value
Age in years (mean ± SD)67.6 ± 13.169.9 ± 11.067.4 ± 13.3.007
Gender<.01
Male933 (46.7%)54 (25.7%)879 (49.1%)
Female1067 (53.3%)156 (74.3%)911 (50.9%)
Medical History
Hypertension1486 (74.3%)158 (75.2%)1328 (74.2%).802
Diabetes Mellitus882 (44.1%)107 (51%)775 (43.3%).040
Dyslipidemia878 (43.9%)96 (45.7%)782 (43.7%).607
Currently smokers273 (13.7%)16 (7.6%)257 (14.4%).025
BMI.071
X ≥ 24.9409 (22.8%)38 (20.4%)371 (23.0%)
25 > X > 29.9649 (36.1%)57 (30.6%)592 (36.7%)
X ≥ 30739 (41.1%)91 (49.0%)648 (40.2%)
Total1797 (100%)186 (10.4%)1611 (89.6%)
Type of AF.649
Paroxysmal727 (36.4%)73 (34.8%)654 (36.5%)
Non-paroxysmal1273 (63.6%)137 (65.2%)1136 (63.5%)
Total2000 (100%)210 (10.5%)1790 (89.5%)
Etiology of AF.735
Valvular177 (8.8%)23 (21.0%)154 (8.5%)
Non-valvular1823 (91.2%)187 (89.0%)1636 (91.4%)
2000 (100%)210 (10.5%)1790 (89.5%)
AF symptoms
Palpitations859 (43.0%)89 (42.4%)770 (43%).883
SOB673 (33.7%)86 (41.0%)587 (32.8%).020
Fatigue420 (21.0%)60 (28.6%)360 (20.1%).005
Dizziness226 (11.3%)32 (15.2%)194 (10.8%).065
Syncope45 (2.3%)8 (3.8%)37 (2.1%).133
Chest pain34 (1.7%)4 (1.9%)30 (1.7%).776
Asymptomatic591 (29.5%)59 (28.1%)532 (29.7%).689
Comorbid diseases
Stroke or systemic embolization319 (15.9%)35 (16.6%)284 (15.8%).907
Heart failure467 (23.3%)47 (22.3%)420 (23.4%).796
Left ventricular hypertrophy707 (39.1%)71 (37.4%)636 (39.3%).638
Coronary artery disease225 (11.2%)14 (6.6%)211 (11.7%).028
Congenital heart disease11 (0.5%)1 (0.4%)10 (0.5%).999
Pulmonary hypertension543 (27.2%)72 (34.3%)471 (26.3%).017
Sleep apnea76 (3.8%)10 (4.8%)66 (3.7%).444
Chronic kidney disease181 (9.0%)29 (13.8%)152 (8.5%).015
Active malignancy117 (5.8%)10 (4.8%)107 (5.9%).995
CHA2DS2-VASc score.179
Score 1 in women and 0 in men (1)173 (8.6%)12 (5.7%)161 (8.9%)
Score 2 in women and 1 in men (2)251 (12.5%)23 (10.9%)228 (12.7%)
Score ≥ 3 in women and ≥ 2 in men (3)1575 (78.7%)175 (83.3%)1400 (78.2%)
HAS-BLED score.731
0266 (13.3%)27 (12.9%)239 (13.4%)
1728 (36.4%)72 (34.3%)656 (36.6%)
2623 (31.1%)69 (32.9%)554 (30.9%)
≥ 3384 (19.2%)42 (20%)341 (19.1%)
Echocardiography findings
LVEF (mean ± SD)53.6 ± 12.454.6 ± 12.853.5 ± 12.3.261
Moderate to severe rhematic mitral stenosis66 (3.3%)9 (4.3%)57 (3.2%).411
Metallic prosthetic valve111 (5.5%)14 (6.7%%)97 (5.4%).427
Patients' pharmacological characteristics are reported in Table 2. With respect to the patients’ pharmacological history, AF patients with thyroid disorders were significantly more likely to use anticoagulants (p = .027), whether in the form of vitamin K antagonists (33.8%) or oral anticoagulants (54.3%). On the other hand, AF patients without thyroid disease had significantly higher usage of antiplatelets (p = .019). The most prevalent types of antiarrhythmics within both groups of patients were beta blockers (80.0%) and amiodarone (20.0%). The sociodemographic characteristics, clinical features and pharmacologic histories of patients with specific thyroid statuses (hyper-, eu-, or hypothyroidism) are reported in Table 3.
Table 2

Pharmacological history of AF patients with/out thyroid disorders.

VariablesTotal n (%)AF/Thyroid disease n (%)AF/no Thyroid disease n (%)p-value
Anticoagulants.027
Use of anticoagulants1625 (81.3%)185 (88.1%)1440 (80.4%)
Vitamin K antagonist632 (31.6%)71 (33.8%)561 (31.3%)
Oral anticoagulants993 (49.7%)114 (54.3%)879 (49.1%)
Antiplatelets
Use of antiplatelets925 (46.3%)81 (38.6%)844 (47.2%).019
Antiarrhythmics
Beta blockers1603 (80.2%)168 (80%)1435 (80.2%).927
Amiodarone403 (20.2%)43 (20.5%)360 (20.1%).928
Calcium Channel Blockers199 (10.0%)23 (11.0%)176 (9.8%).626
Digoxin299 (15.0%)32 (15.2%)267 (14.9%).919
Others
RAAS746 (37.3%)85 (40.5%)661 (36.9%).327
Diuretics759 (38.0%)77 (36.7%)666 (37.2%).051
Statins727 (36.4%)93 (44.3%)650 (36.3%).940
Table 3

Demographic and clinical characteristics of 210 AF patients with thyroid disorders with reference to thyroid status.

Clinical featureAF/Hypothyroidism n (%)AF/Hyperthyroidism n (%)AF/Euthyroid n (%)p-value
Age in years (mean ± SD)70.0 ± 11.070.5 ± 11.667.1 ± 9.0.779
Gender.029
Male44 (20.9%)7 (3.3%)3 (1.4%)
Female146 (69.5%)6 (2.8%)4 (1.9%)
Medical History
Hypertension145 (69.0%)10 (4.7%)3 (1.4%).130
Diabetes Mellitus95 (45.2%)8 (3.8%)4 (1.9%).684
Dyslipidemia85 (40.4%)9 (4.2%)2 (0.9%).150
Currently smokers12 (5.7%)3 (1.4%)1 (0.4%).070
BMI.132
X ≥ 24.932 (15.2%)4 (1.9%)2 (0.9%)
25 > X > 29.948 (22.8%)5 (2.3%)4 (1.9%)
X ≥ 3087 (41.4%)3 (1.4%)1 (0.4%)
Type of AF.593
Paroxysmal64 (30.4%)6 (2.8%)3 (1.4%)
Non-paroxysmal126 (60.0%)7 (3.3%)4 (1.9%)
Etiology of AF.277
Valvular19 (9.0%)3 (1.4%)1 (0.4%)
Non-valvular171 (81.4%)10 (3.3%)6 (2.8%)
AF symptoms
Palpitations80 (38.0%)7 (3.3%)2 (0.9%).535
SOB77 (36.6%)7 (3.3%)2 (0.9%).509
Fatigue54 (25.7%)4 (1.9%)2 (0.9%).984
Dizziness29 (13.8%)3 (1.4%)0 (0.0%).391
Syncope7 (3.3%)1 (0.4%)0 (0.0%).664
Chest pain2 (0.9%)1 (0.4%)1 (0.4%).012
Asymptomatic52 (24.7%)4 (1.9%)3 (1.4%).645
Comorbid diseases
Stroke or systemic embolization31 (16.6%)2 (0.9%)2 (0.9%).539
Heart failure41 (19.5%)4 (1.9%)2 (0.9%).687
Left ventricular hypertrophy65 (30.9%)3 (1.4%)3 (1.4%).850
Coronary artery disease11 (5.2%)1 (0.4%)2 (0.9%).059
Congenital heart disease1 (0.4%)0 (0.0%)0 (0.0%).948
Pulmonary hypertension68 (32.3%)2 (0.9%)2 (0.9%).308
Sleep apnea10 (4.7%)0 (0.0%)0 (0.0%).575
Chronic kidney disease27 (12.8%)1 (0.4%)1 (0.4%).804
Active malignancy10 (4.7%)0 (0.0%)0 (0.0%).575
CHA2DS2-VASc score.387
Score 1 in women and 0 in men (1)11 (5.2%)1 (0.4%)0 (0.0%)
Score 2 in women and 1 in men (2)21 (10.0%)0 (0.0%)2 (0.9%)
Score ≥ 3 in women and ≥ 2 in men (3)158 (75.2%)12 (5.7%)5 (2.3%)
HAS-BLED score.693
025 (11.9%)2 (0.9%)0 (0.0%)
168 (32.3%)2 (0.9%)2 (0.9%)
260 28.5%)6 (2.8%)3 (1.4%)
≥ 337 (17.6%)3 (1.4%)2 (0.9%)
Echocardiography findings
LVEF (mean ± SD)54.8 ± 12.353.8 ± 19.649.1 ± 14.0.503
Moderate to severe rhematic mitral stenosis7 (3.3%)2 (0.9%)0 (0.0%).112
Metallic prosthetic valve12 (5.7%)1 (0.4%)1 (0.4%).700
Demographic and clinical characteristics of AF patients with/out thyroid disorders. Pharmacological history of AF patients with/out thyroid disorders. Demographic and clinical characteristics of 210 AF patients with thyroid disorders with reference to thyroid status.

Discussion

We performed a retrospective analysis of the latest Jordanian multicentric registry for patients with AF. Our analysis demonstrated a thyroid disease prevalence rate of 10.5% among patients with AF. This rate is almost twice of that reported in the Gulf Survey of Atrial Fibrillation Events (GULF SAFE) registry, which prospectively observed the baseline characteristics and clinical outcomes of more than 2000 patients with AF [21]. In addition, our detected thyroid disease prevalence is similar to that of global and European AF registries such as the Registry on Cardiac Rhythm Disorders Assessing the Control of Atrial Fibrillation (RecordAF) and the German Competence Network on Atrial Fibrillation (AFNET), both of which report a prevalence rate of 9.0% in enrolled patients with AF [22,23]. Our analysis showed significant differences in baseline characteristics between AF patients with thyroid disease and their non-thyroid counterparts. Notably, significantly higher rates of diabetes mellitus, chronic kidney disease, and pulmonary hypertension were observed in AF patients with thyroid disease. Although the exact mechanisms are not elucidated, thyroid disease is highly prevalent in patients with pulmonary hypertension and chronic kidney disease [24,25]. The prevalence of diabetes mellitus in such patients can be either due to its observed high rates in Jordanians with thyroid dysfunction [26], or a manifestation of diabetes mellitus as a surrogate marker for metabolic syndrome, which is already associated with higher risk of AF [15]. Furthermore, it hypothesized that pulmonary hypertension and thyroid disease may share a common autoimmune etiology [24,27]; on the other hand, chronic kidney disease, which can be theoretically accelerated by hyperthyroidism, impacts the pituitary-thyroid axis and peripheral thyroid hormone metabolism resulting in a hypothyroid state [25]. Assessment tools of risk of stroke or major bleeding such as the CHA2DS2-VASc or HAS-BLED score categories did not significantly change in relation to the presence of thyroid disease. Such results were surprising as the effect of altered thyroid function on higher stroke and bleeding risks is well documented in the literature [1,4,10]. In fact, hyperthyroidism have been shown to increase the risk of thrombotic episodes in AF patients independently of CHA2DS2-VASc score [28]. Yet, the impact of thyroid disease on thrombosis risk could have been underestimated in our population due to inherit concerns towards the validity of such predictive models in a Middle Eastern population, which is a concern that was previously raised by the GULF SAFE study [21]. Interestingly, AF patients with thyroid disease were more likely to complain of shortness of breath and fatigue despite having similar rates of left ventricular hypertrophy and ejection fraction to their non-thyroid counterparts, which could be attributed to the effect of thyroid hormone dysfunction on the cardiovascular system. Management of AF with anticoagulants is a class Ia as recommended by the ACC/AHA/ESC 2019 guidelines [20]. In comparison with vitamin K antagonists, non-vitamin K oral anticoagulants (NOAC) display non-inferiority in terms of efficacy with even higher safety, and are now the preferred method of anticoagulation in patients with non-valvular AF [12]. Nonetheless, the optimal use of anticoagulants represents a therapeutic dilemma due to the increased risk of bleeding [29]. Thyroid disorders impact the hemostatic balance, therefore affecting the efficacy of anticoagulant use in patients with AF. While hyperthyroidism increases the risk of strokes through establishing a prothrombotic state [1], hypothyroidism aggravates bleeding complications by shifting the hemostatic balance towards a hypocoagulable and hyperfibrinolytic state [10]. Nonetheless, a secondary analysis from the Apixaban for Reduction in Stroke and Other Thromboembolic Events in Atrial Fibrillation (ARISTOTLE) trial recommended similar oral anticoagulants management protocols for AF patients with thyroid disease as it demonstrated comparable efficacy and safety outcomes in such population in comparison to their non-thyroid counterparts [4]. Among our cohort, the use of anticoagulation was significantly higher in AF patients with thyroid disease. This is mostly owed to physician concerns over the pharmacodynamic interactions between altered thyroid hormone balance and anticoagulants, and the inherently increased risk of stroke in AF patients with both clinical and subclinical thyroid disease [1,2,30]. Hyperthyroidism is associated with higher risk of AF incidence, prevalence, recurrence, and complications [1,2,4,5]. Higher levels of free thyroxine and low levels of thyroid stimulating hormone are proportionally associated with higher risk of AF [4]. Moreover, a Danish observational cohort of more than 500,000 participants and subsequent studies demonstrated increased AF risk with subclinical hyperthyroidism [6,28]. Despite being associated with a multitude of cardiovascular risk factors and diseases, the relationship between hypothyroidism and AF is still controversial as one secondary analysis of the Framingham study failed to demonstrate increased 10-year risk of AF with hypothyroidism while a Danish cohort reported protective effects of subclinical hypothyroidism on patients with AF [6,31]. This warrants further investigation due to the overlap of risk factors and high density of hypothyroid patients in published AF registries [4,[21], [22], [23]]. A secondary analysis of the ARISTOTLE trial conducted on a randomized cohort of 18,021 AF participants with and without thyroid disease is the only scholarly work investigating distinct clinical findings in between those two groups while also assessing the effectiveness of oral anticoagulants in AF patients with thyroid disease [4]. Their analysis found that AF patients with and without thyroid disease history are similar in terms of rates of systemic strokes/embolization, all-cause mortality, and major bleeding due to oral anticoagulants. Moreover, they demonstrated the superiority of NOACs (apixaban) over warfarin, and the appropriateness of oral anticoagulation management in AF patients with thyroid disease. In contrast to this secondary analysis, we demonstrated no significant differences in terms of type of AF, CHA2DS2-VASc score categories, and pharmacological agents with the exception of anticoagulants, while similarly finding significantly comparable rates of stroke/embolization between AF patients with and without thyroid disease, and significantly higher rates of AF with concomitant thyroid disease in older individuals and females. As far as is known, this is the earliest and largest study examining the epidemiological characteristics among AF patients with a history of thyroid disease throughout the entire Middle Eastern region. AF treatment recommendations for this important and vulnerable population, as set by the ACC/AHA, are scarce and inconclusive. Therefore, this preliminary analysis could act as a starting point for future researchers to advance our understanding of the clinical differences, epidemiological characteristics, and therapy recommendations among AF patients with thyroid disease. However, our analysis is not devoid of limitations. Firstly, the retrospective nature of the study subjected it to various biases including recall bias and selection bias. Secondly, the criteria for diagnosing thyroid disease were not based on laboratory values. Thirdly, the study conducted its analysis on a baseline thyroid disease history, of which thyroid-related treatment data were not available. Finally, the study's sampling protocol (i.e., recruiting patients from specialized cardiology centers) may have affected the generalizability of our results and conclusions.

Conclusions

Our analysis demonstrated a thyroid disease prevalence rate of 10.5% in patients with AF, of which 90.0% were hypothyroid, 6.1% were hyperthyroid, and 3.3% were euthyroid. Despite having similar risks of stroke and major bleeding, patients with thyroid disease had significantly higher rates of comorbidities and usage of anticoagulants. Further prospective studies should be conducted in order to assess the impact of thyroid disease on treatment outcomes. Due to the high prevalence of hypothyroidism within AF registries, a better understanding of its course in AF would aid in tailoring screening and treatment protocols for such a vulnerable population.

Reporting checklist

The authors have completed the STROBE reporting checklist.

Provenance and peer review

Not commissioned, externally peer reviewed.

Ethical approval

The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by institutional/regional/national ethics/committee/ethics board of the University of Jordan (NO.: 10/2021/416) and individual consent for this retrospective analysis was waived.

Sources of funding

This research received no external funding.

Author contribution

Conceptualization, H.A, and A.H; Data curation, R.A, D.A, L.S and Y.A; Formal analysis, A.A, and N.S; Methodology, A.A; Project administration, H.A, and A.H Supervision, H.A, and A.H; Writing – original draft, All authors; Writing – review & editing, all authors. H.A: Hanna Al-Makhamreh, A.H: Ayman Hammoudeh, R.A: Rusul Almarayaty, D.A: Dana Alkhulaifat, L.S: Liza Shaban, Y.A: Yazan Alhuneidy, A.A: Abdallah Al-Ani, N.S: Neveen Salah.

Consent

The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by institutional/regional/national ethics/committee/ethics board of the University of Jordan (NO.: 10/2021/416) and individual consent for this retrospective analysis was waived.

Registration of research studies

•Name of the registry: Clinicaltrials.gov; Research Registry •Unique Identifying number or registration ID: NCT03917992; researchregistry (UIN:7578) •Hyperlink to your specific registration (must be publicly accessible and will be checked): https://clinicaltrials.gov/ct2/show/NCT03917992; https://www.researchregistry.com/register-now#user-researchregistry/registerresearchdetails/61ebc6a40c2646001ef56d26/

Guarantor

Abdallah Al-Ani, Hanna Al-Makhamreh.

Declaration of competing interest

The authors declare no conflict of interest.
  30 in total

1.  2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines and the Heart Rhythm Society.

Authors:  Craig T January; L Samuel Wann; Joseph S Alpert; Hugh Calkins; Joaquin E Cigarroa; Joseph C Cleveland; Jamie B Conti; Patrick T Ellinor; Michael D Ezekowitz; Michael E Field; Katherine T Murray; Ralph L Sacco; William G Stevenson; Patrick J Tchou; Cynthia M Tracy; Clyde W Yancy
Journal:  Circulation       Date:  2014-03-28       Impact factor: 29.690

2.  Relation of hypothyroidism and incident atrial fibrillation (from the Framingham Heart Study).

Authors:  Eun-Jeong Kim; Asya Lyass; Na Wang; Joseph M Massaro; Caroline S Fox; Emelia J Benjamin; Jared W Magnani
Journal:  Am Heart J       Date:  2013-10-19       Impact factor: 4.749

3.  The RecordAF study: design, baseline data, and profile of patients according to chosen treatment strategy for atrial fibrillation.

Authors:  Jean-Yves Le Heuzey; Günter Breithardt; John Camm; Harry Crijns; Paul Dorian; Peter R Kowey; Ihsen Merioua; Eric N Prystowsky; Peter J Schwartz; Christian Torp-Pedersen; William Weintraub
Journal:  Am J Cardiol       Date:  2009-12-07       Impact factor: 2.778

4.  Gulf Survey of Atrial Fibrillation Events (Gulf SAFE): design and baseline characteristics of patients with atrial fibrillation in the Arab Middle East.

Authors:  Mohammad Zubaid; Wafa A Rashed; Alawi A Alsheikh-Ali; Wael Almahmeed; Abdullah Shehab; Kadhim Sulaiman; Ibrahim Al-Zakwani; Ahmed Alqudaimi; Nidal Asaad; Haitham Amin
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2011-07

5.  Prevalence and Predictors of Thyroid Dysfunction Among Type 2 Diabetic Patients: A Case-Control Study.

Authors:  Adi H Khassawneh; Abdel-Hameed Al-Mistarehi; Anas M Zein Alaabdin; Laith Khasawneh; Thekraiat M AlQuran; Khalid A Kheirallah; Nesreen A Saadeh; Othman Beni Yonis; Mohamid Shawkat; Nail Obeidat
Journal:  Int J Gen Med       Date:  2020-10-12

6.  Characteristics and Outcomes of Atrial Fibrillation in Patients With Thyroid Disease (from the ARISTOTLE Trial).

Authors:  Sarah A Goldstein; Jennifer Green; Kurt Huber; Daniel M Wojdyla; Renato D Lopes; John H Alexander; Dragos Vinereanu; Lars Wallentin; Christopher B Granger; Sana M Al-Khatib
Journal:  Am J Cardiol       Date:  2019-08-07       Impact factor: 2.778

7.  Performance of the HEMORR(2)HAGES, ATRIA, and HAS-BLED bleeding risk-prediction scores in patients with atrial fibrillation undergoing anticoagulation: the AMADEUS (evaluating the use of SR34006 compared to warfarin or acenocoumarol in patients with atrial fibrillation) study.

Authors:  Stavros Apostolakis; Deirdre A Lane; Yutao Guo; Harry Buller; Gregory Y H Lip
Journal:  J Am Coll Cardiol       Date:  2012-08-01       Impact factor: 24.094

Review 8.  Atrial fibrillation and hyperthyroidism: A literature review.

Authors:  Vivek Reddy; Wael Taha; Shanker Kundumadam; Mazhar Khan
Journal:  Indian Heart J       Date:  2017-07-05

9.  The spectrum of thyroid disease and risk of new onset atrial fibrillation: a large population cohort study.

Authors:  Christian Selmer; Jonas Bjerring Olesen; Morten Lock Hansen; Jesper Lindhardsen; Anne-Marie Schjerning Olsen; Jesper Clausager Madsen; Jens Faber; Peter Riis Hansen; Ole Dyg Pedersen; Christian Torp-Pedersen; Gunnar Hilmar Gislason
Journal:  BMJ       Date:  2012-11-27

Review 10.  Thyroid disorders and chronic kidney disease.

Authors:  Mohamed Mohamedali; Srikanth Reddy Maddika; Anix Vyas; Viswanathan Iyer; Pramil Cheriyath
Journal:  Int J Nephrol       Date:  2014-04-13
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.