Branches of the brachiocephalic was an independent risk factor for hemorrhagic pulmonary sheath (HPS) patients with acute Stanford A aortic dissection

Background: AAD refers to the blood flow into the middle membrane through the intimal rupture of the aorta. Hemorrhagic pulmonary sheath (HPS) is a common complication of Stanford-A AAD. The risk factors of HPS are remaining unclear Methods: In this study, we have probed the potential risk factors of HPS patients with acute Stanford A aortic dissection. 18 HPS patients with acute Stanford A aortic dissection were selected as the case group. The age difference ± 5 years and the same sex are set as the matching principles. 36 patients with acute Stanford-A type AD who did not detect HPS in the same period were matched according to the ratio of 1:2. Demographic data, treatment methods, AD-related disease history, clinical symptoms and Charlson comorbidity index (CCI) values of each patient were collected. Meanwhile, the values of the maximum diameter of ascending aorta (mm), aortic dissection range, and the main branch of the aorta, pleural effusion/blood, and pericardial effusion/blood were measured by two experienced cardiovascular radiological physicians. Univariate and multivariate conditional logistic regression analysis was used in this study. Results: CCI value and the branches of the brachiocephalic in the case group were significantly higher than those in the control group (p<0.05). Univariate conditional logistic regression analysis showed CCI and branches of the brachiocephalic were associated with HPS. Multivariate conditional logistic regression analysis suggested that branches of the brachiocephalic were an independent risk factor for HPS (OR=7.02, 95%CI=1.28-38.62, p=0.025). Conclusions: Branches of the brachiocephalic were an independent risk factor for HPS.

medical anatomical classification methods for AAD include Debakey typing and Stanford type. The Stanford typing method is closely related to the treatment method. Therefore, it is more commonly used [6]. The Stanford typing method divides AAD into Stanford-A and Stanford-B. Stanford-A accounts for approximately 75% of AAD. Meanwhile, the diagnosis of AAD mainly depends on the imaging examination. CT examination as one of the most important imaging method has been widely used in the diagnosis of AAD [6,7]. Multi-detector computed tomography (MDCT) has high imaging speed and high resolution. Computed tomographic angiography (CTA) has high sensitivity and specificity for AAD diagnosis. The sensitivity and specificity of both methods for AAS diagnosis are close to 100% [8][9][10]. The mechanism of AAD has not been clarified. Studies have shown that genetic or metabolic abnormalities may cause degeneration and/or cystic necrosis of collagen fibers and elastic fibers in the aortic wall, which would further result in the separation of the aortic intima and adventitia in the proximal and/or distal aorta [11][12][13]. Meanwhile, studies have shown that multiple acquired factors can affect the occurrence and development of AAD. These factors include Hypertension, trauma, infection, iatrogenic injury, dyslipidemia, atherosclerosis, pregnancy, smoking, stroke, drugs, chronic renal insufficiency, autoimmune diseases, chronic obstructive pulmonary disease, etc [6]. Approximately 77% of AAD patients are associated with hypertension. Therefore, hypertension is considered to be the most important risk factor [12]. Hypertension can lead to a variety of emergency reactions, including increased arterial wall pressure, the release of matrix metalloproteinases and various cytokines, and excessive degradation of the extracellular matrix.
Therefore, it ultimately leads to intimal injury and aortic wall degeneration [13].
Hemorrhagic pulmonary sheath (HPS) is a common connective tissue with a sheath structure in which the blood of the aortic dissection breaks into the central pulmonary artery and the aortic root.
Previous reports have suggested that HPS is a common complication of Stanford-A AAD [14]. Due to the poor evidence, previous studies used different terms to describe this complication such as intrahepatic hematoma [15,16], pulmonary sphincter hematoma [17], blood infiltration of the aorta and pulmonary vascular adventitia [18], and hemorrhage along the pulmonary sheath [19], extraluminal perivascular hemorrhage [20], and hemorrhage along the pulmonary artery [21][22][23]. The results of HPS in chest radiographs examination varies according to the range of bleeding (normal to double lung flaky infiltration) [24][25]. Sueyoshi et al. retrospectively analyzed 232 cases of Stanford-A AD patients with extravasation of blood along the pulmonary artery [23]. The results suggested that 21 cases (9.1%) of extravasated blood along the pulmonary artery, double-chamber aortic dissection, and blood in the alveoli are associated with poor prognosis. The authors speculate that the poor prognosis is due to high pressure around the pulmonary artery and massive exudation of blood around the pulmonary artery, which leads to alveolar hemorrhage and reduced pulmonary circulation [23].

Group
This study retrospectively analysis 188 patients who were diagnosed with acute Stanford-A AD by chest and abdomen CT scan and CTA examination in The Eighth Affiliated Hospital of Sun Yat-sen University between January 2011 and January 2016. 18 HPS patients were finally included based on the results of the CT scan image and CTA image. 36 acute Stanford-A aortic dissection without HPS were included and marked as the control group. Patients in the control group should satisfy the following criteria: age difference in ± 5 years, same gender, and paired with HPS patients according to the similar visiting time. Exclusion criteria complied with the following conditions: patients with chronic aortic dissection; patients with aortic dissection stenting; patients with a simple aortic aneurysm; patients with severe lesions (trauma); poor quality of CT images.

Clinical information
The data of the control group and the case group were collected: 1) baseline data (age, gender), 2) AD-related diseases information (history of hypertension, history of diabetes, history of connective tissue disease, history of chronic lung disease, history of chronic cardiovascular disease, chronic History of kidney disease, history of hyperlipidemia. 3) Clinical symptoms and clinical signs associated with AD: chest and back pain, syncope, sudden dyspnea, cough, hemoptysis or blood stasis, nervous system symptoms, shortness of breath, tachycardia, decreased blood pressure, myocardial infarction or infarction, heart failure, renal failure Abnormal liver function. 4) Treatment information (surgical treatment or conservative treatment). Charlson comorbidity index (CCI) was calculated based on the information of AD-related diseases. Table S1 showed detailed information for scoring criteria.

MDCT scanning method and CT image analysis
A 64-slice spiral CT (Aquilion TSX-101A, Canon Medical Systems (China) Co., Ltd.) was used to perform a three-phase (plain, arterial, venous) scan. The patient was placed in a supine position. Scanning was ranged from chest inlet to groin level. Scanning parameters were listed as following: tube voltage 120kV, automatic tube current, volume data layer thickness 1mm, layer spacing 0.8mm, rotation time 0.5s/Rot, pitch 0.828, collimator width 64×0.5mm. The matrix was 512×512. The window width was set to 400HU, the window level was set to 40HU. The soft tissue reconstruction algorithm was used.
The thick layer transverse image reconstruction layer had a thickness of 3 mm and a layer spacing of 3 mm. After the flat scan, a high-pressure syringe (meDRAD) was used to inject 80 ml iopromide (300 mg /ml, Bayer HealthCare Co., Ltd.) through the right elbow vein (3.5 ml/s). After the injection, 40 ml of physiological saline was added at the same rate to perform flushing. The contrast agent automatic tracking technology is used to trigger the arterial phase scan. Firstly, a layer is pre-scanned on the diaphragm plane as the detection plane. The region of the aortic cavity is placed to trigger the region of interest to monitor the change of CT value in the aortic cavity. The scanning interval was 1 s. The auto-trigger CT threshold was set to 150HU. When the CT value threshold of the interested region reached 150HU, the delay 6s automatically started scanning to acquire the arterial phase image. The venous phase was scanned 65 seconds after the contrast injection. The scanning range and scanning parameters were the same as those of the arterial phase. Acute Stanford-A aortic dissection refers to dissection that separates the intima of the ascending aorta from the adventitia [26]. Meanwhile, the onset time is <14 days [27]. The HPS diagnostic criteria were listed as following: 1) The CT scan image had a circular, crescent-shaped high-density shadow around the main pulmonary artery and/or pulmonary artery trunk or branch vessel wall. 2) Enhanced CT images showed that ring-shaped, crescent-shaped shadows were low-density soft tissue shadows without enhancement. Aortic branch vascular involvement is defined as the following: 1) The torn inner membrane entered into the intima of the branch vessel. The branch vessel was supplied by the true cavity and the false lumen. 2) The inner membrane of the branch vessel was completely torn. The blood supply of the branch vessel was completely from the false lumen.
3) The tearing inner membrane did not enter the branch vessel. The blood supply of the branch vessel was derived from true lumen with branch vessels. Any combination of dissection involving the brachiocephalic or left common carotid artery or left subclavian artery or brachiocephalic trunk left subclavian artery and left common carotid artery was defined as involvement of the brachial vascular branch. Any combination of dissection involving the celiac trunk or superior mesenteric artery or left or right renal artery or celiac trunk, superior mesenteric artery, left renal artery, and the right renal artery was defined as abdominal branch vessel involvement.
Chest or pericardial exudate CT value > 20HU was defined as chest or pericardial hemorrhage [28].
Definitions of hypertension, heart disease, and dyslipidemia were referred to published guidelines [29,30].

Statistics
Data analysis was performed using the SPSS 20.0 software package (Version 16, IBM, USA).
Quantitative data with normal distribution were expressed as mean and standard deviation.
Quantitative data with non-normal distribution were expressed by median and quartile. Categorical variables were described by percentage. The nonparametric rank-sum test (Wilcoxon method) was used to compare the difference of the age the maximum diameter of the ascending aorta, and the CCI index between the case group and the control group. Χ 2 test and Fisher exact probability method were used to calculate the differences of gender, CCI, aortic dissection, aortic main branch vascular involvement, pleural effusion/blood, pericardial effusion/blood, hypertension, basic disease history, clinical symptoms, clinical Signs between the case group and the control group. Before the single factor logistic regression analysis, the variables were assigned (Table S2). The single factor regression analysis of 1:2 matching data was performed to calculate the P-values, odds ratio (OR) and odds ratio (OR) with 95% CI of age, gender, maximal diameter of ascending aorta, CCI, the extent of aortic dissection, the involvement of major branches of the aorta, pleural effusion/blood, pericardial effusion/blood, hypertension. Before the multiple factor logistic regression analysis, the variables were assigned (Table S3). All factors with p < 0.1 were included in a 1:2 matched multivariate conditional logistic regression analysis (fitting using Cox in survival analysis) to screen for risk factors for HPS. The odds (OR) was used as an approximate estimate of relative risk (RR). OR>1 was an independent factor, and OR<1 is an independent protective factor. In the single-factor analysis test, the test level was α=0.1. In a multivariate analysis test, the test level was α=0.05. All p values represent the two-sided probability.

Basic information
In this study, a total of 188 patients, including 136 males (72.3%) and 52 females (27.7%) with acute Stanford-A AD were enrolled. The male to female ratio of total patients was 2.61:1, with an age range of 29-78 years and an average age of 59 years. There were 18 Stanford-A AD patients with HPS (case group), 13 males and 5 females. The male to female ratio of those patients was 2.6:1. The youngest was 34 years old, and the oldest was 74 years old. The average age was 60.0 years. In the control group, members were matched with 2:1 for each HPS in the case group (age ≤ 5 year and the same gender). A total of 36 Stanford-A AD patients without HPS were included in the control group (26 males and 10 females, aged 29-78 years). The average age was 60.0 years old. There was no significant difference between the two groups (p>0.05). The detailed information of patients was listed in Table 1 and Table 2 Table 3. Moreover, we have further compared the Charlson comorbidity index (CCI) between the two groups ( Table 4). The results suggested that significant differences could be detected in both groups. In the case group, the median CCI was 2, the 25th percentile was 1; the 75th percentile was 3. Meanwhile, in the control group, the median CCI was 1, the 25th percentile was 1; the 75th percentile was 1.5 (Table 4). There were statistical differences between the two groups in the CCI index rank-sum test and CCI score distribution chi-square test (P<0.05).

Clinical information
In this study, we have further compared the clinical symptoms, clinical signs, and MDCT features between the two groups. In clinical symptoms study, we have compared six indexes, including chest pain, syncope, sudden breathing difficulty, hemoptysis or blood stasis, cough, and shortness of breath. There are no significant differences could be harvested (P>0.05) ( Table 5). In clinical signs study, we have studied tachycardia, blood pressure drop, myocardial infarction or ischemia, renal failure, and abnormal liver function. The results indicated that no differences between these six indexes could be detected between the two groups (P>0.05) ( Table 6). Moreover, we have studied the MDCT features between the two groups ( Table 7). The results revealed that no differences could be harvested in maximum diameter of ascending aorta (mm), aortic dissection range, pleural effusion/blood, and pericardial effusion/blood. However, patients number related to branches of the brachiocephalic and ventral branch in case group was significantly higher than that in the control group (P<0.001). This result indicated that the main branch of the aorta was an important indicator for HPS patients in the case group.

Univariate logistic regression analysis
In this study, HPS was used as the dependent variable Y. Meanwhile, all other factors were used as the independent variable X. We performed the univariate logistic regression analysis. The results suggested that no relationships could be retrieved between age, gender, hypertension and HPS (P>0.05). However, the CCI value in the case group was lower than that in the control group (P=0.077). Moreover, we had also calculated the relationship between other MDCT features and HPS.
The results suggested that close relationships could only be detected between branches of the brachiocephalic and HPS ( Table 8). The results mentioned above revealed that branches of the brachiocephalic and CCI value were two risk factors for HPS patients (P<0.1).

Multivariate logistic regression analysis of HPS
Based on the results of univariate logistic regression analysis, two variables with p<0.1 (CCI, branches of the brachiocephalic) were selected for multivariate logistic regression analysis. To avoid the false negative variables in multivariate analysis, P < 0.1 is considered to be related to HPS in multivariate logistic regression analysis. Enter method was used in multivariate logistic regression analysis. HPS was considered as the dependent variable with a value of 1. Meanwhile, no HPS as the dependent variable assigned a value of 0. Multi-factor conditional logistic regression analysis was carried out with a 1:2 match ratio (case group: control group) at the test level of ɑ=0.05. Multivariate logistic regression analysis of variable names and assignment instructions were listed in Table S3. The results suggested that branches of the brachiocephalic are an independent risk factor for HPS (OR=7.02, 95%CI=1.28-38.62, p=0.025) ( Table 9).

Discussion
In this study, the average age of 188 patients with acute Stanford-A AD was 59.0 years old. Although the onset age of acute AD patients continued to increase with the aging of cardiovascular and cerebrovascular diseases and the aging of the population, the overall average age did not change much. The minimum age of this group of patients was 29 years old, and the maximum age was 78 years old (Average age=59.0 years). This is consistent with previous research results (64±14.1 years) [14]. Men are more likely to develop acute Stanford-A AD than women. In this study, Male to female ratio was 2.61:1. Males accounted for 72.3% of all patients. The international related acute AD database (IRAD) had reported that male acute Stanford-A AD patients accounted for 2/3 of all acute Stanford-A AD patients. The results in this study were adopted with the literature reports [31]. It is speculated that the high incidence rate of acute Stanford-A AD in the male may be related to the bad habits of men such as smoking and drinking. Moreover, the clinical manifestations of patients with AAD are diverse. The literature reported that sudden chest pain or back pain (96%) is the most common clinical symptom. The pain is continuous tearing, piercing, and knife cutting [32]. IRAD had studied a large sample size of AAD. The work (2932 cases) suggested that 85% of type A AAD clinical symptoms were chest pain [14]. In this study, 53 patients presented with chest pain (98.1%), which was higher than the results reported, which may be caused by the small sample size.
Multiple risk factors could be related to AD, including hypertension, trauma, dyslipidemia, iatrogenic injury, pregnancy, drugs, smoking, chronic renal insufficiency, chronic obstructive pulmonary disease, stroke, Marfan syndrome, etc [5,6,14]. Hypertension is the most important risk factor for AD (77% of AD patients with hypertension) [14]. Hypertension could lead to changes in arterial hemodynamics, increased aortic insufficiency, and increased pressure in the arterial wall. Meanwhile, hypertension could promote the release of matrix metalloproteinases and inflammatory factors, causing excessive degradation of the extracellular matrix and altering the morphology of collagen fibers in the aortic wall. In this study, 52 patients (96.3%) with Stanford-A AD had a history of hypertension, which was higher than the results of previous studies (70%) [33]. We speculated that it could be related to the high incidence of hypertension in China. Meanwhile, a variety of underlying diseases can affect the development of AD, such as chronic renal insufficiency, chronic obstructive pulmonary disease, infectious vascular disease, and so on. In this study, the CCI score was used to reflect the overall underlying disease status. The CCI index of the case group was higher than that of the control group.
There was a statistically significant difference between the two groups. Univariate analysis showed that the CCI score was one of the risk factors for HPS. However, CCI was not an independent risk factor for HPS.
The formation and development of aortic dissection are associated with increased arterial blood flow pressure. Muta et al. suggested that pulsating blood flow pressure could repeatedly act on the edge of AD dissection, leading to AD expansion. Therefore, pulsating blood flow pressure is the most important factor affecting AD [34]. In this study, CCI and branches of the brachiocephalic were included in multivariate analysis. Hypertension and the maximum diameter of the ascending aorta had not been included in this study. Previous work indicated that aortic wall tension was increased when the blood pressure was increased. The higher the blood pressure of AD patients, the more likely the aortic rupture occurs. However, in B-type AD patients, there is no evidence about the relationships between higher blood pressure and aortic rupture based on the multi-factor analysis [35]. Although hypertension was the cause of AD, it was not necessarily a risk factor for AD rupture.
We speculated that the fluctuations in blood pressure may have a greater impact on dissection rupture. Theoretically, the larger the aortic diameter, the more easily the aortic dissection was broken. However, the CT three-dimensional image study of AD patients showed that the higher ratio of the maximum diameter of the aortic dissection to the length of the dissection, the greater the risk of interlayer rupture [36]. In this study, no significant differences in the maximum diameter of the ascending aorta and the extent of involvement of the aortic dissection could be observed between the case group and the control group. The ratio of the maximum diameter of the aortic dissection to the length of the dissection had not been included in the study. Therefore, the correlation between the maximum diameter of the ascending aorta and HPS remains to be further studied.
The proportion of patients with involvement of branches of the brachiocephalic in the case group was higher than that in the control group (33.30% for the case group and 8.33% for the control group).
There was a statistically significant difference between the two groups (p<0.001). Univariate analysis showed CCI and branches of the brachiocephalic were closely related to HPS. Multivariate analysis showed that the involvement of branches of the brachiocephalic was an independent risk factor for HPS compared with the involvement of the ventral branch. Chang et al. showed that the degree of involvement of the main branches of the aorta can indirectly reflect the intracavitary tension and can indicate the risk of AD [37]. The involvement of the branches of the brachiocephalic may change the intra-orbital tension which could further cause increased blood flow impact and rupture of the ascending aorta. The results of this study showed that the risk of HPS involvement in the branches of the brachiocephalic was 7.02 times higher than that of the ventral branch, which may be due to the highest anatomical location of the brachiocephalic artery to ascending aorta. However, the relationships between the branches of the brachiocephalic number, brachiocephalic artery, left common carotid artery, left subclavian artery, and the HPS has not been fully demonstrated.
Therefore, further study was necessary to conduct in related areas.

Conclusions
In summary, univariate analysis showed that CCI and branches of the brachiocephalic were the two major risk factors for HPS associated with acute Stanford-A AD. Meanwhile, multivariate analysis revealed that branches of the brachiocephalic were an independent risk factor for HPS.

Authors' contributions
Qiuxia Xie: Study design, concept, writing; Haoling Qin and Ling Lin: Data collection, data analysis; Jian Guan, Xuhui Zhou: Corresponding author; Xuhui Zhou: Review the data organization; Jian Guan: Review the data management. All authors read and approved the final manuscript.

Funding
Not applicable.

Availability of data and materials
The datasets generated during the present study are not publicly available, because detailed clinical information of each participant was included in these materials.

Ethics approval and consent to participate
The study design was approved by the Ethics Committee of the Eighth Affiliated Hospital of Sun Yatsen University (No: SunYat-sen-2011-KY-EAH-032; Aug. 8, 2011). Written informed consent was obtained from all participants. All procedures performed in studies involving human participants were following the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.

Consent for publication
Not applicable.    Table 4 Charlson comorbidity index (CCI) comparison between the case group and the control group 20 * Median value; # (The first quartile value, the third quartile value)