Lithuanian University of Health Sciences Faculty of Medicine
Department of Radiology
Title of Master’s Thesis:
Influence of gender, age and comorbidities on CT measurements
and location of infrarenal abdominal aneurysms
A Dissertation Submitted in Partial Fulfilment of the Requirements for the Degree Master of Medicine
Lithuanian University of Health Sciences
Author: Carl Bruno Neisser
Supervisor:
Prof.Dr.med. Saulius Lukoševičius
Kaunas 2017 – 2019
TABLE OF CONTENTS
SUMMARY………..3
ACKNOWLEDGMENTS………...………...…...4
CONFLICTS OF INTEREST………...……5
ABBREVIATIONS………...5
PERMISSION ISSUSED BY THE ETHICS COMMITTEE………...6
INTRODUCTION……….7
AIM AND OBJECTIVES………...8
LITERATURE REVIEW………..9
RESEARCH METHODOLOGY AND METHODS………..14
RESULTS………17
DISCUSSION OF THE RESULTS………23
CONCLUSIONS……….25
REFERENCES………26
SUMMARY
Author name: Carl Bruno NeisserResearch title: Influence of gender, age and comorbidities on CT measurements and location of infrarenal abdominal aneurysms
Aim: The aim of this master thesis is to estimate the influence of gender, age and comorbidities on CT measurements and location of infrarenal AAA.
Objectives:
1. To determine the effect of unchangeable risk factors (gender, age) on the size and location of infrarenal AAA.
2. To analyse how the total number of certain comorbidities per patient affect the size and location of infrarenal AAA.
3. To determine the effect of single comorbidities on the size and location of infrarenal AAA.
Methodology: This is a retrospective evaluative study. All examinations were undertaken using high-resolution spiral computed tomography with intra-aortic iodine-based contrast media. The measurements of the AAA were conducted using the Syngovia program and only AAA that fitted the inclusion criteria were further evaluated. All the measurement data was collected in Microsoft Excel, which was further used to conduct the statistical analysis of the data and two linear regression analyses were performed.
Results: As a consequence of the sample size (46 observations) the conclusions drawn from this work cannot be implemented on the whole population. Female gender always had a negative effect on AAA length and width in our research. During the linear regression
analysis the width of AAA showed a statistical significant effect on the length of AAA yet the width of AAA is less of a predictor of AAA size and location than the length of AAA, which throughout the linear regression analysis showed the most statistical significant results as its P-value was always <0,05. Also hypertension was proven to have a statistical significant effect (P-Value: 0,047) on the width of AAA.
Conclusion:
1. Female gender always had a negative effect on AAA length and width during our research, thus making female AAA shorter and narrower than compared to the male patient group.
2. The length of AAA was the most statistical significant variable since the P-value was always <0,05 and therefore has the qualities of being a good tool to use in evaluation of AAA size and location characteristics.
ACKNOWLEDGMENTS
I would like to dedicate this thesis to my parents, as I cannot express enough thanks for their continuous support and encouragement. Thank you! This accomplishment would not have been possible without you!
I express my gratitude to my supervisor Prof.Dr.med. Saulius Lukoševičius for his valuable guidance and supervision throughout this research project.
I would also like to express my appreciation to Denise Gawron for her patience and help with the statistical part of this study.
CONFLICTS OF INTEREST
The author reports no conflicts of interest.ABBREVIATIONS
AAA – Abdominal Aortic AneurysmUS – Ultrasound
CT – Computed Tomography
CTA – Computed Tomography Angiography EVAR – Endovascular Aneurysm Repair
PERMISSION ISSUED BY THE ETHICS COMMITTEE
Approved by: LSMU bioethical centreBiomedical research name: To estimate the influence of gender, age, comorbidities and infrarenal AAA CT measurements on the size and location of infrarenal AAA
Number: BEC-MF-89 Date: 2018-11-19
INTRODUCTION
Abdominal aortic aneurysm (AAA) is a condition characterised by an enlargement of the abdominal aorta, in which the diameter of the aorta is greater than 3cm or exceeding the normal diameter by at least 50% [1].
Through autopsy studies it has been concluded that 1-2% of the population has aortic
aneurysms, with AAA being the most common type due to a prevalence of about 5% among men older than 65 years [6][3].
The normal diameter of the abdominal aorta is around 1,8cm – 2cm. AAA mainly affects an elderly population in which males are mainly afflicted with a male-to-female ratio of AAA being 4-6 times more common [1][2].
Recent studies have shown that the gradual enlargement of the diameter of the aorta is associated with an increased risk of AAA rupture, which is a life-threatening event with high mortality rates up to 80% [4][5].
As there is currently no effective treatment for existing AAA, the main goals are early identification and elective treatment before they rupture. Surgical treatment is recommended by current guidelines when the AAA starts to become symptomatic manifesting with low back or abdominal pain, when the AAA diameter exceeds 5,5cm in men and in women at an aneurysm diameter of 5cm, since the risk of rupture is higher in woman than in men. Options of treatment include endovascular aneurysm repair (EVAR) or an open aneurysm repair (OR) [1][5][7].
The main risk factors for aneurysm development are advanced age, tobacco smoking and hypertension. These risk factors also apply in case of AAA with the addition of male gender, a positive family history of AAA, hyperlipidaemia, and cardiovascular diseases [1][4]. Currently it’s believed that smoking is potentially one of the most important risk factors for AAA development due to its modifiable character, since decreasing or the total cessation of smoking can prevent a further growth in diameter of the AAA.
The aim of this master thesis is to estimate the influence of gender, age, comorbidities and infrarenal AAA CT measurements on the size and location of infrarenal AAA. We hope to find significant correlations between the independent and dependent variables and to evaluate the influence of specific clinical diagnoses on AAA size and location.
AIM AND OBJECTIVES
Aim:The aim of this master thesis is to estimate the influence of gender, age and comorbidities on CT measurements and location of infrarenal AAA.
Objectives:
1. To determine the effect of unchangeable risk factors (gender, age) on the size and location of infrarenal AAA.
2. To analyse how the total number of certain comorbidities per patient affect the size and location of infrarenal AAA.
3. To determine the effect of single comorbidities on the size and location of infrarenal AAA.
LITERATURE REVIEW
The prevalence of about two million diagnosed patients and approximately 15,000 deaths annually in the United States make Abdominal Aortic Aneurysms (AAA) a very common and potentially life-threatening disease [4][8].
The main causative risk factors for AAA development have been identified and are closely related to male gender, hypertension, smoking and a positive family history of AAA. But until now the exact pathogenesis of AAA still remains unclear [2].
AAA can have numerous different symptoms but in most cases presents asymptomatic. Later in the course of the disease the most serious complication of AAA is rupture with a high mortality rate [9].
Epidemiology of AAA
AAA is a disease mainly presenting in the elderly population, with reaching a peak of 4% in people older than 60 years of age [2]. This is due to the fact that risk factors like smoking and hypertension gradually damage and thus weaken the aortic wall over a longer period of time and therefore result in a detectable enlargement of the aorta in later years mainly.
It’s 4 to 6 times more common for AAA to affect males than females and it’s also more common in white populations [1][4].
Studies have shown that AAA in men start around the age of 50 years, whereas in women the disease starts around the age of 60-70 years. In both genders the prevalence increases
significantly with each decade. Since 2000, there is a decline in prevalence of AAA, which is mainly thought to be the result of a change in risk factors, especially smoking habits [10].
Risk factors of AAA development
Smoking, advanced age, hypertension, male gender, hyperlipidaemia, a positive family history of AAA, atherosclerosis and cardiovascular disease are risk factors that are associated with the development of AAA [1][10].
Studies have proven that the main risk factors of AAA development are advanced age, smoking, male gender and a positive family history, in which smoking is potentially the most important and definitely a very strong risk factor for the presence of AAA [1][11].
Results from a screening study have shown a clear relation between duration and amount of smoking and prevalence of AAA. It was also shown that the risk factor smoking outdoes all other modifiable risk factor regarding prevalence of AAA. Due to smoking being such a
strong risk factor, the US Preventive Services Task Force decided to recommend screening check-ups for all men aged 65 to 75 years of age who have ever smoked [11][12].
Location of AAA
About 80% of AAA are located between the renal arteries and bifurcation of aorta, where the dilation begins below the branch off of the renal arteries. This type of AAA is called
infrarenal AAA, shown in fig.1. [13][9].
Then there is also suprarenal AAA, where one or more visceral arteries are part of the aneurysm, but the aneurysm does not extend into the chest, shown in fig.1. [13]. Pararenal AAA in which the renal arteries but not the superior mesenteric arteries are involved in the aneurysm, shown in fig.1. [13].
Lastly juxtarenal AAA, where the aneurysm originates at the junction to the renal arteries, shown in fig.1. [13].
Figure 1. Classification of AAA regarding their location
Pathogenesis of AAA
Till now the exact pathogenesis of AAA is still unknown. Even though different theories have been proposed, none of them have been fully accepted [2].
The main connective tissue constituents of the aortic vessel wall are collagen and elastin fibres. They are the major element in determining the mechanical properties of the aortic
vessel wall. The development of AAA is closely related to an inflammatory process in the aortic vessel wall leading to a degradation of the connective tissue fibres which in turn leads to a loss of structural integrity of the aortic wall. Studies have shown the presence of
disruption of linearity of elastic and collagen fibres in the aortic wall, as well as an increased amount of inflammatory cells in the outer layer of the aortic wall [2].
Expansion rate of AAA
The current available guidelines recommend treatment amongst other things if the AAA grows at a rate greater than 5 mm in six months [5]. This is due to the fact that studies have shown that the risk of rupture of AAA is not only affected by the size of the AAA but also by the expansion rate of the AAA [15].
The growth rate of AAA is reported to be between 1mm-8mm per year, with a mean growth rate of 2,2mm per year for both genders [1].
The expansion rate of AAA is closely related to risk factors like smoking, hypertension and female gender, in which the expansion rate is increased. On the other hand it is reported that diabetes mellitus and peripheral vascular disease have a slowing effect on the expansion rate of AAA [9].
Clinical features of AAA
Most AAA are asymptomatic or present with nonspecific symptoms, therefore the majority are discovered as incidental findings during routine physical examinations or US and/or CT scans [9].
Asymptomatic AAA can be discovered as a pulsatile abdominal mass at or above the level of umbilicus during a physical examination, but the sensitivity is poor since it is based on the practitioner’s skill and experience [10].
Symptomatic AAA can present as lower back pain or ischaemic symptoms in the lower extremities due to peripheral thrombosis or embolization of distal peripheral vessels. This can represent as blue toe syndrome and livedo reticularis [16].
A ruptured AAA represents as a hemodynamically unstable patient with abdominal pain that radiates to the back and a palpable pulsatile abdominal mass. But it’s important to point out that not all patients represent with those classic symptoms of an AAA rupture [16].
Screening and diagnostics of AAA
For a screening modality the availability, risk and reliability of the specific test are most important for evaluating whether the test suits as a screening modality or not. It is important for the test to have both a high specificity as well as sensitivity.
At the moment ultrasonography meets these criteria for AAA and is therefore used as a screening modality. The advantages of US are that it is inexpensive, easily available and transportable, non-invasive and if operated by an experienced practitioner the sensitivity as well as specificity are very high as well [4].
CT measurements of AAA are used for clinical decision-making and are considered the most accurate modality for planning interventions [17].
Nowadays CTA is the preferred imaging modality for AAA prior to interventions like endovascular aneurysm repair (EVAR), because they require very accurate and detailed measurements of the aorta which can be achieved using CTA [18].
CT or CTA are not suitable as screening modalities for AAA even though they produce more accurate measurements than US, because they expose the patients to significant doses of radiation. Furthermore CTA involves the use of a contrast media, which is always related to the risk of nephrotoxicity thus resulting in kidney damage [19].
Rupture of AAA
Rupture of AAA occurs when the local wall stress exceeds the local wall strength leading to a tear in the aortic vessel wall [19].
The main current rupture risk indicators of AAA are size and expansion rate of AAA. It’s accepted that AAA size is the best indicator for AAA rupture risk, but more and more and studies have shown clear relationships between high risk of AAA rupture and AAA expansion rate. Therefore rupture risks groups can be divided using the following:
Low risk – Diameter <5cm, Expansion rate <0,3cm/y. Average risk – Diameter 5-6cm, Expansion rate 0,3-0,6cm/y. High risk – Diameter >6cm, Expansion rate >0,6cm/y [20].
Treatment of AAA
The treatment of AAA mainly depends on size and expansion rate of AAA. Most guidelines recommend invasive treatment of AAA at a size of 5,5cm in men and 5cm in women or at an expansion rate greater than 5mm per six month or >10mm in one year [21].
Since the emergence of EVAR in the early 1990s, it has strongly increased in importance and surpassed conventional open repair of AAA as the invasive intervention of choice in most patient cases [22].
The main goal of AAA repair is to relieve the sac of the aneurysm from the high-pressure blood flow and still maintain a normal blood flow through the aorta with a normal diameter. In EVAR, the stent acts as a conduit for the blood flow and it also maintains a certain
diameter. The main complications of EVAR are unintended coverage of renal or iliac arteries, endoleaks, renal failure, bleeding or infection of wound or stent graft [23].
The general operative risk was described by a study that found an average mortality rate of 5,5% including all types of invasive treatments [24].
RESEARCH METHODOLOGY AND METHODS
Methodology: This is a retrospective evaluative study. All examinations were undertaken using high-resolution spiral computed tomography with intra-aortic iodine-based contrast media using one of the two CT scanners, Toshiba Aqilion ONE (Canon Medical Systems Europe) or LightSpeed VCT (GE Healthcare). The contrast media used was 300mg Iodine – 100ml. The measurements were taken with the patient in the supine position. Themeasurements of the AAA were conducted using the Syngovia program (Syngo.Via, Siemens, Healthinners).
Microsoft Excel was used to conduct the statistical analysis of the data and two linear regression analyses were performed.
The literature review was conducted using several databases including ScienceDirect, PubMed and UpToDate. More than 70% of the cited publications are less than 10 years old. The search terms used were: ‘Abdominal Aortic aneurysm’, ‘Radiologic evaluation of AAA’, ‘AAA CT imaging’, ‘AAA risk factors’, ‘AAA treatment’. Keywords were matched to database indexing terms.
Selection criteria: Only infrarenal AAA were included in the measurements. Inclusion criteria were as follows: Patients with non-operated infrarenal AAA with a minimum diameter of 3cm undergoing CTA examination between the 11th of January 2017 and 29th of November 2017. Exclusion criteria were: Non-infrarenal AAA, diameter < 3cm, placement or use of stents or other invasive therapies.
The sample size was 46 patients that fitted into the selection criteria. Of those 46 patients seven were female and 39 were male.
Measurement tactics: The measurements were conducted at different positions of the AAA to improve the quality and accuracy of comparison between the patients. All measurement figures used below are taken from the Syngovia program (Syngo.Via, Siemens, Healthinners). The Length of the AAA was measured in two different tomographic sections, once in the sagittal and once in the frontal section. Then the average was taken from both measurements as the final length.
Figure 2. Length of AAA measurements. On the left, length of AAA measured in the sagittal section (D1). On the right, length of AAA measured in the frontal section (D7).
The width was measured using the axial tomographic section. We conducted two
measurements. The first measurement was taken at the widest diameter of the AAA. The second measurement was taken perpendicular to the first one. Then the average was taken from both measurements again as the final width.
To measure the size of the thrombus, we decided to measure the lumen of the AAA without including the thrombus and subtract the lumen of the AAA without the thrombus from the total width of the AAA (including the thrombus). The lumen of the AAA excluding the thrombus was measured in the axial tomographic section at two points. The first measurement was taken again at the widest diameter of the AAA lumen till the thrombus and the second measurement was taken perpendicular to the first one. Then the average was taken from both measurements again as the final inner width. Then
we subtracted the final inner width from the final width to get the approximate size of the thrombus. Figure 3. Width of AAA and thrombus
measurements. Width of AAA measured in the axial section (D3, D4). Thrombus measurements in the axial section (D5, D6). Now the average of D3+D4 is taken as well as the average of D5+D6. To get the approximate size of thrombus the
Finally we measured the distance of the AAA to the aortic bifurcation and the distance from the lower renal artery (we always chose the renal artery that attaches to the aorta closest to the AAA) to the beginning of the AAA. The distance from the AAA to the aortic bifurcation was measured using the sagittal tomographic section. The distance from the lower renal artery to the beginning of the AAA was measured using the frontal tomographic section.
Figure 4. On the left, measurement of the distance from the lower renal artery to the beginning of AAA in the frontal section (D8). On the right, measurement of distance from the AAA to the aortic bifurcation in the sagittal section (D9).
Patient diagnoses: The patient information was accessed using the hospital information system and checked for any diagnosis besides AAA. Only diagnoses that affect the growth and/or development of AAA or diagnoses that affect the vasculature in general were taken into account. The resulting list of diagnoses is as follows: Hypertension, atherosclerosis, angina pectoris, coronary artery disease, diabetes mellitus, carotid artery stenosis, myocardial infarction.
RESULTS
Differences between the male and female group of patients
The total sample size was 46 patients, with 7 being female and 39 being male. Two patients that fitted the inclusion criteria had to be excluded from the study due to missing online diagnosis.
The average age of the male patients is 72,32 years of age and that of the female patient group is 71,57 years of age.
Figure 5. Histogram showing age distribution among the participants
The average length of the AAA of the male group of patents is 8,76cm whereas the length of the female group of patients is 7,48cm. The average length of all patients together is 8,57cm. The measurements for the width of AAA are similar, in which the average width of the AAA of the male group of patients is 5,52cm and the average width of AAA of the female group of patients is 4,79cm.
The thrombus size is bigger on average in male patients with an average size of 2,20cm, compared to the 1,87cm in female patients.
The distance of the AAA to the aortic bifurcation is very similar in both patient groups. The average distance of AAA to the aortic bifurcation of the male patients group is a little shorter with 0,51cm compared the female patients groups with 0,54cm in length.
The average distance of the AAA to the lower renal artery is a lot bigger than compared to the distance of the AAA to the aortic bifurcation. The average distance of the AAA to the lower renal artery in the male group of patients is 3,64cm in length whereas in the female group of patients is 4,35cm in length.
Table 1. Measurement results of the male and female groups of patients Gender Age (years) Length of AAA (cm) Width of AAA (cm) Thrombus Size (cm) Distance of AAA to bifurcation (cm) Distance of AAA to Lower Renal Artery (cm)
Male 72,32 8,76 5,52 2,20 0,51 3,64
On average female patients had in addition to the diagnosis of AAA 1,29 further
comorbidities, whereas male patients had 1,15 further comorbidities. On average both patient groups together had 1,17 further comorbidities besides the diagnosis of AAA.
Linear Regression Model No. 1
A linear regression model was produced for certain variables affecting the AAA size and location. The regression-statistics and linear regression analysis results are collected in tables and shown in the annexes at the end.
1. Linear regression analysis of the width of AAA
Estimates the influence of gender, age, number of diagnoses and the length of AAA (independent variables) on the width of AAA (dependent variable).
The linear regression analysis shows, that male patients have on average a 0,36cm larger width of AAA than female patients. The correlation between the width of AAA and the length of AAA is statistical significant (p<0,001). If the length of AAA increases by 1cm the width of AAA will increase by 0,28cm.
The diagram below shows the correlation between the width of AAA and the length of AAA. The blue markers show the official width of the AAA of the patients examined and the red markers show the estimated width of AAA for the examined patients. The diagram clearly shows a correlation between the two variables.
Figure 3. Official and estimated width of AAA represented using the correlation between width of AAA and length of AAA
0,00 1,00 2,00 3,00 4,00 5,00 6,00 7,00 8,00 9,00 10,00 0,00 2,00 4,00 6,00 8,00 10,00 12,00 14,00 16,00 Width of A A A in c m Length of AAA in cm
We can use the data from Table 3. in the annexes to estimate the width of AAA of any patient. For example a 65 year old women with 2 diagnoses and an AAA length of 7,5 cm would have a theoretical AAA width of 4,6cm.
2. Linear regression analysis of the length of AAA
Estimates the influence of gender, age, number of diagnoses and the width of AAA (independent variables) on the length of AAA (dependent variable).
Once again the linear regression analysis shows a statistical significant correlation (p<0,001) between the length of AAA and the width of AAA, meaning if the width of AAA increases by 1cm the length of AAA will increase by 1,39cm.
The diagram below shows the correlation between the length of AAA and the width of AAA. The blue markers show the official length of the AAA of the patients examined and the red markers show the estimated length of AAA for the examined patients. The diagram shows a correlation between the two variables.
Figure 4. Official and estimated length of AAA represented using the correlation between length of AAA and width of AAA
3. Linear regression analysis of the distance of AAA to the lower renal artery
Estimates the influence of gender, age, number of diagnoses, the length of AAA and the width of AAA (independent variables) on the distance of AAA to the lower renal artery (dependent variable).
Looking at Table 7. in the annexes it shows that only the length of AAA has a statistical 0 2 4 6 8 10 12 14 16 0 1 2 3 4 5 6 7 8 9 10 L en gt h of AAA in c m Width of AAA in cm
case the length of AAA has a negative relationship with the distance of AAA to the lower renal artery meaning that if the length of AAA increases by 1cm, the distance of AAA to the lower renal artery decreases.
4. Linear regression analysis of the distance of AAA to the aortic bifurcation
Estimates the influence of gender, age, number of diagnoses, the length of AAA and the width of AAA (independent variables) on the distance of AAA to the aortic bifurcation (dependent variable).
The linear regression analysis shows a statistical significant correlation (p<0,001) between the distance of AAA to the aortic bifurcation and the length of AAA. The distance of AAA to the aortic bifurcation increases with increasing number of diagnoses, male gender and increasing width of AAA. On the contrary the distance of AAA to the aortic bifurcation decreases with increasing age and increasing length of AAA.
Linear Regression Model No. 2
A second linear regression model was developed to evaluate the impact of specific diagnoses on the size and location of infrarenal AAA, instead of the total amount of certain diagnoses and demographic data of the patients.
Due to the small sample size the new linear regression model only includes the two most frequent presenting diagnosis of the patient group and the variable that was proven to be statistically significant in most previous linear regression models. Hypertension (14 patients) and angina pectoris (13 patients) were presenting most frequently in the observed patient group. In the previous linear regression models the length of AAA was always statistically significant.
By including fewer variables we prevent the problem of overfitting a model, which could result in misleading coefficients, p-values and R-squared. Studies have shown that 10 to 15 observations for each predictor variable will generally allow good estimates [25].
Therefore including 3 variables, with each having more than at least 13 observations, should work well with a sample size of 46 observations.
5. Linear regression analysis of the width of AAA using only three variables
Estimates the influence of the diagnosis of hypertension and angina pectoris as well as the length of AAA (independent variables) on the width of AAA (dependent variable). The linear regression analysis shows, that both the length of AAA and the diagnosis of
width of AAA is 0,67cm larger. Therefore the diagnosis of hypertension shows a statistical significant correlation with the width of AAA. The influence of the length of AAA on the width of AAA is again statistically significant as it was in the first model and the impact of the length of AAA on the width of AAA is almost identical to the previous model, this means that the effect of length of AAA on the width of AAA stays almost unchanged when adding specific diagnoses.
6. Linear regression analysis of the length of AAA using only three variables
Estimates the influence of the diagnosis of hypertension and angina pectoris as well as the width of AAA (independent variables) on the length of AAA (dependent variable). This time the width of AAA is used as the third variable, because the length of AAA is already the dependent variable and the width of AAA showed a statistical significant correlation with the length of AAA in the previous linear regression model.
Table 13. in the annexes shows that only the width of AAA has a statistical significant relation with the length of AAA. Both the diagnosis of hypertension and angina pectoris are not statistical significant but interestingly both show a negative correlation with the length of AAA, therefore those patients in our sample who were diagnosed with either hypertension or angina pectoris showed on average smaller values for the length of AAA than patients without those diagnoses.
7. Linear regression analysis of the distance of AAA to the lower renal artery using only three variables
Estimates the influence of the diagnosis of hypertension and angina pectoris as well as the length of AAA (independent variables) on the distance of AAA to the lower renal artery (dependent variable).
The linear regression analysis shows that only the length of AAA has a statistical significant relation with the distance of AAA to the lower renal artery. Both the diagnosis of
hypertension and angina pectoris are not statistical significant. This time all variables have negative correlation with the distance of AAA to the lower renal artery, therefore those patients in our sample who were diagnosed with either hypertension or angina pectoris or an increased length of AAA showed on average smaller values for the distance of AAA to the lower renal artery than patients without those diagnoses.
8. Linear regression analysis of the distance of AAA to the aortic bifurcation using only three variables
Estimates the influence of the diagnosis of hypertension and angina pectoris as well as the length of AAA (independent variables) on the distance of AAA to the aortic bifurcation (dependent variable).
Lastly the linear regression analysis in Table 17. in the annexes shows that only the length of AAA has a statistical significant relation with the distance of AAA to the aortic bifurcation. Therefore if the length of AAA increases by 1cm the distance of AAA to the aortic
bifurcation would decrease by 0,2cm. Both the diagnosis of hypertension and angina pectoris are not statistical significant.
DISCUSSION OF THE RESULTS
As a consequence of the sample size (46 observations) the conclusions drawn from this work cannot be implemented on the whole population.
Previous studies have been conducted focusing on both the risk factors and growth of AAA by using high-resolution spiral computed tomography as a measurement device in most cases [26-27].
During the research I quickly developed a special interest in unchangeable risk factors, in our case age and gender, and how they affect the length and width of AAA and therefore closely looked at their correlation. Multiple studies have been made concerning the effect of these risk factors on AAA development before with very similar results as my research.
Female gender always had a negative effect on AAA length and width during our research, thus making female AAA shorter and narrower than compared to the male patient group. The distance of AAA to the aortic bifurcation was also smaller in women than in men. Only the distance of AAA to the lower renal artery was larger in women than in men, which can probably be attributed to the overall smaller size of AAA in women thus occupying a smaller amount of the infrarenal abdominal aorta and increasing the distance to the lower renal artery. Unfortunately due to the small number of females (7 observations) taking part in this
research, the results cannot be extrapolated from our patient group to the general population as the statistical power and reproducibility are too low and the false discovery rate is thus inflated. Many studies and the general knowledge regarding size differences between female and male AAA reflect the research outcome of this thesis [1][9].
One of the main objectives of this research was to assess the effect of multiple clinical
diagnoses on AAA size. First we had to decide which diagnoses we include in the research to only include comorbidities that affect or are affected by AAA size. It was impractical to evaluate every single comorbidity independently, due to the resulting amount of different small sample size groups. Thus we decided to assemble all comorbidities affecting AAA size together and analyse them as one group. Ironically the results of the research showed that the more comorbidities a patient had, the smaller the AAA would be. This outcome opposes most studies as a few comorbidities included in this research (like hypertension and atherosclerosis)
positive fashion by increasing the size of AAA [1][10][11]. The small size of observations might be the source of the unusual result. A follow up research testing a larger patient group in which all comorbidities that are used in this work are analyse independently can help to evaluate whether this odd result was a false discovery or whether any of the comorbidities might really have a reducing effect on the size of AAA. It’s important to point out that the influence of the number of diagnosis on the size and location of infrarenal AAA is not statistically significant and therefore is of little significance to our study.
During the linear regression analysis the width of AAA showed a statistical significant effect on the length of AAA yet the width of AAA is less of a predictor of AAA size and location than the length of AAA, which throughout the linear regression analysis showed the most statistical significant results as its P-value was always <0,05. This demonstrates that the length of AAA is a very good tool to use in evaluation of AAA size and location
characteristics.
To improve the linear regression model thus making it more accurate we decreased the number of variables by only using the two diagnosis that were present the most frequently in our patient group and the length of AAA that had proven to be statistically significant in most previous linear regression models. By doing so the results of the new linear regression
analysis are more meaningful since every predictor variable will approximately have 10 to 15 observations. Hypertension was proven to have a statistical significant effect (P-Value: 0,047) on the width of AAA. If the patient is diagnosed with hypertension, the width of AAA is increased by 0,67cm. Previous studies have shown that hypertension is positively associated with AAA presence, thus supporting our research outcome [28][29].
The main drawback of this study was the overall small sample size and the low number of females in our research group. By increasing the sample size this problem can easily be resolved. A larger sample size would have also allowed us to analyse each comorbidity separately and in more detail, which could have produced interesting new findings.
Plenty of variables included in our study have shown values that resemble those in other studies (except the total number of diagnoses), but didn’t generate a statistical significance. Increasing the total sample size will not only result in more significant results, but will also allow the development of more complex models, in which a less strict preselection of independent variables can be applied.
CONCLUSIONS
1. Female gender always had a negative effect on AAA length and width during our research, thus making female AAA shorter and narrower than compared to the male patient group.
2. The length of AAA was the most statistical significant variable since the P-value was always <0,05 and therefore has the qualities of being a good tool to use in evaluation of AAA size and location characteristics.
3. The linear regression analysis showed that the diagnosis of hypertension has a statistical significant effect on the width of AAA by increasing its size.
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ANNEXES
No. 1
No. 2
Linear regression statistics and linear regression analysis results:
Linear Regression Model No. 1
1. Linear regression analysis of the width of AAA Table 2. Regressions-Statistics for width of AAA
Regressions-Statistic
Coefficient of determination 0,428
Adjusted coefficient of determination 0,372
Observations 46
Table 3. Linear regression analysis of the width of AAA
Coefficients Standard Error P-Value
Intercept 0,651 1,424 0,65
Gender 0,361 0,406 0,379
Age 0,029 0,018 0,107
Number of Diagnoses -0,017 0,165 0,919
Length of AAA 0,28 0,055 7,829E-06
2. Linear regression analysis of the length of AAA Table 4. Regressions-Statistics for length of AAA
Regressions-Statistic
Coefficient of determination 0,423
Adjusted coefficient of determination 0,367
Observations 46
Table 5. Linear regression analysis of the length of AAA
Coefficients Standard Error P-Value
Intercept 5,729 3,056 0,068
Gender 0,232 0,912 0,801
Age -0,066 0,039 0,101
Number of Diagnoses -0,172 0,366 0,641
Width of AAA 1,391 0,272 7,829E-06
3. Linear regression analysis of the distance of AAA to the lower renal artery Table 6. Regressions-Statistics for the distance of AAA to the lower renal artery
Regressions-Statistic
Coefficient of determination 0,355
Adjusted coefficient of determination 0,274
Table 7. Linear regression analysis of the distance of AAA to the lower renal artery
Coefficients Standard Error P-Value
Intercept 7,996 1,967 2,179E-04 Gender -0,345 0,564 0,544 Age -0,028 0,025 0,268 Number of Diagnoses -0,071 0,227 0,755 Length of AAA -0,414 0,096 1,096E-04 Width of AAA 0,323 0,215 0,14
4. Linear regression analysis of the distance of AAA to the aortic bifurcation Table 8. Regressions-Statistics for the distance of AAA to the aortic bifurcation
Regressions-Statistic
Coefficient of determination 0,275
Adjusted coefficient of determination 0,184
Observations 46
Table 9. Linear regression analysis of the distance of AAA to the aortic bifurcation
Coefficients Standard Error P-Value
Intercept 2,566 1,627 0,123 Gender 0,1453 0,467 0,757 Age -0,021 0,021 0,326 Number of Diagnoses 0,139 0,188 0,463 Length of AAA -0,293 0,08 7,053E-04 Width of AAA 0,305 0,178 0,094
Linear Regression Model No. 2
5. Linear regression analysis of the width of AAA using only three variables Table 10. Regressions-Statistics for width of AAA
Regressions-Statistic
Coefficient of determination 0,434
Adjusted coefficient of determination 0,393
Observations 46
Table 11. Linear regression analysis of the width of AAA
Coefficient Standard Error P-Value
Intercept 2,755 0,499 1,945E-06
Length of AAA 0,283 0,052 2,921E-06
Hypertension 0,669 0,326 0,047
6. Linear regression analysis of the length of AAA using only three variables Table 12. Regressions-Statistics for length of AAA
Regressions-Statistic
Coefficient of determination 0,412
Adjusted coefficient of determination 0,37
Observations 46
Table 13. Linear regression analysis of the length of AAA
Coefficient Standard Error P-Value
Intercept 1,089 1,473 0,464
Width of AAA 1,447 0,268 2,921E-06
Hypertension -1,182 0,752 0,123
Angina Pectoris -0,215 0,738 0,771
7. Linear regression analysis of the distance of AAA to the lower renal artery using only three variables
Table 14. Regressions-Statistics for the distance of AAA to the lower renal artery
Regressions-Statistic
Coefficient of determination 0,304
Adjusted coefficient of determination 0,255
Observations 46
Table 15. Linear regression analysis of the distance of AAA to the lower renal artery
Coefficient Standard Error P-Value
Intercept 6,599 0,708 8,973E-12
Length of AAA -0,319 0,074 1,054E-04
Hypertension -0,137 0,463 0,769
Angina Pectoris -0,101 0,462 0,827
8. Linear regression analysis of the distance of AAA to the aortic bifurcation using only three variables
Table 16. Regressions-Statistics for the distance of AAA to the aortic bifurcation
Regressions-Statistic
Coefficient of determination 0,26
Adjusted coefficient of determination 0,207
Observations 46
Table 17. Linear regression analysis of the distance of AAA to the aortic bifurcation
Coefficient Standard Error P-Value
Intercept 1,888 0,570 0,002
Length of AAA -0,199 0,06 0,002
Hypertension 0,573 0,372 0,132
