Effect of cardiovascular risk factors on overall survival in postoperative patients with esophageal squamous cell carcinoma: a retrospective cohort analysis

Introduction

Esophageal cancer (EC) is the seventh leading cause of cancer-related mortality globally, posing a significant health burden. Epidemiological studies have shown a marked gender disparity in its incidence, with males accounting for approximately 70% of cases and an incidence rate 2.5 times higher than that of females. Additionally, the risk of developing EC increases markedly with age (1). In China, esophageal squamous cell carcinoma (ESCC) constitutes over 90% of EC cases, with smoking and alcohol consumption being well-recognized major risk factors (2,3).

Surgical resection remains the primary treatment strategy for most patients with EC. For patients with stage II–III ESCC, a multimodal treatment approach involving postoperative chemoradiotherapy is commonly adopted, with further adjustments made according to individual circumstances. However, existing therapeutic modalities have limitations. Chemotherapeutic agents, such as fluorouracil, platinum compounds, carboplatin, and paclitaxel, are frequently associated with cardiotoxicity. Moreover, radiotherapy, a crucial component of treatment, may also induce cardiac toxicity (4). Collectively, these factors contribute to a significant increase in the incidence of cardiovascular disease (CVD) among cancer patients (5), highlighting an increasingly critical issue in the management of EC patients.

The burden of CVD is equally severe in China. The “China Cardiovascular Health and Disease Report 2022” indicates that approximately 330 million individuals are affected by CVD, and by 2020, CVD had become the leading cause of death among urban and rural residents (6). Global assessments of the impact of cardiovascular risk factors (CVRFs) have shown that diabetes, dyslipidemia, hypertension, obesity, and smoking together account for 50% of the global CVD burden (7). Notably, cancer and CVD share numerous CVRFs, including smoking, obesity, and hypertension. Among these, obesity, hyperglycemia, and other factors are modifiable CVRFs, while age and gender are non-modifiable (8). Previous studies have demonstrated that these overlapping risk factors may exacerbate cancer prognosis (9,10). However, a significant research gap exists: CVD studies often exclude patients with malignancies, while cancer studies frequently omit individuals with CVRFs.

Therefore, this retrospective cohort study focuses on Chinese patients with ESCC to investigate the association between modifiable CVRFs and long-term overall survival (OS) after surgery, providing evidence for the integration of cardiovascular and oncological prognostic management. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1216/rc).

Methods

Study population

This retrospective cohort study was conducted using data from patients with ESCC who were treated at Fujian Provincial Hospital Affiliated to Fuzhou University between June 2015 and December 2018 (Figure 1).

Figure 1 Study flow chart. CVRF, cardiovascular risk factor; ESCC, esophageal squamous cell carcinoma.

Patients were included if they met the criteria, including (I) aged >18 years; (II) pathologically confirmed as stage II–III ESCC after surgery; (III) underwent first-time radical resection; and (IV) patients with available follow-up data to reach the 60-month endpoint or until all-cause mortality occurs. Individuals were excluded if they had conditions, including (I) a history of acute infection within 1 week before treatment; (II) a past history of other malignancies or concurrent malignancies; (III) autoimmune diseases or disorders related to the bone marrow and hematopoietic system; (IV) use of glucocorticoids or blood transfusion within 1 week before treatment; (V) advanced liver cirrhosis or stage 5 chronic kidney disease; and (VI) incomplete clinical data.

This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. It was approved by the Ethics and Research Committee of the Fujian Provincial Hospital Affiliated to Fuzhou University (approval No. K2021-10-007). Given the retrospective nature of the study, individual informed consent for this analysis was waived by the above-mentioned ethics committee.

Data collection

Data were retrieved from medical records, including physical examination findings, CVRFs, and laboratory results (e.g., blood tests, complete blood count, lipid profiles, liver function, and renal function). Physical examinations included measurements of height, weight, systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate. The body mass index (BMI) was calculated as weight (kg) divided by the square of height (m²). Mean arterial blood pressure (MABP) was computed using the formula 33% × SBP + 66% × DBP. Pulse pressure (PP) was derived by subtracting DBP from SBP.

Modifiable CVRFs

Modifiable CVRFs in this study included hypertension, diabetes, dyslipidemia, elevated BMI, and smoking. Definitions are as follows. Hypertension was defined as self-reported hypertension, blood pressure >140/90 mmHg, or a history of antihypertensive medication use. Diabetes was identified by self-reported diabetes or hypoglycemic drug use. Dyslipidemia was defined as triglyceride (TG) levels >1.7 mmol/L, total cholesterol (TC) >5.2 mmol/L, low-density lipoprotein cholesterol (LDL-C) >3.4 mmol/L, high-density lipoprotein cholesterol (HDL-C) <1.0 mmol/L, or use of lipid-lowering agents. Elevated BMI was classified as BMI ≥25.0 kg/m². Smoking was defined as smoking >1 cigarette per day for ≥6 months (current smokers or those who quit within the past 3 months).

The Heart Failure Association of the European Society of Cardiology-International Cardio-Oncology Society specifies in its baseline cardiovascular risk assessment that patients with cancer aged over 65 years who have more than 2 CVRFs should be classified as a high-risk group for cancer therapy-related cardiovascular toxicity (11). Given that the study population consisted of patients aged ≥58 years, the patients were ultimately divided into two groups in this study: the low-CVRF group (with ≤2 CVRFs) and the high-CVRF group (with ≥3 CVRFs).

Oncological data

ESCC was pathologically confirmed postoperatively and staged using the tumor-node-metastasis (TNM) system. Radiotherapy was defined as radiation administered preoperatively or postoperatively; chemotherapy was defined as cytotoxic agents given preoperatively or postoperatively.

Study endpoint

The primary endpoint for patients with EC was 60-month postoperative all-cause mortality. Follow-up for these patients started on the first day after surgery and continued until the occurrence of the primary endpoint (all-cause mortality) or the completion of 60 months of follow-up.

Statistical analysis

Continuous variables were described as follows. Normally distributed data were presented as mean ± standard deviation and compared via unpaired Student’s t-test; non-normally distributed data were described as median (interquartile range) and compared using the Wilcoxon rank-sum test. Categorical variables were presented as counts and percentages (n, %), compared via the Chi-squared test.

Survival analysis was performed using Kaplan-Meier (K-M) curves to visualize survival outcomes, with intergroup differences in survival rates compared via the log-rank test. The variance inflation factor (VIF) was used to assess collinearity between model variables, and least absolute shrinkage and selection operator (LASSO) regression was applied to screen key prognosis-related variables, based on which Cox regression analysis was further conducted to assess independent prognostic factors.

To evaluate associations between modifiable CVRFs and OS, two Cox regression models were constructed, including Model 1, which was unadjusted for confounders, and Model 2, which was adjusted for a comprehensive set of covariates. The covariates included modifiable CVRFs (diabetes, elevated BMI, hypertension, dyslipidemia, smoking status), non-modifiable CVRFs (gender, age ≥65 years), tumor-related variables (TNM stage, chemotherapy, radiotherapy) and laboratory indices [white blood cell (WBC) count, hemoglobin (HB), platelet (PLT) count, albumin (ALB), alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatinine (CR), blood urea nitrogen (BUN), and uric acid (UA)]. These models addressed three key aspects, including: (I) impact of individual modifiable CVRFs (e.g., diabetes, hypertension) on OS; (II) association between CVRF burden (high vs. low CVRF count) and OS; and (III) prognostic effect of diabetes, hypertension, and high CVRF burden on OS in subgroups receiving chemotherapy or radiotherapy. Sensitivity analysis was performed. First, stratified analyses were conducted by age (<65 vs. ≥65 years), gender, TNM stage (stage II vs. stage III), and among all patients (with patients who died within 90 days after surgery excluded) to analyze the association between high-CVRFs and OS. Statistical significance was set at (P<0.05). All analyses were performed using R software version 4.4.0, and IBM SPSS Statistics 25.0 (IBM Corp., Armonk, NY, USA).

Results

Baseline characteristics

Initially, 664 patients with stage II–III ESCC confirmed by postoperative pathological examination at Fujian Provincial Hospital from 2015 to 2018 were screened. A total of 167 patients were excluded during the screening process, with the following exclusion reasons: 72 patients did not meet the inclusion criteria, 16 had missing laboratory data, 19 were excluded for other reasons, and 60 had incomplete data on CVRFs. Ultimately, we investigated the remaining 497 patients (Figure 1). The median age of the included patients was 63 years (mean ± standard deviation: 63.1±8.5 years). Among these patients, 382 (76.9%) were male, 275 (55.3%) were at TNM stage III, 243 (48.9%) received chemotherapy, and 159 (32.0%) received radiotherapy (Table 1).

In the study population, the distribution of modifiable CVRFs was as follows: 154 patients (31.0%) had hypertension, 75 (15.1%) had diabetes, 327 (65.8%) had dyslipidemia, 83 (16.7%) had high BMI, and 204 (41.0%) had a smoking history. Patients in the high-CVRFs group had significantly higher BMI, SBP, DBP, and MABP compared with those in the low-CVRFs group (all P<0.001). There were no significant differences between the two groups regarding TNM stage, proportion of patients receiving radiotherapy or chemotherapy, routine blood test indicators [WBC, neutrophil (N), lymphocyte (L), and PLT count], lipid profiles (TG, TC, HDL-C, and LDL-C), liver function indicators (ALB, AST, and ALT), renal function indicators (CR and BUN), and coagulation function indicators [fibrinogen (FIB) and D-dimer (D-D)] (all P>0.05). Regarding survival outcomes, the high-CVRFs group had a higher all-cause mortality rate (58.0% vs. 45.6%, P=0.03) and a shorter median survival time (50.00 vs. 60.00 months, P=0.007) compared with the low-CVRFs group (Table 1).

Relationship between modifiable CVRFs and OS

K-M survival curves showed that the cumulative survival rate in the high-CVRFs group was significantly lower compared with that in the low-CVRFs group (log-rank test; P=0.009; Figure 2A). VIF analysis revealed a certain degree of collinearity between AST and ALT, while the VIF values of all other variables were <2, indicating no severe collinearity (Table S1). After excluding AST and ALT, LASSO regression was used to screen key variables among clinical prognostic factors. The results showed that high-CVRFs, age ≥65 years, and BUN were positively associated with poor prognosis, while chemotherapy, radiotherapy, and ALB were negatively associated with poor prognosis (the coefficient for PLT count was 0; Table S2, Figure S1). Therefore, the PLT variable was excluded from the subsequent Cox regression analysis models. Consequently, 12 variables were included in the subsequent models: gender, age ≥65 years, chemotherapy, radiotherapy, TNM stage, WBC, HB, ALB, BUN, CR, and UA. In addition, subgroup analyses were conducted to verify the sensitivity of the results. Subgroup analysis based on the multivariate analysis showed that the hazard ratio (HR) for the association between high-CVRFs and all-cause mortality was consistently greater than 1 (Table S3).

Figure 2 Comparison of the survival curves of the low-CVRFs group and high-CVRFs group in the (A) entire population, (B) chemotherapy subgroup, (C) non-chemotherapy subgroup, (D) radiotherapy subgroup, and (E) non-radiotherapy subgroup. CI, confidence interval; CVRF, cardiovascular risk factor; HR, hazard ratio.

In the univariate Cox regression analysis, high-CVRFs [HR =1.48; 95% confidence interval (CI): 1.10–1.99; P=0.01], diabetes (HR =2.03; 95% CI: 1.49–2.76; P<0.001), and hypertension (HR =1.38; 95% CI: 1.06–1.80; P=0.02) were all associated with OS deterioration. After adjusting for confounding factors, the high-CVRFs group still had a significantly increased worse OS risk (HR =1.54; 95% CI: 1.14–2.08; P=0.005); additionally, for each 1-unit increase in the number of CVRFs, the OS risk increased by 15% (HR =1.15; 95% CI: 1.02–1.31; P=0.02). Meanwhile, diabetes remained an independent risk factor for OS deterioration (HR =1.96; 95% CI: 1.41–2.72; P<0.001) (Tables 2,3).

To exclude the potential impact of early postoperative deaths (which may be caused by surgical complications rather than CVRFs or tumor-related factors) on the association between high-CVRFs and OS, an additional sensitivity analysis was conducted in this study by excluding patients who died within 90 days after surgery. The results (Table S4) showed that in the univariate Cox regression model, high CVRFs were still significantly associated with an increased risk of all-cause mortality during the period from 90 days to 60 months after surgery (HR =1.45; 95% CI: 1.07–1.98; P=0.02). After adjusting for confounding factors, compared with patients in the low-CVRFs group, patients in the high-CVRFs group had a 1.50-fold higher risk of all-cause mortality (HR =1.50; 95% CI: 1.10–2.06; P=0.01). This result further confirms the robustness of the association between high CVRF burden and poor OS in patients with stage II–III ESCC after surgery.

Impact of CVRFs in chemotherapy and radiotherapy subgroups

K-M curves (Figure 2) showed the following subgroup-specific results in the order of chemotherapy, non-chemotherapy, radiotherapy, and non-radiotherapy: Specifically, in the chemotherapy subgroup (Figure 2B), the cumulative survival rate of the high-CVRFs group was significantly lower than that of the low-CVRFs group (P<0.001); in contrast, no significant difference in cumulative survival rate was observed between the high- and low-CVRFs groups in the non-chemotherapy subgroup (Figure 2C). Similarly, in the radiotherapy subgroup (Figure 2D), the high-CVRFs group had a significantly lower cumulative survival rate compared with the low-CVRFs group (P<0.001), while no significant difference was found in the non-radiotherapy subgroup (Figure 2E).

After adjusting for confounding factors, high-CVRFs were associated with a 2.62-fold increase in OS risk in the chemotherapy subgroup (HR =2.62; 95% CI: 1.71–4.01; P<0.001) and a 2.01-fold increase in OS risk in the radiotherapy subgroup (HR =2.01; 95% CI: 1.19–3.40; P=0.009). When the number of CVRFs was treated as a continuous variable, a significant trend of increased OS risk was observed in the chemotherapy subgroup (HR =1.32; 95% CI: 1.09–1.58; P=0.004), and a similar (though not statistically significant) trend was noted in the radiotherapy subgroup (HR =1.23; 95% CI: 0.98–1.53; P=0.08) (Table 4).

Prognostic role of diabetes in subgroups

After adjusting for confounding factors, diabetes was significantly associated with increased OS risk in the chemotherapy subgroup (HR =3.72; 95% CI: 2.24–6.18; P<0.001) and the radiotherapy subgroup (HR =3.08; 95% CI: 1.65–5.75; P<0.001). In the non-radiotherapy subgroup, diabetes was associated with OS risk but the association was not statistically significant; no significant association was observed between diabetes and OS in the non-chemotherapy subgroup (non-radiotherapy: HR =1.61, 95% CI: 1.06–2.42, P=0.02; non-chemotherapy: HR =1.11, 95% CI: 0.68–1.80, P=0.68) (Table 5).

Discussion

This study is the first to systematically analyze the association between CVRFs and OS in Chinese patients with stage II–III ESCC after radical surgery. The results showed that diabetes mellitus is an independent prognostic risk factor for postoperative OS, and a high CVRF burden (combination of ≥3 risk factors) significantly increases the risk of postoperative mortality. This risk effect is more prominent in patients receiving chemoradiotherapy. These findings provide key evidence for the integrated management of cardiovascular risk in ESCC patients.

Results of multivariate Cox regression analysis showed that after adjusting for confounding factors, the OS risk in the high-CVRF group was significantly higher than that in the low-to-moderate CVRF group (HR =1.54; 95% CI: 1.14–2.08; P=0.005), indicating that the 5-year postoperative mortality risk in the high-CVRF group was 54% higher than that in the low-to-moderate CVRF group. Additionally, for each additional CVRF, the risk of adverse OS increased significantly by 15% (HR =1.15; 95% CI: 1.02–1.31; P=0.02). This “cumulative hazard effect” suggests that clinical practice should pay attention to the additive impact of CVRFs, and comprehensive risk intervention should be initiated earlier for patients with multiple comorbid CVRFs. Meanwhile, as an independent risk factor (HR =1.96; 95% CI: 1.41–2.72; P<0.001), diabetes mellitus indicates that the 5-year postoperative mortality risk in ESCC patients with diabetes is 1.96 times that of non-diabetic patients, suggesting that blood glucose control should be one of the core targets in the long-term management of such patients.

Subgroup analysis revealed that the adverse impact of high CVRF burden was significantly amplified in patients receiving chemoradiotherapy: in the chemotherapy subgroup, the OS risk in the high-CVRF group was 2.62 times that in the low-to-moderate CVRF group (HR =2.62; 95% CI: 1.71–4.01; P<0.001), meaning the 5-year mortality risk in patients with chemotherapy combined with high CVRFs was 162% higher than that in patients with the same treatment regimen but low-to-moderate CVRFs; in the radiotherapy subgroup, the OS risk in the high-CVRF group was 2.01 times that in the low-to-moderate CVRF group (HR =2.01; 95% CI: 1.19–3.40; P=0.009), indicating that the 5-year mortality risk in patients with radiotherapy combined with high CVRFs was 101% higher than that in patients with low CVRFs. This difference in effect size is closely related to the “treatment toxicity-underlying disease” synergistic mechanism: from an anatomical perspective, the esophagus is adjacent to the heart, so radiotherapy inevitably leads to radiation exposure of cardiac structures. When the radiation dose exceeds 10 Gy, the risk of cardiac death increases significantly (12). However, issues such as vascular endothelial dysfunction and oxidative stress associated with high CVRFs (13) further reduce the heart’s tolerance to radiation, increase the risk of radiation-induced heart diseases (e.g., pericarditis, arrhythmia), and may lead to radiotherapy interruption or dose reduction. From the perspective of drug toxicity, chemotherapeutic agents [e.g., fluorouracil-induced coronary vasospasm (14), cisplatin-increased risk of venous thrombosis (15), and paclitaxel-induced arrhythmia (16)] interact with metabolic disorders related to high CVRFs [e.g., hyperglycemia exacerbating the toxic metabolism of drugs (17)], which significantly increases the incidence of cardiovascular complications. At the same time, this interaction may also reduce the sensitivity of tumor cells to chemotherapy: hyperglycemia and hyperlipidemia enhance glycolysis and reprogram lipid metabolism (18,19), helping tumor cells adapt to the hypoxic microenvironment and resist the killing effect of energy-dependent chemotherapeutic drugs.

Although hypertension did not reach the statistical threshold for being an independent risk factor (P=0.09), the adjusted HR was still greater than 1, and a trend of increased risk was observed in the chemoradiotherapy subgroup, suggesting its potential adverse effects. Vascular endothelial damage caused by hypertension (20) exerts a synergistic effect with chemoradiotherapy-induced cardiotoxicity [e.g., radiation-induced damage to cardiac structures from radiotherapy (21-23), and inhibition of vascular smooth muscle cells by chemotherapeutic drugs (24)], increasing the risk of cardiovascular complications and thereby affecting patients’ treatment tolerance and survival (25).

The risk amplification effect of diabetes mellitus was also significant in the chemoradiotherapy subgroups: in the chemotherapy subgroup, the OS risk in patients with diabetes was 3.72 times that in non-diabetic patients (HR =3.72; 95% CI: 2.24–6.18; P<0.001), indicating that the 5-year mortality risk in patients with chemotherapy combined with diabetes was 272% higher than that in patients with chemotherapy but without diabetes; in the radiotherapy subgroup, the OS risk in patients with diabetes was 3.08 times that in non-diabetic patients (HR =3.08; 95% CI: 1.65–5.75; P<0.001), meaning the 5-year mortality risk in patients with radiotherapy combined with diabetes was 208% higher than that in patients with radiotherapy but without diabetes. This result is consistent with the role of diabetes in promoting tumor progression and affecting treatment tolerance: diabetes promotes tumor progression through the synergistic effect of metabolic abnormalities (hyperglycemia, hyperinsulinemia) and chronic inflammation. Under hyperglycemic conditions, advanced glycation end products (AGEs) bind to their receptors, activating the nuclear factor-κB (NF-κB) pathway. Activation of this pathway triggers the release of pro-inflammatory cytokines such as interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α), which not only exacerbate the inflammatory response in the tumor microenvironment (26) but also induce the expression of vascular endothelial growth factor (VEGF) to promote tumor angiogenesis. On the other hand, hyperinsulinemia activates the phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) pathway, enhancing the proliferation and invasion capabilities of ESCC cells. It also induces the polarization of tumor-associated macrophages toward the M2 phenotype, thereby suppressing immune surveillance (27). In addition, diabetes alters the pharmacokinetic and pharmacodynamic characteristics of chemotherapeutic agents (e.g., fluorouracil, cisplatin), increasing drug toxicity and reducing efficacy (17), which may lead to treatment interruption or dose reduction and further worsen patient prognosis.

Notably, this study found no significant association between dyslipidemia, high BMI, or smoking and patient prognosis. This may be attributed to the following factors: patients with dyslipidemia commonly use statins, which have immunomodulatory and anti-angiogenic effects (28); there is an “obesity paradox” in cancer patients, where higher BMI can maintain energy reserves to counteract cancer-related cachexia (29); and widespread smoking cessation after surgery offsets the adverse effects of previous smoking. These conclusions still require verification in larger-sample studies.

Based on the above findings, this study provides practical guidance for cardiovascular risk management in ESCC patients after surgery: for patients with comorbid diabetes or high CVRF burden, it is recommended to complete cardiac function assessment (e.g., echocardiography) before chemoradiotherapy; at the same time, adjustments to chemotherapeutic drug doses (e.g., reducing the initial doses of fluorouracil and cisplatin) and enhanced control of blood glucose and blood pressure are advised. During radiotherapy, target volume design should be optimized to reduce the cardiac radiation dose; meanwhile, regular monitoring of indicators such as myocardial enzymes and brain natriuretic peptide (BNP) is necessary to detect cardiotoxicity at an early stage. In addition, drugs such as statins (30) and metformin (31) may have both cardiovascular protective and anti-tumor effects, and their intervention value in ESCC patients with comorbid CVRFs could be explored in future studies.

This study has certain limitations: first, the single-center retrospective design may introduce selection bias and information bias. For example, data on the duration of CVRFs, specific treatment regimens (e.g., specific chemotherapeutic drug doses, fractional radiotherapy doses), and longitudinal cardiac monitoring were lacking. Second, the sample size was limited (497 cases), which may result in insufficient statistical power for some subgroups (e.g., female patients with high CVRF burden). Finally, the study did not distinguish between cancer-related deaths and cardiovascular-related deaths, making it impossible to accurately assess the independent effects of CVRFs on tumor progression and treatment toxicity. Future multi-center prospective studies are needed to address these limitations. Such studies should include more baseline cardiovascular assessment indicators (e.g., echocardiography, coronary computed tomography angiography) and explore whether interventions targeting CVRFs (e.g., blood glucose and blood pressure control) can improve the prognosis of ESCC patients.

Conclusions

This study confirms that diabetes mellitus and high CVRF burden are important prognostic factors in patients with stage II–III ESCC after radical surgery, and the risks associated with these factors are higher in patients receiving chemoradiotherapy. In clinical practice, cardiovascular risk assessment should be integrated into the development of cancer treatment regimens, and the dual goals of “anti-tumor and cardioprotection” should be achieved through multidisciplinary collaboration involving medical oncology, cardiology, and radiation oncology departments, ultimately improving patients’ quality of life and long-term survival outcomes.

Acknowledgments

None

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1216/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1216/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1216/prf

Funding: This work was supported by the National Natural Science Foundation of China (No. 82371593), the Natural Science Foundation of Fujian Province, China (Nos. 2020J011083 and 2022J011014), and the Medical Innovation Project of Fujian Province, China (No. 2020CXB003).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1216/coif). The authors have no conflicts of interest to declare.

Ethical Statement: 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. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. It was approved by the Ethics and Research Committee of the Fujian Provincial Hospital Affiliated to Fuzhou University (approval No. K2021-10-007). Given the retrospective nature of the study, individual informed consent for this analysis was waived by the above-mentioned ethics committee.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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