Abstract
Abstract
Objective
Collect the characteristics of patients’ baseline data, and explore the predictive factors of late recurrence of atrial fibrillation (AF) after catheter ablation according to whether late recurrence or not. The purpose of this study was to determine the significance of the APPLE score in conjunction with the monocyte–high-density lipoprotein cholesterol ratio (MHR) in predicting the late recurrence of AF after catheter ablation in patients with AF.
Methods
Baseline data were collected to explore the predictors of late recurrence after AF catheter ablation. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to compare the predictive value of MHR, the APPLE score and their combined variables in the late recurrence of AF after catheter ablation.
Results
This is a retrospective study. A total of 438 patients were followed-up, including 303 cases of paroxysmal AF, 135 cases of persistent AF (28 cases of long-term persistent AF) and 115 cases of late recurrence. The Cox multivariate regression analysis revealed that MHR, the APPLE score and early recurrence were independent predictors of the late recurrence of AF. The AUC of the combined variables for predicting late recurrence after catheter ablation in patients with AF was higher than that of MHR and the APPLE score (p<0.05). The ROC AUC of the combined variables in predicting the late recurrence of AF after catheter ablation was 0.733 (p<0.001, 95% CI: 0.660 to 0.806), and the best cut-off point was 0.2711 (sensitivity: 69.20%, specificity: 68.00%).
Conclusions
Early recurrence, MHR and the APPLE score are independent risk factors for the late recurrence of AF after catheter ablation. The combination of the APPLE score with MHR improved the value of predicting the late recurrence of AF after catheter ablation. The combined variables were a predictor of an increased late recurrence rate after catheter ablation for AF when the value was greater than 0.2711.
Keywords: cardiology, adult cardiology, pacing & electrophysiology
Strengths and limitations of this study.
A large sample size with diverse atrial fibrillation types enhances study reliability.
Use of receiver operating characteristic curve analysis for predictive value comparison.
Lack of external validation in different patient populations.
Potential bias in patient selection and follow-up duration.
Introduction
Atrial fibrillation (AF) is the most prevalent tachyarrhythmia in the general population. The prevalence and incidence of AF increase with age1 2 and are associated with stroke,3 dementia4 and heart failure.5 Patients with AF face significant impairments in their quality of life, and the condition has emerged as a leading cause of cardiovascular-related mortality. Catheter ablation is currently an essential approach for treating AF that does not respond to medication treatment. Catheter ablation has been shown to be effective for AF, however a substantial recurrence rate remains, especially in persistent AF.
Left atrial diameter (LAD) size, duration of AF, patient age and renal insufficiency are all known risk factors for the late recurrence of AF. An analysis of the available risk prediction models for AF after catheter ablation revealed promising results.6 7 The APPLE8 (age-persistent AF-impaired estimated glomerular filtration rate-LAD left ventricular ejection fraction (LVEF)) scoring system comprises five factors: age >65 years, persistent AF, impaired estimated glomerular filtration rate <60 mL/min/1.73 m2, LAD≥43 mm and LVEF<50%. Each variable is assigned one point on a scale of 0–5. In 2015, Kornej et al8 included 1145 patients undergoing radiofrequency (RF) ablation for AF and analysed their predictive value, and the APPLE score in the results showed moderate predictive value (receiver operating characteristic curve (ROC)=0.643, 95% CI: 0.600 to 0.668, p<0.001). In response, the predictive value of the APPLE score was verified in 261 patients included, and APPLE still showed moderate predictive value (ROC=0.624, 95% CI: 0.562 to 0.687, p<0.001). Preliminary results indicate that the APPLE score has moderate predictive value and consistency. When compared with other methods, the parameters of the APPLE scoring system are more transparent and straightforward.
Many cardiovascular diseases, including AF, are linked to the monocyte–high-density lipoprotein (HDL) cholesterol ratio (MHR) because it serves as a quantitative inflammatory marker that can indicate the progression of inflammation and oxidative stress.9 10 The occurrence and progression of AF are linked to both MHR and the APPLE score. In this study, we examined the hypothesis that incorporating the APPLE score with MHR can enhance the predictive value for the late recurrence of AF following catheter ablation.
Materials and methods
Study population
We enrolled a total of 438 patients (268 male patients and 170 female patients) with symptomatic AF who underwent initial catheter ablation between October 2019 and May 2021 and who were regularly followed-up, in this study. There were 303 cases of paroxysmal AF and 135 cases of persistent AF (including 28 cases of long-term persistent AF).
The inclusion criteria were (1) patients with non-valvular AF who met the 2020 European Society of Cardiology diagnostic criteria for AF,11 who did not respond to antiarrhythmic drugs and who received transcatheter ablation for the first time; (2) patients who consented to ablation treatment and preoperatively signed a consent form; (3) patients who were aged ≥18 years; (4) patients who had preoperative transesophageal echocardiography or left atrial CT angiography, or thrombosis in the left atrium and/or left atrial appendage were excluded; and (5) patients who were regularly followed-up after ablation.
Patient and public involvement
None.
Radiofrequency catheter ablation procedure
Under local anaesthetic, two surgeons isolated the pulmonary veins of the patients. The following instruments were used: a three-dimensional electro-anatomical mapping system (CARTO, Biosense Webster, USA), a contact-force-guided radiofrequency ablation catheter (ThermoCool SmartTouch, Biosense Webster) with an electrode spacing of 1–6–2 mm, a variable circular mapping catheter (CMC) decapolar CMC with an electrode spacing of 8 mm (Lasso 2515, Biosense Webster), and an electrophysiology catheter with an electrode spacing of 2–8–2 mm (Webster, Biosense Webster).
After inserting the duodecapolar catheter into the coronary sinus (CS) via a puncture of the right femoral vein, we performed a transseptal puncture with an 8.5 mm French sheath (Swart SL0, St. Jude Medical, Minnetonka, Minnesota, USA) and a 50° transseptal needle (HeartSpan, Biosense Webster). The use of fluoroscopy was stopped after the ablation catheter was placed in the left atrium. Using the CMC, a three-dimensional model of the left atrium was recreated.
The CMC was used to locate the pulmonary vein potential prior to ablation. Point-by-point pulmonary vein isolation was carried out to anatomically enclose the pulmonary veins, with an inter-lesion distance of less than 4 mm (the diameter of the lesion tag was 4 mm with a contiguous tag) and an ablation index of 450–500 on the anterior wall (35 W) and 350–400 on the posterior wall (30 W). Ablation using a VisiTag module (CARTO, Biosense Webster, USA) was performed on all enrolled patients. Other ablation lines (tricuspid isthmus, mitral isthmus, left atrial roof, left atrial bottom, left anterior atrial wall, CS, etc) were determined intraoperatively in patients with persistent AF. Radiofrequency ablation was successful if it blocked electrical conduction between the pulmonary vein and the atrium, shortened the S1S1 atrial burst from 300 to 180 ms, or prevented rapid atrial arrhythmia (atrial tachycardia, atrial flutter and AF) in response to 2:1 conduction stimulation in the atrium for more than 30 s. If sinus rhythm was not recovered following ablation for persistent AF, synchronised electrical cardioversion at 100–150 J was administered.
Cryoballoon ablation procedure
Pulmonary vein isolation was performed on patients under local anaesthesia. A 28 mm cryoballoon catheter (Arctic Front Advance, Medtronic, USA), a 20 mm decapolar CMC (Achieve, Medtronic, USA), an electrophysiology catheter with an electrode spacing of 2–8–2 mm (Webster, Biosense Webster), and an electrophysiology catheter with an electrode spacing of 10 mm (Avail, Biosense Webster) were used.
After the left femoral vein was punctured and the electrophysiology catheter was placed in the CS and superior vena cava, the transseptal puncture was performed using an 8.5 mm French sheath (Swart SL0, St. Jude Medical) and a 50° transseptal needle (HeartSpan, Biosense Webster) through the right femoral vein.
The potential was recorded using the Achieve catheter inserted into the pulmonary vein, and the cryoballoon catheter was positioned in the vestibule of the pulmonary vein. Angiography was used to confirm the pulmonary vein was completely blocked, and then cryoablation was performed. The freezing time was 180~240 s, the temperature was −40°C~−50°C and the electrical isolation of the pulmonary vein was confirmed. The phrenic nerve was paced during the cryoablation of the right pulmonary vein, and once the diaphragmatic muscle movement was weakened or had disappeared, cryoablation was stopped immediately until normal diaphragm muscle movement had returned. For persistent AF, if the sinus rhythm was not restored after ablation, synchronised electrical cardioversion at 100–150 J was performed.
Follow-up
To prevent excessive blood clotting, all patients were given oral anticoagulant medication for at least 3 months following surgery. Except in cases where arrhythmia persisted, antiarrhythmic medications were not given routinely after an ablation and were completely stopped within 3 months. A regular schedule of outpatient clinical visits or phone calls ensured that the enrolled patients were constantly monitored. Patients were informed when the above symptoms occurred, and they were checked by ECG or telemetry ECG monitoring. At 3, 6 and 12 months post-ablation, patients were followed with 72-hour telemetry ECG monitoring in the outpatient department of our hospital to detect a recurrence of AF. Three months before and 3 months after the surgery, data on the status and any recurrences were documented. Early recurrence of AF was defined as atrial tachycardia, atrial flutter and AF lasting more than 30 s were recorded by ECG or Holter ECG in patients with AF within 3 months after transcatheter ablation. Late recurrence of AF was defined as atrial tachycardia, atrial flutter and AF confirmed by ECG or Holter after 3 months after transcatheter ablation in patients with AF and without taking antiarrhythmic drugs for longer than 30 s.
Endpoints
The endpoint of the follow-up was to assess the predictive value of MHR, the APPLE score and their combined variables in the late recurrence of AF after catheter ablation. This involved identifying patients with late recurrence of AF, which is defined as any rapid atrial arrhythmia (including AF, atrial flutter or atrial tachycardia) on ECG or Holter monitoring after 3 months post-surgery, lasting more than 30 s.
Statistical methods
We used SPSS V.26.0 (SPSS, an IBM Company, Chicago, USA) statistical software for the statistical analysis, and GraphPad Prism V.8.0 to plot the graphs. Count data are expressed as frequency (percentage), and a χ2 test was used to compare significant differences. Measurement data were tested for normality using the Kolmogorov-Smirnov method, and distributed measurement data are expressed as mean±SD (×±s). Comparisons between two groups of data were performed using independent-samples t-tests. Non-normally distributed measurement data are expressed as medians (25th–75th quantile), and data between the two groups were compared using a Mann-Whitney U test. The correlation between variables was analysed by a Cox multiple regression analysis. The ROC curve was created using SPSS V.26.0, and the area under the curve (AUC) was calculated and compared with evaluate the predictive value of MHR, the APPLE score and their combined variables for late recurrence after catheter ablation. Youden’s Index was used to calculate the optimal cut-off value; patients with AF were divided into a higher group and a lower group according to the best cut-off-point value of the two combined variables obtained in the previous step, and a Kaplan-Meier analysis (log-rank test) was performed to compare the recurrence rates of the two groups. After propensity score matching, the ROC curve was drawn to predict the late recurrence of AF after catheter ablation for further performance analysis. A value of p<0.05 indicated a statistically significant difference.
Results
Baseline characteristics
A total of 438 patients with AF were included in this study. As per the basic information of the patients shown in online supplemental table 1, there were a total of 268 male patients (61.19%) and 170 female patients (38.81%), with a mean age of 62 (54–66) years, with an average body mass index of 24.41 (22.49–26.78) kg/m² and an average AF course of 24 (6–48) months. There were 135 cases (30.82%) of persistent AF, 147 cases (33.56%) of cryoballoon ablation, 188 cases (42.92%) of hypertension, 65 cases (14.84%) of diabetes mellitus, 45 cases (10.27%) of coronary heart disease, 12 cases (2.73%) of hypertrophic cardiomyopathy and 10 cases (2.28%) with a history of hyperthyroidism. The APPLE score was 1 (0–2), and the CHA2DS2-VASc score was 2 (1–3). The follow-up time was 11 (8–17) months. Among the patients, 91 (20.78%) developed early recurrence after surgery, and 115 (26.26%) developed late recurrence (see online supplemental table 1).
Univariate analysis
The patients were divided into a recurrence group and a non-recurrence group based on the late recurrence of AF after catheter ablation. The values for early recurrence, MHR, APPLE score, LAD, history of hyperthyroidism, duration of AF and age in the recurrence group were higher than those in the non-recurrence group and the high-density lipoprotein cholesterol (HLD-L) value was lower in the recurrence group than in the non-recurrence group, and the difference was statistically significant (p<0.05) (online supplemental table 1).
Multifactor analysis
The significant factors in the univariate analysis (p<0.05) were as follows: age, early recurrence of AF, HLD-L, MHR, APPLE score, LAD, previous history of hyperthyroidism and AF. They were subjected to a Cox multiple regression analysis, and the results indicated that early recurrence (HR: 3.424, p<0.001, 95% CI: 2.356 to 4.976), MHR (HR: 1.061, p=0.034, 95% CI: 1.005 to 1.121) and APPLE score (HR 1.566, p<0.001, 95% CI: 1.237 to 1.982) were independent risk factors for the late recurrence of AF (online supplemental table 2). This suggested that the combined variable with AF who had an elevated APPLE score and MHR before catheter ablation were more likely to experience a late recurrence of AF compared with a combined variable with lower APPLE scores and MHR (online supplemental table 2).
Combined variables of MHR and APPLE score
Logistic regression analysis (online supplemental table 3) revealed the combined variable score of MHR and APPLE=0.126 MHR + 0.619 APPLE − 2.828, forming a new variable.
Predicting recurrence of AF using MHR, APPLE score and their combined variables
The AUC of the MHR for predicting the late recurrence of AF after catheter ablation was 0.643 (p<0.001, 95% CI: 0.584 to 0.701) (figure 1A). In the subgroup analysis, the AUC of the MHR for predicting the late recurrence of AF after radiofrequency ablation (RFCA) and cryoballoon ablation (CBA) was 0.643 (p<0.001, 95% CI: 0.571 to 0.714) (figure 1B) and 0.642 (p=0.008, 95% CI: 0.539 to 0.746), respectively (figure 1C); the difference between the subgroups was not statistically significant (p=0.996). The AUC of the APPLE score for predicting the late recurrence of AF after catheter ablation was 0.653 (p<0.001, 95% CI: 0.595 to 0.711) (figure 2A). The subgroup analysis showed that the AUC of the APPLE score for predicting the late recurrence of AF after RFCA and CBA was 0.680 (p<0.001, 95% CI: 0.612 to 0.749) (figure 2B) and 0.609 (p=0.04, 95% CI: 0.502 to 0.716), respectively (figure 2C); the difference between the subgroups was not statistically significant (p=0.273). The AUC of the combined variable for predicting the late recurrence of AF after catheter ablation was 0.702 (p<0.001, 95% CI: 0.650 to 0.755) (figure 3A). In the subgroup analysis, the AUC of the combined variables for predicting the late recurrence of AF after RFCA and CBA was 0.711 (p<0.001, 95% CI: 0.648 to 0.774) (figure 3B) and 0.684 (p<0.001, 95% CI: 0.588 to 0.780) (figure 3C), respectively, and the difference was not statistically significant (p=0.647). The best cut-off value of the combined variables calculated using the Youden’s Index for predicting late recurrence after catheter ablation was 0.2445, with a sensitivity of 68.70% and a specificity of 63.20%.
Figure 1. Receiver operating characteristic curve of monocyte–high-density lipoprotein cholesterol ratio for predicting late recurrence after different surgical procedures; (A) catheter ablation, (B) radiofrequency ablation, (C) cryoballoon ablation. AUC, area under the curve.
Figure 2. Receiver operating characteristic curve of APPLE score for predicting late recurrence after different surgical procedures; (A) catheter ablation, (B) radiofrequency ablation, (C) cryoballoon ablation. AUC, area under the curve.
Figure 3. Receiver operating characteristic curve of combined variables for predicting late recurrence after different surgical procedures; (A) catheter ablation, (B) radiofrequency ablation, (C) cryoballoon ablation. AUC, area under the curve.
Comparison of ROC curves of MHR, the APPLE score and their combined variables
The area under the ROC curve of the combination of the APPLE score with MHR in predicting late recurrence after the catheter ablation of AF was larger than that of the MHR and the APPLE score, and the difference was statistically significant (p<0.05). However, the difference between the MHR and APPLE score was not statistically significant (online supplemental table 4).
Propensity score matching
According to the best cut-off value calculated from the results of the previous step, the combined variable was divided into a higher group (n=198 cases, combined variable ≥0.2445) and a lower group (n=240 cases, combined variable <0.2445). The comparison of clinical data between the two groups revealed significant differences in the following factors (p<0.2), which included: sex, smoking, alcohol consumption, hypertension, coronary disease, white blood cell count, neutrophil count, lymphocyte count, eosinophile count, basophilic granulocyte count, platelet count, total cholesterol, low-density lipoprotein cholesterol, N-terminal pro-B-type natriuretic peptide (NT-proBNP), amiodarone treatment, propafenone, betaprolol. Propensity score matching was performed for factors with significant differences (p<0.2) between the higher group (≥0.2445) and the lower group (<0.2445). After matching, there were 109 cases in each of the two groups, and there was no significant difference in clinical variables between the groups (p>0.05) (online supplemental table 5). A Kaplan-Meier analysis (log-rank test) was performed on the late recurrence rate of AF in the group with a higher joint variable value (≥0.2445) and the group with a lower joint variable value (<0.2445). There was a significant difference in the late recurrence rate of AF (figure 4).
Figure 4. Kaplan-Meier curve of recurrence rate between higher and lower combined.
We further explored the effect of the value of the combined variables of the two on the late recurrence of AF, and the combined variable value and follow-up time were included in a univariate binomial Cox regression analysis. The results are shown in online supplemental table 6. The group with a higher combined variable value was a risk factor for the late recurrence of AF (p<0.001, HR=64.561, 95% CI: 16.07 to 259.38), indicating that patients with AF with values higher than the two combined variables had a 64.561-fold higher risk of late recurrence after ablation than those with lower values of the two combined variables. The corresponding ROC curve was drawn, and the ROC AUC of the combined variables for predicting the late recurrence after AF ablation was 0.733 (p<0.001, 95% CI: 0.660 to 0.806). Taking the maximum value of Youden’s Index, the optimal cut-off point was 0.2711 (sensitivity: 69.20%, specificity: 68.00%) (figure 5).
Figure 5. Receiver operating characteristic curve of combined variables for predicting late recurrence after catheter ablation.
Discussion
Numerous studies have examined the factors that can be used to predict whether or not AF will recur after surgery. Many cardiovascular disorders, including AF, are linked to MHR because they can represent the progression of inflammation and oxidative stress to some extent.9 In this study, we aimed to investigate the risk factors for and predictors of recurrence after AF ablation and to examine whether the combination of MHR and the APPLE score can increase the predictive power of the latter due to the APPLE score’s moderate predictive value.
APPLE score
One of the most influential risk factors for developing AF is a person’s age. The incidence of AF increases with age, from 2% in the general population to 10–12% in those aged 80 and up.12 Increased LAD is not only closely related to the recurrence of AF but also affects the occurrence and development of AF. The development of AF is sometimes aided by atrial structural remodelling and electrophysiological alterations, both of which are commonly brought on by an enlarged LAD or left atrial volume. Not only is there no natural way of stopping persistent AF, but it can also lead to LAD enlargement.13 Since these two factors work in tandem, it should come as no surprise that LAD and AF type (persistent AF) are both substantially linked with AF recurrence. The results of a study showed that a 1 mm increase in LAD was associated with a 1.18-fold increase in the risk of developing AF, and LAD was an independent risk factor for developing AF.14 As previously shown by Chao et al,15 even a little decline in glomerular filtration rate (GFR) is linked to arrhythmogenic left atrial remodelling, which, in turn, leads to low left atrial voltage and, potentially, an increased risk of developing AF when GFR continues to decline. In another study,16 patients with end-stage renal disease who are on long-term haemodialysis had a high prevalence of AF. Heart failure often coexists with AF. A recent study included a total of 363 patients with grade II, III or IV heart failure and AF.17 It was found that catheter ablation could not only improve cardiac function, increase LVEF and eliminate symptoms but could reverse or slow the progression of heart failure. We obtained comparable results in our study.
monocyte-HDL cholesterol ratio
Chronic inflammation and cardiovascular disease are both influenced by monocyte activation, and monocytes and their differentiated macrophages have the ability to control inflammatory cytokines and tissue remodelling.18 Fontes et al reported that leucocyte activation, especially monocyte activation, can occur in patients with postoperative AF.19 HDL cholesterol has been demonstrated to have antioxidant, anti-inflammatory and antithrombotic effects on the cardiovascular system, making it an attractive target for the treatment of dyslipidaemia, a well-known risk factor for cardiovascular disease.20 21 Okin et al analysed 8267 patients with hypertension without a history of AF22; after 4.7±1.10 years of follow-up, 645 patients (7.8%) developed AF, which was comparable to the highest quartile of HDL levels. The patients with the lowest quartile of HDL levels (≤1.2 mmol/L) had a 53% higher risk of new-onset AF compared with those in the highest quartile of HLD levels (>1.78 mmol/L), and the results showed that lower HDL levels on treatment were associated with new-onset of AF. We found that MHR was an independent risk factor of postoperative recurrence in patients with AF after ablation, although monocytes and HDL cholesterol were not. Catheter ablation in patients with AF who had a high MHR before surgery was associated with an HR of 1.061 for late recurrence compared with those who had a low MHR before surgery (p<0.05). Chen et al included 125 patients with AF (with a mean follow-up time of 25.1±12.0 months) and found that compared with the low-MHR group, the incidence of late AF recurrence was significantly increased in the high-MHR group (22.0% vs 57.1%, p<0.05).23 Canpolat et al confirmed that MHR was a strong independent predictor of AF recurrence in patients with successful cryoablation24; using a cut-off value of 11.48, the preoperative MHR ratio predicted the late recurrence of AF during follow-up with a sensitivity of 85% and a specificity of 74%. Similar results were obtained in our study.
APPLE score combined with MHR
Some researchers combined blood biomarkers to improve the APPLE score25; a total of 214 patients were included, and the levels of N-terminal pro-A-type natriuretic peptide (NT-proANP) (p<0.001) and NT-proBNP (p=0.016) were found to increase with the APPLE score. However, when these two markers were included in the APPLE score, the ability of the APPLE score to predict the late recurrence of AF did not improve. This is probably because NT-proANP and NT-proBNP reflect myocardial stretch (ie, atrial-ventricular dilation), which is consistent with the association of some parameters already in the APPLE score (especially persistent AF and LAD), suggesting that NT-proANP and NT-proBNP have limited ability to enhance the APPLE score.
When compared with the parameters currently included in the APPLE score, the introduction of MHR as an indication of inflammation and antioxidant activity represents a significant departure from the prior literature. Patients with AF were classified in this study based on the recurrence of AF in the post-catheter ablation follow-up period. The ROC curve revealed that the combination of the APPLE score with MHR was a powerful predictor of late AF recurrence.
Limitations
This study has the following limitations: (1) The research was a single-centre retrospective study with a small sample size, so it requires further verification by a multicentre, large-sample prospective cohort study. (2) Patients were followed up by telephone to determine the postoperative recurrence of AF (symptoms of palpitations, chest tightness and shortness of breath, which were assessed by 72-hour Holter monitoring, echocardiography and random ECGs). Among which, asymptomatic AF is easily overlooked, resulting in a postoperative recurrence rate that may not be consistent with the actual situation. Therefore, the postoperative recurrence rate may not match the actual situation. (3) This study only measured MHR once before ablation and did not consider its trend in the follow-ups, which may have affected its predictive value for late recurrence after AF ablation.
Conclusion
The following conclusions can be drawn: (1) Early recurrence, MHR and APPLE scores are independent risk factors for predicting late recurrence after the catheter ablation of AF. (2) MHR, APPLE scores and their combined variables have predictive value for different ablation methods (RFCA and CBA). (3) The AUC of the combination of the APPLE score with MHR in predicting late recurrence after the catheter ablation of AF was better than that of MHR and the APPLE score alone. Therefore, the prediction efficiency of the APPLE score can be improved by combining it with MHR. (4) A value of ≥0.2711 for the combined variable of the APPLE score with MHR is a predictor of late recurrence of AF after catheter ablation. Improving surgical success rates and guiding clinical practice requires a better understanding of how to prevent AF after catheter ablation when the combined variable is high (≥0.2711).
supplementary material
Acknowledgements
We would like to acknowledge the hard and dedicated work of all the staff who implemented the intervention and evaluation components of the study.
Footnotes
Funding: The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Prepub: Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online (https://doi.org/10.1136/bmjopen-2023-081808).
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient consent for publication: Not applicable.
Ethics approval: This study was conducted with approval from the Ethics Committee of Fujian Medical University Union Hospital (2022KY152). This study was conducted in accordance with the declaration of Helsinki. Written informed consent was obtained from all participants.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Contributor Information
Wei Song, Email: songwwei@21cn.com.
Yi Chen, Email: cheyyiii@21cn.com.
Xue-Hai Chen, Email: chenxuehaicxh9@21cn.com.
Jian-Hua Chen, Email: chenjianhuacjh9@21cn.com.
Zhe Xu, Email: xuzhexz9a@21cn.com.
Ke-Zeng Gong, Email: gongkezenggkz8@21cn.com.
Wei-Wei Wang, Email: wangweiwei01ka@21cn.com.
Fei-Long Zhang, Email: cardizhang@163.com.
Data availability statement
Data are available upon reasonable request.
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