- Academic Editor
†These authors contributed equally.
Background: Women are frequently underrepresented in clinical trials
and databases focusing on ventricular arrhythmias (VAs). However, understanding
sex-based differences in risk factors and the prognosis of VAs is essential for
tailoring personalized prevention and treatment strategies. This study aimed to
investigate sex differences in the epidemiology, risk factors, and prognosis of
VAs in patients with sepsis. Methods: We conducted a comprehensive
analysis of 27,139 sepsis patients (mean [SD] age, 66.6 [16.2] years; 15,626
[57.6%] male), among whom 1136 (4.2%) developed VAs during their
hospitalization. We evaluated VAs incidence and potential risk elements in both
male and female patients, along with in-hospital mortality. Results: Men
had a significantly higher likelihood of developing VAs compared to women (odds
ratio [OR]: 1.70, 95% confidence interval [CI]: 1.50–1.94, p
Infection induced-sepsis is prevalent in Intensive Care Units (ICU) and gives rise to numerous complications. Notably, it significantly impacts the heart. Sepsis-induced cardiac dysfunction extend beyond systolic and diastolic anomalies, encompassing cardiac rhythm disturbances [1]. While prior research has identified sepsis as a predisposing factor for arrhythmias, the emphasis has largely been on atrial arrhythmias [2]. Notably, malignant ventricular arrhythmias (VAs)—encompassing ventricular tachycardia (VT) and ventricular fibrillation (VF)—are of particular concern due to their potential to induce acute heart failure and result in sudden cardiac death (SCD) [3, 4]. Studies indicate that patients with sepsis are vulnerable to suffering from VAs [3]. These irregular heart rhythms can arise from factors such as electrolyte imbalances, reduced afterload, ventricular dysfunction, elevated catecholamines, and chronotropic dysregulation [5, 6].
While the relationship between sepsis and malignant VAs has been well investigated, the impact of sex differences is less explored. Previous studies have underscored sex-specific variations in the epidemiology, underlying mechanisms, clinical presentations, and outcomes of arrhythmias [7, 8, 9]. However, a significant portion of the evidence shaping clinical decisions in the field of cardiology is derived from studies with a conspicuous lack of female representation. Moreover, the sex-specific distribution of diseases, clinical risk elements, and outcomes of VAs in septic patients have been scarcely addressed. Gaining insights into how sex modulates the risk and prognosis of arrhythmias in these patients could lay the groundwork for personalized therapeutic approaches. With this in mind, we aimed to conduct a thorough assessment of sex disparities in the epidemiology, risk factors, and outcomes of VAs in septic patients.
We employed data from a substantial intensive care database, namely the Medical Information Mart for Intensive Care IV (MIMIC-IV, version 2.0). This repository includes data on more than 200,000 patients who were admitted to a variety of ICUs at Beth Israel Deaconess Medical Center (BIDMC) during the period from 2008 to 2019 [10]. It provides details on patient demographics, vital statistics, common health conditions, and lab results. The researcher (LL) has the necessary permissions to retrieve data from this database (record ID: 35965741). Given that our research involved a third-party, anonymized, and publicly accessible database with prior institutional review board (IRB) consent, there was no need for additional IRB approval from our side.
This study encompassed individuals aged 18 and older who were primarily admitted to the hospital for sepsis. Those with missing or incomplete records were not included. For the purposes of our research, sepsis was characterized as organ dysfunction due to infection, defined by a rise in the Sequential Organ Failure Assessment (SOFA) score by at least 2 points [11]. The primary outcome was the incidence of VAs, encompassing both sustained and non-sustained VT, as well as VF, during the hospital stay. Guidelines provide specific details on the criteria for VT/VF [12].
For data retrieval, we utilized PostgreSQL tools (version 13.0, University of California, California, USA), employing unique patient identifiers, or Subject IDs, to accurately identify individual patients. Our focus was on collecting potential VT/VF risk factors for septic patients from their initial hospital visits. Conditions like congestive heart failure (CHF), atrial fibrillation (AF), non-ischemic cardiomyopathy (NICM), old myocardial infarction (OMI), acute myocardial infarction (AMI), and chronic kidney disease (CKD) have been linked with a heightened risk of VAs or SCD [13, 14]. Moreover, elements such as admission type, logistic organ dysfunction system (LODS) rating, length of stay in the ICU (LOS-ICU), occurrence of pneumonia, serum white blood cell (WBC) count, and the administration of specific medications (like macrolides, quinolones, vasoactive substances, or anti-arrhythmic drugs including amiodarone, propafenone, sotalol, and dronedarone)—vital for evaluating and managing sepsis—were factored into our analyses [6, 11]. For instances where multiple LODS score and WBC count records existed, we opted for the earliest entries. The specifics of these parameters are detailed in Supplementary Table 1. Information regarding in-hospital deaths, interpreted as mortality from any cause during hospital or ICU stay, was also sourced from the database.
The Kolmogorov-Smirnov test was utilized to evaluate the normality of continuous
variables. Continuous variables that adhered to a normal distribution were
presented as mean
To discern the relationships between potential risk determinants and VAs in both male and female sepsis patients, sex-segregated multivariable logistic analyses were conducted. Each risk determinant underwent a univariate logistic regression assessment. Furthermore, a comprehensive model encompassing admission type, LOS-ICU, LODS rating, CHF, AF, AMI, OMI, NICM, CKD, pneumonia, vasoactive drugs, antibiotics, and WBC was developed. Sex interactions were incorporated for all variables in every model. Relative risk ratios (RRRs) were calculated for sex-specific OR ratios, and we also computed population-attributable fractions (PAFs) for emerging VAs [16]. Within this research, the PAF represents an estimation of the VAs incidence that might be averted by eradicating the risk determinants. For PAF estimations, continuous data points like LOS-ICU and LODS rating were segmented, using thresholds of 3 and 11, respectively. Purifying the MIMIC-IV database data is pivotal to bolster result accuracy. Illogical or extreme data points were substituted with average figures. Metrics with over 30% omissions were disregarded. For data gaps below 5% of the total count, we applied average value imputation. For data gaps ranging between 5% and 30%, multiple imputations were executed.
Every statistical evaluation was bi-directional, with a p-value less than 0.05 deemed to indicate statistical relevance. The statistical computations were carried out using the R software package (version 4.0.4, R Foundation for Statistical Computing, Vienna, Austria) and Stata (version 15.0, StataCorp, College Station, TX, USA).
This study recruited 27,139 patients diagnosed with sepsis for analysis (mean [SD] age, 66.6 [16.2] years; 15,626 [57.6%] male). The methodology of the study is detailed in Supplementary Fig. 1. We observed that males had a higher prevalence of comorbidities associated with VAs, including CHF, AF, AMI, OMI, NICM, and CKD. Conversely, a larger percentage of females had pneumonia compared to their male counterparts. Furthermore, the use of vasoactive agents and anti-arrhythmic drugs (AAD) was higher in men than in women. Finally, the baseline WBC levels were similar between the two groups (Table 1).
Variables | Total | Women | Men | p value |
(n = 27,139) | (n = 11,513) | (n = 15,626) | ||
Age, years | 66.6 |
68.3 |
65.5 |
|
ER admission, % | 13,060 (48.1) | 5847 (50.8) | 5666 (36.3) | |
LOS-ICU, days | 4.66 |
4.64 |
4.68 |
0.564 |
LODS score | 5.54 |
5.48 |
5.58 |
0.010 |
CHF, % | 9191 (33.9) | 4117 (35.8) | 5074 (32.5) | |
VAs, % | 1136 (4.2) | 348 (3.0) | 788 (5.0) | |
AF, % | 9760 (36.0) | 3974 (34.5) | 5786 (37.0) | |
AMI, % | 2609 (9.6) | 1028 (8.9) | 1581 (10.1) | 0.001 |
OMI, % | 3769 (13.9) | 1323 (11.5) | 2446 (15.7) | |
NICM, % | 1142 (4.2) | 352 (3.1) | 790 (5.1) | |
CKD, % | 7745 (28.5) | 3041 (26.4) | 4704 (30.1) | |
ICD, % | 259 (1.0) | 47 (0.4) | 212 (1.3) | |
Pneumonia, % | 10,206 (37.6) | 4408 (38.3) | 5798 (37.1) | 0.047 |
Antibiotics, % | 21,878 (80.6) | 9301 (80.8) | 12,577 (80.5) | 0.538 |
Vasoactive agents, % | 12,606 (46.4) | 5023 (43.6) | 7583 (48.5) | |
AAD, % | 5052 (18.6) | 1844 (16.0) | 3208 (20.5) | |
WBC, × 10 |
11.0 |
11.1 |
11.1 |
0.710 |
ER, emergency room; LOS-ICU, length of stay in the Intensive Care Units; LODS, logistic organ dysfunction system; CHF, congestive heart failure; VAs, ventricular arrhythmias; AF, atrial fibrillation; AMI, acute myocardial infarction; OMI, old myocardial infarction; NICM, non-ischemic cardiomyopathy; CKD, chronic kidney disease; ICD, implantable cardioverter-defibrillator; AAD, anti-arrhythmia drugs; WBC, white blood cell.
Among patients hospitalized with a simultaneous diagnosis of sepsis, 1136
(4.2%) displayed signs of VAs (VT/VF). A smaller proportion of females exhibited
VAs compared to their male counterparts (3.0% vs. 5.0%, p
The cumulative incidence curve for VAs. Among patients diagnosed with sepsis, VAs were significantly more common in males. Males exhibited an increase in VA incidence after the age of 50, with a similar increase seen in females after the age of 60. VAs, ventricular arrhythmias.
In the initial singular logistic regression assessment, all variables, with the
exception of age, were correlated with VAs. This finding prompted a more detailed
multivariate logistic regression analysis, as detailed in Supplementary
Table 2. Additionally, Supplementary Table 3 presents the unadjusted
odds ratios (ORs) for VAs based on sex, alongside the interaction p
values for all the factors under consideration. We found significant sex
disparities in the relationship between specific risk factors and VA occurrence.
Notably, the interaction p values for pneumonia, CHF, and NICM are all
less than 0.05, indicating significant interactions with sex. Age demonstrates a
differential effect on VAs risk between sexes, with women showing a slightly
diminished risk as they age compared to men. Pneumonia significantly elevates the
risk of VAs in men but not in women. Additionally, both CHF and NICM exhibit
distinct VAs risk associations between men and women. A multivariate model was
created utilizing OR as the effect measure. Table 2 presents the ORs adjusted for
VAs by sex and the associated interaction p-values. We noted a robust
link between CHF and an elevated likelihood of VAs across both sexes, with a
significant sex-based interaction. Within the multivariate framework, factors
like ER admission, LOS-ICU, CKD, and pneumonia did not significantly influence VA
occurrence. Additionally, NICM had a marked correlation with VAs, more so in
males (OR: 4.072, 95% CI: 3.338–4.967, p
Variables | Interaction p value | Sex | Odd ratio | p value | Relative risk ratio |
ER admission | 0.945 | Men | 0.82 (0.71–0.96) | 0.014 | 1.01 (0.77–1.32) |
Women | 0.82 (0.65–1.02) | 0.073 | |||
LOS-ICU | 0.848 | Men | 1.00 (0.99–1.02) | 0.530 | 1.00 (0.98–1.02) |
Women | 1.01 (0.99–1.02) | 0.504 | |||
LODS score | 0.286 | Men | 1.06 (1.03–1.08) | 1.02 (0.98–1.06) | |
Women | 1.03 (1.00–1.07) | 0.032 | |||
CHF | 0.031 | Men | 2.27 (1.90–2.71) | 1.35 (1.03–1.76) | |
Women | 1.68 (1.34–2.13) | ||||
AF | 0.080 | Men | 1.06 (0.91–1.24) | 0.463 | 0.79 (0.60–1.03) |
Women | 1.35 (1.08–1.68) | 0.009 | |||
AMI | 0.931 | Men | 2.95 (2.49–3.51) | 1.01 (0.76–1.36) | |
Women | 2.92 (2.28–3.74) | ||||
OMI | 0.249 | Men | 1.37 (1.15–1.63) | 1.20 (0.88–1.65) | |
Women | 1.13 (0.86–1.50) | 0.375 | |||
NICM | 0.014 | Men | 4.07 (3.34–4.97) | 1.63 (1.10–2.40) | |
Women | 2.50 (1.77–3.54) | ||||
CKD | 0.506 | Men | 0.97 (0.83–1.15) | 0.757 | 1.10 (0.83–1.45) |
Women | 0.89 (0.70–1.12) | 0.315 | |||
Pneumonia | 0.036 | Men | 1.13 (0.97–1.33) | 0.124 | 1.33 (1.02–1.74) |
Women | 0.85 (0.68–1.07) | 0.159 | |||
Vasoactive agents | 0.619 | Men | 1.27 (1.08–1.50) | 0.004 | 1.07 (0.82–1.40) |
Women | 1.19 (0.95–1.49) | 0.137 | |||
Antibiotics | 0.495 | Men | 2.15 (1.62–2.87) | 1.18 (0.73–1.90) | |
Women | 1.83 (1.24–2.69) | 0.002 | |||
WBC | 0.874 | Men | 1.02 (1.00–1.03) | 0.013 | 1.00 (0.98–1.02) |
Women | 1.02 (1.00–1.03) | 0.049 |
ER, emergency room; LOS-ICU, length of stay in the Intensive Care Units; LODS, logistic organ dysfunction system; CHF, congestive heart failure; AF, atrial fibrillation; AMI, acute myocardial infarction; OMI, old myocardial infarction; NICM, non-ischemic cardiomyopathy; CKD, chronic kidney disease; WBC, white blood cell.
Table 3 showcases the PAFs for VAs in inpatient settings, stemming from possible risk determinants. Most risk elements exhibited similar PAFs across both sexes. However, distinctions were observed in a few variables. In particular, the PAF for CHF in males (PAF 16.5%, 95% CI: 12.9–19.7) exceeded that of females (PAF 11.0%, 95% CI: 5.4–15.9). A similar trend was seen in NICM, where men had a PAF of 17.5% (95% CI: 14.4–20.5) compared to women’s 7.4% (95% CI: 3.8–10.8). In contrast, AF showed a higher PAF in women (PAF 15.9%, 95% CI: 6.3–24.5) than in men (PAF 3.0%, 95% CI: –6.7–6.8).
Variables | PAF (95% CI) Men | PAF (95% CI) Women |
ER admission | –7.6 (–13.6–0.1) | –7.4 (–18.1–2.2) |
LOS-ICU |
12.2 (5.1–18.9) | 7.0 (–3.7–16.6) |
LODS |
5.3 (2.5–8.1) | 3.6 (–3.7–4.3) |
CHF | 16.5 (12.9–19.7) | 11.0 (5.4–15.9) |
AF | 3.0 (–6.7–6.8) | 15.9 (6.3–24.5) |
AMI | 9.8 (8.0–11.8) | 10.5 (7.8–31.2) |
OMI | 6.4 (2.0–10.7) | 2.9 (–2.8–8.2) |
NICM | 17.5 (14.4–20.5) | 7.4 (3.8–10.8) |
CKD | –1.6 (–8.1–4.5) | –0.9 (–9.5–7.0) |
Pneumonia | 4.6 (–2.3–10.1) | –5.3 (–15.4–4.0) |
Antibiotics | 5.4 (3.4–6.9) | 5.7 (3.0–7.7) |
Vasoactive agents | 10.4 (2.4–17.7) | 10.2 (–9.7–20.2) |
WBC |
7.7 (9.7–13.8) | 7.1 (–3.7–16.8) |
ER, emergency room; LOS-ICU, length of stay in the Intensive Care Units; LODS, logistic organ dysfunction system; CHF, congestive heart failure; AF, atrial fibrillation; AMI, acute myocardial infarction; OMI, old myocardial infarction; NICM, non-ischemic cardiomyopathy; CKD, chronic kidney disease; WBC, white blood cell.
The age adjusted model (Model 1) identified that VAs almost doubled the
mortality risk during hospitalization for both sexes. After adjusting for risk
factors (Model 2) VAs emerged as independent risk factors for in-hospital death,
regardless of sex. The interplay between in-hospital death and VAs, based on sex,
was not significant in either model, with interaction p values exceeding
0.05 (Fig. 2). Furthermore, we found that the occurrence of VAs during
hospitalization influenced the long-term prognosis of septic patients, leading to
an almost 1.5 times heightened risk of mortality within a year. However, there
was no significant difference between sexes (interaction p values
In-hospital mortality risk models between the sexes. Model 1 includes adjustments for age-adjusted, while Model 2 incorporates adjustments for various factors including admission pattern, LODS score, LOS-ICU, comorbidities such as CHF, AF, AMI NICM, OMI, and CKD. Additionally, it accounts for pneumonia, the use of vasoactive agents and antibiotics, and WBC count. LOS-ICU, length of stay in the Intensive Care Units; LODS, logistic organ dysfunction system; CHF, congestive heart failure; AF, atrial fibrillation; AMI, acute myocardial infarction; OMI, old myocardial infarction; NICM, non-ischemic cardiomyopathy; CKD, chronic kidney disease; WBC, white blood cell.
Mortality risk for VA within one year of treatment, differences between the different sexes. Model 1 includes adjustments for age-adjusted, while Model 2 incorporates adjustments for various factors including admission pattern, LODS score, LOS-ICU, comorbidities such as CHF, AF, AMI NICM, OMI, and CKD. Additionally, it accounts for pneumonia, the use of vasoactive agents and antibiotics, and WBC count. VA, ventricular arrhythmia; LOS-ICU, length of stay in the Intensive Care Units; LODS, logistic organ dysfunction system; CHF, congestive heart failure; AF, atrial fibrillation; AMI, acute myocardial infarction; OMI, old myocardial infarction; NICM, non-ischemic cardiomyopathy; CKD, chronic kidney disease; WBC, white blood cell.
In this large-scale cohort study, we observed sex disparities in VAs incidence and risk factors. With age as the metric, men had a higher VAs risk, particularly in older age groups. The multivariate model showed a stronger link between NICM, CHF, and VAs in men. Furthermore, the occurrence of VAs during hospitalization was associated with a nearly 2-fold increased risk of in-hospital mortality in septic patients, and this risk was consistent across both sexes.
Despite the underrepresentation of female patients in VAs-focused randomized
controlled trials, existing research underscores distinct lifetime risks of VAs
and SCD between the sexes [7]. This underrepresentation in clinical trials may be
linked to the lower incidence of coronary artery disease and the frequency of VAs
in women compared to men [7]. In our study, we found that 4.2% of hospitalized
sepsis patients experienced VAs. Notably, men had a significantly higher
incidence of VAs than women. Furthermore, being male was found to be a strong
predictor of increased VAs risk in sepsis. Additionally, Santangeli et
al. [17] reported that women with heart failure (HF) exhibit a lower rate of
receiving appropriate implantable cardioverter-defibrillator (ICD) shocks in
comparison to men. The underlying mechanisms that lead to VAs in sepsis remain
incompletely understood. Several factors, such as electrolyte disturbance,
inflammation, oxidative stress, cardiomyocyte apoptosis, exotoxins, endotoxins
and ischemic heart disease are believed to play pivotal roles [18, 19, 20, 21]. The sex
disparities observed might be attributed to the effects of sex hormones on
Ca
Our findings reveal that for sepsis patients, the cumulative incidence of VAs remains particularly low up until the age of 50. After this age, there’s a marked increase in incidence for men, whereas for women, this increase is observed after 60 years. Interestingly, we observed a decade-long delay in the onset of VAs for women compared to men, a pattern consistent with prior studies [14]. This decade-long difference in VAs onset between sexes might be attributed to protective hormonal factors in women that diminish post-menopause. As patients approach the age of 95, the incidence rates for both sexes tend to stabilize. Previous studies have established that increasing age is a potent predictor for the onset of VAs, a relationship that was also evident in our current research [5, 24]. Furthermore, the role of CHF as a risk factor for VAs has been previously established, which aligns with our study results [14, 25]. Notably, we observed that CHF has a more pronounced impact on men than on women. Potential mechanisms underlying the occurrence of VAs in CHF patients encompass structural and mechanical alterations in the ventricles, ventricular metabolic abnormalities, electrophysiological changes, neurohormonal imbalances, and the use of vasoactive agents [26, 27]. Moreover, the relationship between CHF and VAs is bidirectional, potentially creating a vicious cycle that exacerbates CHF progression and further heightens susceptibility to VAs [28]. Future prospective studies should further validate these sex differences and elucidate their underlying mechanisms. Risk factors such as NICM, which includes hypertrophic cardiomyopathy (HCM) and NICM, play a crucial role in evaluating patient susceptibility to for VAs and SCD [29, 30]. Our study clearly showcased sex disparities. However, contrasting findings were reported in the Multicenter Automatic Defibrillator Implantation Trial With Cardiac Resynchronization Therapy (MADIT-CRT) [31]. The authors indicated that there was no statistically significant difference in the incidence of VAs and SCD between males and females within NICM (p = 0.063) [31]. Interestingly, the cumulative incidence of VAs was lower in females compared to males, a pattern consistent with our study [31]. It’s noteworthy to mention that in this research, female participants constituted only 35% of the total cohort. It’s important to highlight that other investigations into sex differences in VAs incidence are constrained by a limited number of female participants.
Additionally, among sepsis patients who developed VAs, the impact of AF might be more pronounced in females compared to males. There is growing evidence suggesting a mechanistic connection between AF and ventricular tachyarrhythmias [7, 32]. This connection may be attributed to reduced ventricular refractoriness and the occurrence of pro-arrhythmic short-long-short sequences preceding the onset of ventricular tachyarrhythmias in the presence of AF, compared to when the heart is in sinus rhythm [32]. The sex disparity might be related to the fact that female patients often do not receive timely treatment for AF [7]. Furthermore, while our study identified sex differences in the impact of pneumonia on the occurrence of VAs, pneumonia does not appear to be a critical influencing factor for VAs development. A prior study regarding COVID-19 indicated that cardiac arrest and arrhythmias might result from systemic illness rather than being solely a direct consequence of COVID-19 infection [33]. The influence of LOS-ICU and CKD on VAs risk seems limited. For these factors, our study did not observe a significant sex effect on the occurrence of VAs during hospitalization in sepsis patients. However, our study did not incorporate CKD staging, creatinine clearance, or renal replacement therapy in the analysis, so the impact of CKD on VAs should be interpreted with caution.
At present, there remains a debate regarding sex differences in the mortality rate associated with VAs [34]. Our study indicates that the occurrence of VAs in sepsis is correlated with an elevated in-hospital mortality rate and a heightened one-year mortality rate, yet no significant sex disparity was observed. Variations in cardiac regulation, cellular electrophysiology, and the influence of sex hormones might explain the sex-based differences in arrhythmia [7, 34]. Our study unveils the intricate interplay of various risk factors in determining the likelihood of VAs occurrence in sepsis patients. The observed sex disparities in VAs incidence and associated risks underscore the importance of adopting a sex-specific approach in clinical assessments and interventions. Future research should place greater emphasis on potential sex differences within certain cardiovascular diseases.
Our investigation delineates the nuanced interplay between sepsis and VAs, underscoring salient sex-based disparities in both incidence and predisposing factors. Our data reveals an augmented predisposition to VAs in male patients, with determinants such as CHF and NICM exerting a more pronounced influence in this demographic. The etiological underpinnings of these observations are intricate, spanning cellular electrophysiology, cardiac autoregulation, and the modulatory effects of sex hormones. These insights advocate for a sex-centric paradigm in clinical evaluations and therapeutic interventions. Emphasizing this, it becomes crucial to advocate for sophisticated, sex-tailored therapeutic strategies in addressing these challenges.
While this cohort study benefits from a substantial population size, several limitations warrant mention. First, the study’s retrospective design necessitates the need for future prospective investigations. Second, the absence of baseline electrocardiograms in this cohort may have resulted in an underestimation of VA incidence. Third, the data in this article originates from a substantial intensive care medicine cohort, which may limit the generalizability of our findings to other patient populations. Additionally, we did not account for iatrogenic VAs in our analysis despite their relatively frequent occurrence in ICU settings. Given the limitations of our data source, we are unable to account for iatrogenic VAs in our analysis. Studying iatrogenic VAs and their relationship with sex among ICU patients is indeed a valuable topic that merits further research. Lastly, the method used for imputing missing may have influenced our results. In light of these limitations, the conclusions drawn from this study should be approached with prudence.
The datasets analyzed during the current study are available from the corresponding author on reasonable request.
Study conception and design: LL, YY and XP. Acquisition of data: LL and XP. Analysis and interpretation of data: LKZ, YLX, ZHZ, ZXZ and ZH. Writing, review, and/or revision of the manuscript: LL, YY, ZXZ, LKZ, ZHZ, YLX, ZH and XP. Study supervision: YY. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.
Given that our research involved a third party, anonymized, and publicly accessible database with prior institutional review board (IRB) consent, there was no need for additional IRB approval from our side and no additional patient’s informed consent is required.
Not applicable.
This research was funded by Medical and Health Technology Innovation Project of Chinese Academy of Medical Sciences, grant number 2021-CXGC09-1.
The authors declare no conflict of interest.
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