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Association between blood test indicators and atrial fibrillation in elderly patients aged 65 and above in the Central Jiangsu region: a cross-sectional study

BMC Cardiovascular Disorders volume 25, Article number: 51 (2025) Cite this article

Abstract

Objectives

The aim of this study was to explore the correlation between blood test indicators and Atrial Fibrillation (AF) in Individuals Aged 65 and Older in Yangzhou, Jiangsu.

Methods

From January 1, 2019, to August 31, 2023, an epidemiological cross-sectional survey was conducted among the elderly population undergoing health check-ups at Northern Jiangsu People’s Hospital in Jiangsu Province. Patients diagnosed with AF after a 12-lead electrocardiogram were included in the case group, and non-AF individuals matched by age and gender in a 1:4 frequency ratio were included in the control group. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to select important variables from routine blood tests and biochemical indicators and their derived indicators (such as TyG, TyG-BMI, TG/HDL-c, RAR, NLR, MHR). Based on the selected variables, participants were divided into four groups (Q1 ~ Q4), and multifactorial Logistic regression analysis, restricted cubic spline regression, gender subgroup analysis and Receiver Operating Characteristic (ROC) curve were used to explore the relationship between the relevant variables and AF.

Results

A total of 5,879 elderly individuals over the age of 65 were included in the study, with a prevalence of AF of 2.96% (174/5,879). The prevalence of AF in the overall population, as well as in male and female populations, showed a continuous increasing trend with age (P for trend < 0.001). A total of 696 individuals without AF after matching served as the control group, and LASSO regression identified albumin, direct bilirubin, and uric acid as three significant indicators. After adjusting for relevant confounding factors, lower levels of albumin, and higher levels of direct bilirubin and uric acid were significantly associated with the occurrence of AF (P < 0.05). Gender subgroup analysis revealed that in the elderly female population, albumin was not significantly associated with AF (P > 0.05), while direct bilirubin and uric acid were significantly associated with AF (P < 0.05). In the male population, albumin, direct bilirubin, and uric acid were significantly associated with AF (P < 0.05). Restricted cubic spline regression analysis showed a significant nonlinear relationship between direct bilirubin and AF (P for nonlinear < 0.001). The ROC curve analysis indicates that albumin, direct bilirubin, and uric acid all have good association strength with AF in elderly patients, with direct bilirubin showing the strongest association effect (AUC (95% CI) = 0.728 (0.686, 0.769)).

Conclusions

Low levels of albumin, high levels of direct bilirubin, and uric acid are all significantly associated with AF in the elderly population of the Central Jiangsu region. The conclusions of this study need further validation with a larger sample size.

Peer Review reports

Introduction

Atrial fibrillation (AF) is the most common type of arrhythmia in clinic, affecting 33 million people worldwide, with an all-cause mortality rate of 63.3 per 1,000 person-years [1]. The prevalence and mortality rates both increase with age, reaching a peak between the ages of 90 and 94, after which they decline [2]. In the 2019 Global Burden of Disease Study data, the incidence rate of AF in males was 61.2 per 100,000 (95% uncertainty interval 47.3–77.6), while in females it was 60.8 per 100,000 (95% uncertainty interval 46.6–77.1) [3]. Both European and American guidelines [4] and the consensus of Chinese experts [5] recommend screening for AF in high-risk populations aged 65 and above using electrocardiograms (Class I recommendation). Most research on AF is based on related risk factor studies of hospitalized cases, while epidemiological studies on AF screening and risk factor analysis in elderly health check populations are relatively scarce. This study aims to collect current cases of AF in elderly individuals aged 65 and above at the Physical Examination Center of Northern Jiangsu People’s Hospital to understand the current prevalence of AF in the elderly population of Yangzhou city, which will provide basic data for arrhythmia disease surveillance and other epidemiological studies. Additionally, through a case-control study, we aim to explore the potential associated factors of AF in the elderly individuals, in order to provide a scientific basis for the prevention and treatment measures and effective evaluation of AF.

Materials and methods

Study population

Participants were selected from community elderly individuals aged 65 and above at the Physical Examination Center of Northern Jiangsu People’s Hospital in Jiangsu Province, who underwent health checks from January 1, 2019 to August 31, 2023 and were screened for AF using electrocardiograms. All participants signed an informed consent form. Inclusion criteria were as follows: (1) aged 65 and above; (2) with health examination data and results from a 12-lead electrocardiogram examination. Exclusion criteria: (1) history of cancer; (2) history of heart surgery, structural heart disease, valvular disease, or heart failure; (3) liver or kidney dysfunction; (4) pregnant women; (5) other arrhythmias (non-AF). In the case-control study of AF, individuals diagnosed with AF were considered as the case group, and 696 individuals with sinus rhythm, frequency-matched by age (± 5 years) and gender, were included as the control group.

Diagnostic criteria

The standard for AF follows the current widely recognized diagnostic method [6], which is characterized by the disappearance of P waves on a 12-lead electrocardiogram, replaced by irregular atrial fibrillation waves with a frequency of 350 to 600 beats per minute; the RR intervals are absolutely irregular, and the QRS wave morphology is mostly normal. Paroxysmal AF was considered to be AF terminated spontaneously or with intervention within 7 days of initiation. Permanent AF was defined as AF for which sinus rhythm could not be restored or maintained.

Data collection

Basic clinical data of the examines were collected through the electronic medical record system, including demographic information (such as age, gender), relevant medical histories (hypertension, diabetes, cancer, etc.), and family history. Health check-ups were conducted to obtain physical examinations, laboratory tests, basic conditions of participants (height, weight, etc.), laboratory biochemical indicators (complete blood count, urine routine, liver and kidney function, blood sugar, blood lipids, etc.) and the results of 12-lead electrocardiogram.

The body mass index (BMI) was calculated as weight (kg)/height(m)^2, the triglyceride glucose index (TyG) was calculated as ln [100 × triglycerides (mg/l) × fasting blood glucose (mg/l) /2], the triglyceride glucose body mass index (TyG-BMI) was calculated as TyG index × BMI, the ratio of triglycerides to high-density lipoprotein cholesterol (TG/HDL-c) was calculated as TG (mg/dl) / HDL-c (mg/dl), the red cell distribution width to albumin ratio (RAR) was calculated as RDW (%) / albumin (g/l), the neutrophil to lymphocyte ratio (NLR) was calculated as the neutrophil count (×10^9)/lymphocyte count (×10^9), and the monocyte to high-density lipoprotein cholesterol ratio was calculated as the monocyte count (×10^9) / HDL-c (mg/dl).

Electrocardiogram collection

The subjects lay in a supine position for the collection of a complete 10-second resting electrocardiogram using a standard 12-lead ECG machine.

Quality control

Epidemiological surveys, all physical examinations, laboratory tests, imaging studies and electrocardiograms were performed by well-trained clinical physicians; all electrocardiogram reports were read, analyzed, and diagnosed by two experienced cardiovascular experts simultaneously.

Statistical analysis

Data analysis and plotting were conducted using SPSS 27.0 software and R-4.4.1. Quantitative data that conform to a normal distribution are expressed as x ± s, and if they are skewed, they are represented as M(P25∼P75). Qualitative data are described using frequency. For the comparison of count data between two groups, chi-square tests are used, and trend chi-square tests are applied to analyze multiple categorical variable groups. Independent sample t-tests or Wilcoxon rank-sum tests are used for group comparisons. Descriptive statistics were employed to analyze the prevalence characteristics of AF in different genders and age groups among the elderly participants. All variables, including blood test indicators and biochemical indicators and their derived indicators (such as TyG, TyG-BMI, TG/HDL-c, RAR, NLR, MHR), were included in the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, with AF as the outcome variable. The regularized parameter λ corresponding to one standard deviation of the minimum mean squared error (Mean-Squared-Error) was selected through cross-validation to identify non-zero coefficient indicators, thereby screening out features significantly associated with elderly AF. Subsequently, after considering potential confounding factors such as hypertension, diabetes, fatty liver, and gallstones, each feature variable was divided into quartiles, namely Q1, Q2, Q3, and Q4, and multifactorial Logistic regression analysis was used to explore the association between these variables and elderly AF, and to determine whether the relevant trends would be affected by confounding factors. Then, these feature variables were included in the analysis as continuous variables, to assess their specific impact on the incidence of elderly AF for each single unit change. In addition, gender stratified analysis was conducted to identify the specific effects of each feature variable in different gender populations.

To help clinicians more accurately assess the impact of the continuous changes in these feature indicators on elderly AF patients, restricted cubic spline(RCS) analysis was added to the study. The RCS curve fits the entire curve by using cubic functions to reveal the potential non-linear relationships between these indicators and elderly AF patients. Finally, by constructing the receiver operating characteristic (ROC) curve, the study compared the association between different feature indicators and elderly AF.

Results

Comparison of AF prevalence across different ages and genders

Flow chart of the research process is shown in Fig. 1. The overall prevalence of AF in the elderly population aged 65 and above is 2.96% (174/5879), with the participating population comprising 3,808 males (64.77%) and 2,071 females (35.23%). The prevalence of AF in elderly males was higher than in elderly females (129/3,808 [3.39%] vs. 45/2,071 [2.17%], X²=6.892, P = 0.009). To assess the potential association between AF prevalence and age, participants were divided into four groups: 2,643 participants (1,640 males/1,003 females) aged 65–70; 1,353 participants (885 males/468 females) aged 70–75; 949 participants (625 males/324 females) aged 75–80; and 934 participants (658 males/276 females) aged over 80. The prevalence of AF in each age group was 27 (1.02%), 43 (3.18%), 46 (4.85%), and 58 (6.21%), respectively, with significant differences in AF prevalence among the four age groups (X²=80.916, P < 0.001) (Fig. 2).

Fig. 1
figure 1

Flow chart of the research process

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Fig. 2
figure 2

Comparison of atrial fibrillation prevalence across different ages and genders. *P < 0.001 male versus female

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The prevalence of AF in males across the age groups was 22 (1.34%), 34 (3.84%), 34 (5.44%), and 39 (5.93%), respectively, with significant differences in AF prevalence among the four age groups (X²=42.546, P < 0.001). The prevalence of AF in females across the age groups was 5(0.50%), 9(1.92%), 12(3.70%), and 19 (6.88%), respectively, with significant differences in AF prevalence among the four age groups (X²=47.932, P < 0.001). The prevalence of AF in the overall population and in both male and female subgroups increased with age. Additionally, in the 65–70 and 70–75 age groups, the incidence of hyperuricemia in males was significantly higher than in females (P < 0.05), while over 75 years old, there was no statistically significant difference in the prevalence rates between the two genders (P > 0.05).

Baseline characteristics of AF group and non-AF group

This study collected datas from 5,879 individuals over the age of 65, with 174 individuals diagnosed with AF. The 174 AF patients were included in the case group, and 696 individuals were included in the control group. The average age of both the case and control groups was 77.30 ± 5.97 years, with 45 females (25.9%) in the case group and 180 females (25.9%) in the control group. Significant statistical differences were observed between the case and control groups in terms of BMI, hypertension, diabetes, non-alcoholic fatty liver disease, gallstones, TyG-BMI index, TG/HDL-c index, hemoglobin, hematocrit, red cell distribution width, albumin, total bilirubin, direct bilirubin, indirect bilirubin, gamma-glutamyl transpeptidase, blood sugar, uric acid, triglycerides, low-density lipoprotein cholesterol, MHR index, RAR index, monocyte count, and platelet count(all P < 0.05) (Table 1).

Table 1 Comparison of general data between atrial fibrillation group and non-atrial fibrillation group
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LASSO regression selection

Using LASSO regression to select variables from 28 routine blood tests and biochemical indicators, including BMI, triglycerides, and blood sugar, the results showed that Lambda.min (λ = 0.002) and Lambda.1se (λ = 0.046) corresponded to two vertical lines, respectively (Fig. 3b). At Lambda.min, 22 predictive variables were selected, and at Lambda.1se, 3 predictive variables were selected. The three predictive variables selected at Lambda.1se were albumin, direct bilirubin, and uric acid (Fig. 3a).

Fig. 3
figure 3

(a) LASSO regression model coefficient shrinkage path diagram. (b) LASSO regression cross-validation diagram

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The relationship between atrial fibrillation and correlated variables in the elderly under different models

In elderly participants, we found that lower levels of albumin, higher levels of direct bilirubin, and uric acid were significantly associated with AF (P < 0.05). In the fully adjusted model (Model 2), we observed a negative correlation between albumin and AF (OR (95% CI) = 0.844 (0.783, 0.908)), indicating that for each unit increase in albumin, the prevalence of AF decreased by 15.6%. Direct bilirubin showed a positive correlation with AF (OR (95% CI) = 1.576 (1.431, 1.745)), suggesting that for each unit increase in direct bilirubin, the prevalence of AF increased by 57.6%. Uric acid also demonstrated a positive correlation with AF (OR (95% CI) = 1.003 (1.002, 1.004)), indicating that for each unit increase in uric acid, the prevalence of AF increased by 0.3%.

To better understand the potential associations between these three indicators and AF, we transformed them from continuous variables to categorical variables (quartiles). In Model 1, albumin [Q2, 0.574 (0.365, 0.896); Q3, 0.634 (0.406, 0.983); Q4, 0.361 (0.214, 0.591)] may be negatively associated with AF in the elderly population; direct bilirubin [Q2, 2.092 (1.104, 4.118); Q3, 4.122 (2.280, 7.860); Q4, 8.899 (5.055, 16.656)], and uric acid [Q3, 1.843 (1.143, 3.011); Q4, 2.091 (1.307, 3.393)] were significantly associated with AF in the elderly population. In Model 2, after adjusting for body mass index (BMI), hypertension, diabetes, fatty liver, gallstones, red blood cells, white blood cells, lymphocytes, and low-density lipoprotein cholesterol, albumin [Q4, 0.326 (0.182, 0.571)] may be negatively associated with AF in the elderly population; direct bilirubin [Q2, 2.189 (1.123, 4.426); Q3, 4.172 (2.062, 7.904); Q4, 9.074 (4.809, 18.102)], and uric acid [Q3, 1.961 (1.184, 3.288); Q4, 2.202 (1.319, 3.727)] were significantly positively associated with AF in the elderly population (Table 2).

Table 2 The relationship between atrial fibrillation and different characteristic variables in the elderly under different models
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Gender stratified analysis

In elderly participants of different genders, after adjusting for BMI, hypertension, diabetes, fatty liver, gallstones, red blood cells, white blood cells, lymphocytes, and low-density lipoprotein cholesterol, we found that albumin, direct bilirubin, and uric acid had statistically significant associations with AF (P < 0.05). For males, albumin [Q3, 0.488 (0.268, 0.873); Q4, 0.216 (0.105, 0.424)]. The continuous variable showed that albumin was significantly negatively associated with AF in elderly males (OR = 0.831, 95% CI (0.760–0.905), P < 0.05), but not statistically significant in females (P > 0.05). For direct bilirubin, in males [Q3, 3.838 (1.727, 9.507); Q4, 8.067 (3.659, 19.965)], and in females [Q2, 8.13 (2.789, 26.401); Q3, 7.192 (2.287, 24.634); Q4, 24.519 (7.337, 51.253)]. The continuous variable confirmed that direct bilirubin was significantly positively associated AF in elderly males (OR = 1.501, 95% CI (1.338, 1.692), P < 0.05) and elderly females (OR = 2.006, 95% CI (1.559, 2.667), P < 0.05). For uric acid, in males [Q3, 2.685 (1.408, 5.322); Q4, 2.385 (1.237, 4.775)], and in females [Q4, 7.077 (2.391, 21.944)]. The continuous variable confirmed that uric acid was significantly positively associated with AF in elderly males (OR = 1.005, 95% CI (1.002, 1.008), P < 0.05) and elderly females (OR = 1.006, 95% CI (1.002, 1.012), P < 0.05) (Table 3).

Table 3 Gender stratified analysis
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Analysis of the restricted cubic splines

After adjusting for BMI, hypertension, diabetes, fatty liver, gallstones, red blood cells, white blood cells, lymphocytes, and low-density lipoprotein cholesterol, RCS were used to assess the potential non-linear relationships between albumin (Fig. 4a), direct bilirubin (Fig. 4b) and uric acid (Fig. 4c) with atrial fibrillation in the elderly. The study found a significant non-linear relationship between direct bilirubin and atrial fibrillation (P for nonlinear < 0.05). In contrast, no statistically significant non-linear relationships were observed between albumin, uric acid, and atrial fibrillation (P for nonlinear > 0.05).

Fig. 4
figure 4

Restricted cubic spline (RCS) curve for (a) ALB - Albumin (g/l) (b) DBIL - Direct Bilirubin (µmol/l) and (c) UA - Uric Acid (µmol/l) in relation to atrial fibrillation in the elderly population

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The ROC analysis results

The ROC analysis results for ALB (albumin), DBIL (direct bilirubin), and UA (uric acid) indicated that the association strength of ALB with AF in the elderly is moderate (AUC = 0.591, 95% CI = 0.544–0.637), with a cutoff value of 43.15. The association strength of DBIL is accurate (AUC = 0.728, 95% CI = 0.686–0.769), with a cutoff value of 5.05. The association strength of UA is moderate (AUC = 0.626, 95% CI = 0.583–0.669), with a cutoff value of 355.52(Fig. 5).

Fig. 5
figure 5

Receiver Operating Characteristic (ROC) Curve

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Discussion

AF has a high rate of disability and mortality, and it negatively impacts the quality of life for patients [7, 8]. This study surveyed a physical examination population over 65 years old in the central region of Jiangsu, China, and included 174 cases of AF in the case group, with a detection rate of 2.96%. In this retrospective case-control study, we analyzed associated factors of AF in the elderly population, in order to provide a scientific basis for the prevention and treatment measures and effective evaluation of AF.

Albumin is a primary protein with various biochemical properties present in human plasma. Hypoalbuminemia, commonly defined as ALB < 35 g/L, is considered as a useful marker of cardiovascular diseases [9]. After adjusting for confounding factors such as hypertension, diabetes, and fatty liver in our study, multivariate logistic regression indicates that low levels of albumin are significantly negatively associated with AF in the elderly. This is consistent with many previous studies; a large-scale prospective epidemiological and Mendelian randomization study showed that ALB levels are nearly linearly negatively correlated with the risk of AF [10]. A dose-response meta-analysis found a significant negative linear association between serum ALB and the risk of AF, with a 36% reduction in the risk of AF for every 10 g/L increase in serum albumin levels [11]. Furthermore, several studies have suggested that the relationship between albumin and AF may vary by gender. The Copenhagen City Heart Study based on 8,870 individuals, found that lower ALB levels are independently associated with the occurrence of AF in women, but not in men [12]. However, a single-center study of China in 2022 found an independent negative correlation between male ALB levels and AF [13], which is in consistent with our study.

Several mechanisms may explain the relationship between albumin levels and AF in the elderly. Inflammation and oxidative stress are considered as two major mediators of atrial remodeling, including electrical and structural remodeling of AF [14, 15]. ALB has been shown to have anti-inflammatory activity [16]. A study based on 4,434 patients reported that serum ALB levels are negatively correlated with CRP levels (r = -0.311) and white blood cell levels (r = -0.157) [17]. Atherosclerosis can alter the structure and function of gap junction proteins, increasing the return of electrical signals and the excitability of atrial tissue, further promoting the occurrence and development of AF. Albumin can selectively intervene in this process, reducing the adhesion between monocytes and endothelial cells, thereby alleviating the inflammatory response [18]. Previous studies have shown that ALB is rich in thiol groups, accounting for about 80% of the total thiols in plasma for clearing reactive oxygen and nitrogen species, and can carry NO, thus possessing strong antioxidant stress activity [19], which can prevent the increase in sarcoplasmic reticulum Ca2+ leading to a shortening of atrial action potential duration and delayed after-depolarization [20].

Bilirubin is a bile pigment and a well-known metabolite of heme catabolism. Bilirubin has antioxidant and anti-inflammatory effects and has been proven to be negatively correlated with the risk of cardiovascular diseases (such as coronary artery disease, stroke) [21]. However, the relationship between AF and bilirubin levels remains controversial. Demir et al. reported a negative correlation between serum bilirubin levels and non-valvular AF [22]. However, a cross-sectional study including 90,143 healthy physical individuals found that the AF group showed significantly higher total bilirubin levels than the non-AF group. A study of 437 patients with thyroid toxicity undergoing radioactive iodine treatment showed that the AF group had higher bilirubin levels than the non-AF group [23]. A study of 212 patients with paroxysmal AF after catheter ablation showed that high bilirubin levels were associated with the recurrence of AF [24]. Our results are consistent with most of the research findings in recent years. We found that the levels of direct bilirubin, indirect bilirubin, and total bilirubin in the AF group were significantly higher than those in the control group. Direct bilirubin has a high association strength with the occurrence and development of AF in the elderly.

A Mendelian Randomization (MR) analysis including 8,977 Korean residents found that the genetically predicted bilirubin levels may have a non-causal relationship with AF [25]. AF can induce venous congestion, and the elevated central venous pressure leading to congestive liver disease, which may result in a mild increase in bilirubin [26]. This reverse causality might explain the observed association between bilirubin levels and AF. Uric acid is a heterocyclic organic compound, the end product of human purine metabolism, which acts as an antioxidant at normal concentrations but exerts pro-oxidant effects at high concentrations [27]. Clinical studies have commonly found that high SUA (serum uric acid) levels are associated with the risk of AF occurrence [28, 29]. A community-based study of elderly populations found that elderly individuals with high UA have a higher risk of developing AF [30]. Our study further analyzed the relationship between uric acid and elderly AF patients stratified by gender and found a significant positive correlation between uric acid and elderly AF, with no gender differences. Oxidative stress and inflammation are the most likely factors of the development of AF [31].

High concentrations of uric acid can activate xanthine oxidase, increasing superoxide and its reactive metabolites, which may lead to thrombus formation, inflammation, and tissue remodeling in the heart [32]. At the same time, hyperuricemia can induce inflammation in various cell types by regulating inflammatory signaling pathways such as the NLRP3 inflammasome, macrophage M1/M2 polarization, and hs-CRP [33, 34]. Therefore, hyperuricemia plays an important role in the pathological progression of AF and is worth targeted prevention in the elderly population. However, there is currently a lack of large-scale cohort studies or randomized controlled trials reporting changes in the prevalence of AF after the treatment of hyperuricemia.

This study has several limitations. Firstly, this cross-sectional study can only reflect the associations between factors and atrial fibrillation (AF), which may indicate potential risk factors that require further investigation through longitudinal studies.Second, AF is often asymptomatic and may be intermittent, so the widely used electrocardiogram cannot detect all paroxysmal AF. Third, our study can only describe the epidemiological distribution of the elderly population in the central region of Jiangsu, China. Fourth, since our study is based on the blood routine indicators and biochemical indicators of the physical examination population, it lacks information of participants’ medication history, lifestyle habits, occupation, smoking and drinking history. Multicenter and longitudinal studies are needed to verify whether different regions have related results.

In summary, our study indicates that levels of albumin, direct bilirubin, and uric acid are significant associated factors for AF in the elderly population over 65 years old in the Central Jiangsu region, with albumin showing significant statistical significance only in males, while the association of direct bilirubin and uric acid with atrial fibrillation does not differ between genders.

Data availability

No datasets were generated or analysed during the current study.

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Acknowledgements

We thank the medical staff at the Northern Jiangsu People’s Hospital for support in this study.

Funding

This work was supported by The National Natural Science Foundation of China (81800250), China Postdoctoral Science Foundation (2022M711417), Jiangsu Province Traditional Chinese Medicine Project (MS2023137), Yangzhou Science and Technology Plan Social Development Project (YZ2023096), Clinical Trials from the Northern Jiangsu People’s Hospital(SBLC23002).

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Author notes

  1. Hao Liang and Shuai Zhang contributed equally to this work and share first authorship.

Authors and Affiliations

  1. Department of Cardiology, Northern Jiangsu People’s Hospital Affiliated to Yangzhou University, Yangzhou, 225001, China

    Hao Liang

  2. Department of Gastroenterology, Northern Jiangsu People’s Hospital Affiliated to Yangzhou University, Yangzhou, 225001, China

    Shuai Zhang

  3. Department of Cardiology, Northern Jiangsu People’s Hospital, Nantong West Road No. 98, Yangzhou, Jiangsu, 225001, China

    Ye Zhu

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  1. Hao Liang
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Contributions

YZ designed and wrote the article; H L and S Z collected the clinical data. All authors contributed to the article and approved the submitted version.

Corresponding author

Correspondence to Ye Zhu.

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Ethics and clinical trial statement

The portions of this study involving human participants, human materials, or human data were conducted in accordance with the Declaration of Helsinki .The study has been approved by the Ethics Committee of Northern Jiangsu People Hospital (Approval Number: 2024ky284). Clinical trial number: not applicable.

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The authors declare no competing interests.

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Liang, H., Zhang, S. & Zhu, Y. Association between blood test indicators and atrial fibrillation in elderly patients aged 65 and above in the Central Jiangsu region: a cross-sectional study. BMC Cardiovasc Disord 25, 51 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12872-025-04508-y

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Keywords

BMC Cardiovascular Disorders

ISSN: 1471-2261

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