Prevalence of risk factors associated with rupture of abdominal aortic aneurysm (AAA): a single center retrospective study

Patients

All AAA patients included in this retrospective study were hospitalized at the Meizhou People’s Hospital between January 2018 and December 2022 and were diagnosed based on a computed tomography angiography (CTA) scan. Patients who suffered severe symptomatic abdominal pain were screened with abdominal ultrasound; if the ultrasound suggested an AAA, a CTA scan was subsequently arranged to confirm the diagnosis. AAA cases were diagnosed based on the clinical practice guidelines of the European Society for Vascular Surgery (ESVS) (Wanhainen et al., 2019). An aortic aneurysm with a maximal diameter of more than 3 cm was identified as an AAA. Patients who were also diagnosed with abdominal aorta pseudoaneurysm, aortic dissecting aneurysm, perforating ulcer of abdominal aorta or advanced cancers were excluded (Qiu et al., 2022). AAA patients who lacked preoperative CTA or important clinical data, such as risk factors or laboratory results, were also excluded.

All diagnoses from CTA findings were reviewed by two cardiologists. The first cardiologist wrote the CTA report of the characteristics of the AAA, and the second cardiologist confirmed the diagnosis. AAAs were only diagnosed if both cardiologists agreed. AAAs were divided into three categories based on location: ① infrarenal AAAs are located in or above the renal artery; ② pararenal AAAs are located within the 15mm below the renal artery; ③ľ; suprarenal AAAs are located more than 15 mm below the renal artery. AAA cases were defined as ruptured if a retroperitoneal and/or intraperitoneal hematoma neighboring the aneurysm sac was observed in the preoperative CTA. This study was conducted in accordance with the declaration of Helsinki. The protocol of the study was approved by the Ethics Committee of the Meizhou People’s Hospital (Huangtang Hospital), Meizhou Academy of Medical Sciences (MPH-HEC 2021-C-113). For informed consent, patients were contacted by telephone, and verbal consent was obtained from each patient before the study began.

Data collection

Demographic information and clinical characteristics including age, gender, smoking history, alcohol drinking habits, history of hypertension, history of diabetes, history of CHD, laboratory test data, and CTA data were all collected from the hospital electronic medical record system.

Patients were defined as alcohol drinkers if they consumed more than 30 g/day of alcohol. Patients were diagnosed with hypertension either by having blood pressure ≥130/85 mmHg or regularly taking antihypertensive medication. Diabetes mellitus was diagnosed by either a fasting glucose of ≥126 mg/dL or regular antidiabetic treatment. Patients were diagnosed with dyslipidemia if they met any of the following conditions: (i) serum TC ≥ 5.17 mmol/L, (ii) serum TG ≥ 1.7 mmol/L, (iii) serum HDL-C < 1.04 mmol/L, (iv) serum LDL-C ≥ 4.14 mmol/L, (v) or were taking antidyslipidemic medication.

Fasting blood samples were collected the morning after admission and before AAA treatment. Routine laboratory analyses, including HbA1c, LVEF, cTnI, BNP, hsCRP, creatinine, D-dimer, and serum lipid profiles, were performed immediately upon admission. If lab results, such as cTnI, were acquired multiple times during the hospital stay, the first results, tested prior to AAA treatment, were included in the analysis.

For patients with multiple scans during the study period, pre-operative CTA data were used to analyze the diameter and location of AAAs in this study.

Data analysis

The statistical analysis was performed using SPSS software version 22.0 (IBM Corp., Armonk, NY, USA). Continuous variables were expressed as means ± standard deviation, and categorical variables were expressed as absolute numbers (percentages). The Kolmogorov–Smirnov test was applied to determine the normality of the distribution of continuous variables. Continuous variables were compared using either Student’s t tests between two groups, or one-way ANOVA between three groups. Categorical variables were compared using the chi-square ( ${\chi }^2$) test. The logistic regression analysis was used to identify independent risk factors for rupture. Odds ratios (ORs) were calculated by adjusting for variables, such as age and gender. All tests were two-sided, and a P value <0.05 was considered statistically significant.

Patient characteristics

During the study period, a total of 603 patients who suffered symptomatic severe abdominal pain were scanned with abdominal ultrasound for suspected AAA. After selection according to the inclusion and exclusion criteria, 337 patients diagnosed with AAA were included for analysis (Fig. 1). AAA rupture occurred in 32 of the 337 (9.5%) patients. The clinical characteristics of the included AAA patients are presented in Table 1. The average age of the patients was 73.19 ± 10.26, and 85.76% of the patients were male. There were no significant differences in characteristics between rupture and non-rupture patients.

Comparison of clinical features between rupture and non-rupture AAA patients

We compared the clinical features between rupture and non-rupture AAA patients. As shown in Table 2, the AAA diameter in the rupture group was significantly larger than that in the non-rupture group (6.58 ± 2.04 vs. 4.63 ± 1.61, P < 0.001). Compared to non-rupture patients, rupture patients had higher levels of hs-CRP (91.11 ± 71.42 vs. 42.78 ± 61.01, P < 0.001) and creatinine (161.02 ± 79.34 vs. 117.42 ± 110.29, P = 0.033). AAA rupture patients exhibited lower levels of HDL-C, LDL-C and TC than non-rupture patients (0.88 ± 0.25 vs. 1.14 ± 0.36, P < 0.001; 1.99 ± 0.70 vs. 2.51 ± 0.94, P = 0.005; 3.67 ± 1.05 vs. 4.43 ± 1.25, P < 0.002; respectively). Additionally, ApoA1 and ApoB levels were lower in AAA rupture patients than in non-rupture patients (0.77 ± 0.17 vs. 0.97 ± 0.23, P < 0.001; 0.67 ± 0.20 vs. 0.80 ± 0.25, P = 0.009). There were no significant differences between rupture and non-rupture patients for common cardiovascular markers, such as cTnI and BNP.

Comparison of clinical features based on AAA size and location, and patient gender

Next, we compared clinical features of AAA patients based on AAA size and location, and patient gender. Aneurysm diameter is the single most important predictor of AAA rupture and is the most common measurement used for AAA management. As shown in Table 3, patients with AAA diameters greater than 5.5 cm had significantly higher rates of rupture (21.50% vs. 3.91%, P < 0.001). There were no significant differences in clinical features of AAA patients by aneurism diameter, except for D-dimer, which was higher in patients with AAA diameters greater than 5.5cm (5.04 ± 5.44 vs. 3.48 ± 4.15, P = 0.027). As shown in Table 4, female AAA patients had a higher rupture rate than male patients, but this difference did not reach statistical difference (12.5% vs. 9.0%, P = 0.428); compared to male patients, female patients were older (76.21 ± 11.42 vs. 72.69 ± 9.99, P = 0.027) and had higher levels of HDL-C (1.26 ± 0.44 vs. 1.10 ± 0.34, P = 0.020), TC (4.91 ± 1.52 vs. 4.27 ± 1.17, P = 0.001) and ApoA1 (1.06 ± 0.27 vs. 0.93 ± 0.22, P = 0.004). AAAs were then divided into infrarenal, pararenal and suprarenal based on their locations. As shown in Table 5, most AAAs were infrarenal, followed by pararenal and suprarenal. The rupture rate for infrarenal, pararenal and suprarenal AAAs were 9.84%, 13.64% and 4.55%, respectively. The diameter of pararenal AAAs were significantly larger than infrarenal and suprarenal AAAs (P < 0.001). There were no other significant differences in clinical features by aneurysm location.

Independent risk factors associated with AAA rupture

A binary logistic regression analysis was used to evaluate the clinical features associated with AAA rupture. Based on the results of the previous analysis, gender, smoking history, AAA diameter, HDL-C level, creatinine level and hs-CRP level were input into the regression model. As shown in Table 6, the univariate analysis found that AAA diameter, and creatinine and hs-CRP levels were positively associated with AAA rupture, while HDL-C level was adversely associated with AAA rupture. The multivariate model suggests that AAA diameter (OR = 2.499, 95% CI [1.704 –3.665], P < 0.001) and hs-CRP level (OR = 1.017, 95% CI [1.008–1.026], P < 0.001) are associated with increased risk of rupture, while higher HDL-C level is associated with decreased risk of rupture (OR = 0.024, 95% CI [0.002–0.243], P = 0.002).