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\begin{document}

\title{Socioeconomic Disparities in Surveillance and Follow-Up of Patients with
Thoracic Aortic Aneurysm}



\author[1]{Michael Shang}%
\author[1]{Gabe Weininger}%
\author[2]{Makoto Mori}%
\author[1]{Arianna Kahler-Quesada}%
\author[2]{Ellelan Degife}%
\author[1]{Cornell Brooks}%
\author[2]{Matthew Williams}%
\author[2]{Roland Assi}%
\author[2]{Arnar Geirsson}%
\author[1]{Prashanth Vallabhajosyula}%
\affil[1]{Yale School of Medicine}%
\affil[2]{Yale University School of Medicine}%


\vspace{-1em}



  
  \date{May 29, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
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\selectlanguage{english}
\begin{abstract}
Background: Thoracic aortic aneurysm is a significant risk factor for
aortic dissection and rupture. Guidelines recommend referral of patients
to a cardiovascular specialist for periodic surveillance imaging with
surgical intervention determined primarily by aneurysm size. We
investigated the association between socioeconomic status and
surveillance practices in patients with ascending aortic aneurysms.
Methods: We retrospectively reviewed records of 465 consecutive patients
diagnosed between 2013-2016 with ascending aortic aneurysm [?]4cm on
computed tomography scans. Primary outcomes were clinical follow-up with
a cardiovascular specialist and aortic surveillance imaging within 2
years following index scan. We stratified patients into quartiles using
the area deprivation index (ADI), a validated percentile measure of 17
variables characterizing socioeconomic status at the census block group
level. Competing risks analysis was used to determine interquartile
differences in risk of death prior to follow up with a cardiovascular
specialist. Results: Lower socioeconomic status was associated with
significantly lower rates of surveillance imaging and referral to a
cardiovascular specialist. On competing risks regression, the ADI
quartile with lowest socioeconomic status had lower hazard of follow-up
with a cardiologist or cardiac surgeon prior to death (HR 0.46 {[}0.34,
0.62{]}, p\textless{}0.001). Though there were no differences in
aneurysm size at time of surgical repair, patients in the lowest
socioeconomic quartile were more frequently symptomatic at surgery than
other quartiles (92\% vs 23-38\%, p\textless{}0.001). Conclusion:
Patients with lower socioeconomic status receive less timely follow-up
imaging and specialist referral for thoracic aortic aneurysms, resulting
in surgical intervention only when alarming symptoms are already
present.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Thoracic aortic aneurysm (TAA) represents a significant healthcare
burden worldwide, with an estimated annual incidence of 5.3 per 100,000
persons/year, and is a significant risk factor for rupture, which has
over 90\% mortality.\textsuperscript{1-3} Increased understanding of the
natural history of TAA, with an average annual growth rate of 1mm/year,
has led to recommendations for surveillance imaging at regular intervals
to guide timing of surgical intervention.\textsuperscript{4, 5} However,
whether such periodic, guidelines-based clinical follow-up is
implemented in clinical practice across patients of different
sociodemographic strata remains unknown.

Several studies have demonstrated an association between cardiovascular
health disparities and socioeconomic
inequality.\textsuperscript{6-9}Within cardiac surgery, lower
socioeconomic status (SES) has been associated with greater mortality
and morbidity after valve surgery and coronary artery bypass grafting
(CABG).\textsuperscript{10, 11}

In patients with TAA, it has been observed that lower SES and lack of
health insurance is associated with greater acuity of presentation and
higher mortality after aortic events (dissection and
rupture).\textsuperscript{12} However, it is unknown how SES affects the
follow-up care and progression of TAAs prior to
this.\textsuperscript{12-14} Better characterizing this relationship may
provide important insights into how socioeconomic inequality ultimately
manifests as health outcome disparities for TAA patients. In the present
study, we utilized the area deprivation index (ADI) as a measure of SES,
which uses national census data to calculate a percentile measure of
socioeconomic deprivation within in each census-block
group.\textsuperscript{15} We sought to determine the influence of ADI
on whether patients receive appropriate surveillance follow-up after
diagnosis of ascending thoracic aortic aneurysm (ATAA).

\textbf{Patients and Methods}

\emph{Patient Identification}

We queried radiology reports from 21,336 chest computed tomography (CT)
scans performed at a single tertiary care hospital between 2013-2016 on
patients ages 50-85 for radiologic diagnosis of thoracic aortic
dilatation or thoracic aortic aneurysm. 620 patients were identified
with ascending thoracic aortic aneurysms (ATAA) whose records were
further reviewed.

\emph{Area Deprivation Index}

Area Deprivation Index (ADI) is a measure of SES, determined from 17
variables including income, education, employment, and housing quality
collected by the United States Census Bureau.\textsuperscript{15} By
assigning a national percentile to each residential address at the
Census Block level, ADI allows for quantification of SES on a scale of 1
to 100, where lower percentiles represent less deprivation (higher SES).
National ADI percentile was collected for each patient's home address
using the 2018 Neighborhood Atlas (University of Wisconsin School of
Medicine and Public Health).

\emph{Inclusion/Exclusion Criteria}

Of the 620 patients identified, we included 465 patients age [?]18 years
old with ascending aortic size [?]4 cm on chest CT, including 4 patients
with aortic dissection (2 acute, 2 chronic) on index scan. 18 patients
were excluded due to ADI information being unavailable. 41 patients were
excluded for residential address outside the state of Connecticut, due
to concern for incomplete follow-up information in our institutional
electronic medical record (EMR). 13 patients with only Post Office
(P.O.) Box address were excluded. We excluded 10 patients who were lost
to follow-up, defined as no listed encounters in the EMR within 4 years
after the index CT scan, and 73 patients with mortality occurring less
than 6 months after the index CT scan.

\emph{Demographics and Comorbidities}

Demographic information included age, sex, weight, height, and race
(White, Black, or other). Comorbidities at time of index CT scan
included hypertension, dyslipidemia, diabetes mellitus, congestive heart
failure, chronic kidney disease, myocardial infarction, liver disease,
chronic obstructive pulmonary disease (COPD), active malignancy
(thoracic vs extrathoracic), connective tissue disease, presence of
bicuspid aortic valve, and prior cardiac surgical intervention.

\emph{Clinical follow-up, surveillance imaging, and outcomes}

Follow-up care information was collected from the Yale-New Haven Health
EMR, which encompasses 5 acute care hospitals in academic and community
settings and over 120 outpatient clinics at satellite locations
throughout the state of Connecticut. In addition, we utilized
information from Care Everywhere (Natick, MA), which allows enrolled
patients to share visit notes and imaging reports from outside
healthcare institutions (in- and out-of-state) with our institutional
EMR.

We reviewed the EMR to determine if patients were presently being
followed for ATAA aneurysm by a cardiologist and/or cardiac surgeon, at
the time of index CT scan. In patients without pre-existing
relationships with these specialists, we recorded the dates of first
encounter for ATAA monitoring. In addition, we determined whether
patients received follow-up echocardiography and/or chest CT (with or
without contrast), as recommended by consensus guidelines, and for what
indication (aneurysm surveillance vs. unrelated) prior to 12 months and
24 months post-index scan.\textsuperscript{4} These time intervals were
chosen in light of evidence that annual surveillance imaging of
moderate-size ATAA (\textless{}5cm) may be
unwarranted.\textsuperscript{16} We also determined whether patients had
undergone surgical repair of their aneurysm during the study period, and
if so, the size of the ATAA and presence of related symptoms (chest/back
pain, dyspnea, dysphagia) at the time of surgical evaluation.

The date of the index CT scan was used as the initial time point for the
follow-up. Length of clinical follow-up was defined as time elapsed from
the date of index CT scan identifying ATAA to the date of first review
of the EMR (March 1, 2021) in living patients, or date of mortality in
deceased patients.

\emph{Statistical analysis}

We ranked patients by national ADI percentile, and divided them into 4
equal-sized quartiles, where the lowest quartile (Q1) represents least
socioeconomically deprived status, and highest quartile (Q4) represents
most deprived.\textsuperscript{10} To compare differences in
demographics and comorbidities between ADI quartiles, we used
Kruskal-Wallis rank sum test for continuous variables and Pearson
chi-squared test or Fisher's exact test for categorical variables, as
appropriate. Pairwise chi-squared test with nominal independence and
Bonferroni correction was used for between-group differences. Two-sided
Cochrane-Armitage test was used to compare occurrence of clinical and
imaging follow-up between ADI quartiles.

Bivariate and multivariate generalized logistic regression were used to
determine factors associated with occurrence of surveillance imaging (CT
chest or echocardiogram) at or before 24 months following index CT scan.
Variables with p-value \textless{}0.1 on bivariate analysis were
included in the multivariate model.

Competing risks analysis, as described by Fine et
al.,\textsuperscript{17, 18} was used to model the effect of ADI
quartile on time from index CT scan to first encounter with a
cardiologist or cardiac surgeon for ATAA aneurysm, with the competing
risk of death. Time to follow-up was defined as 0 for patients who were
already established with either of these specialties. This methodology
allows for visual representation of the subset of patients with
pre-established follow-up prior to index scan, in which new first-time
encounters do not apply. We performed competing risks regression
adjusted for ADI quartile, age, sex, race, and ATAA size on index scan,
factors which may influence a provider's decision to refer patients to a
cardiovascular specialist. We defined statistical significance
as\emph{p} \textless{}0.05. All data analysis was performed in R version
3.6.3 (R Foundation for Statistical Computing).

The Yale University Institutional Review Board approved this study and
individual consent was waived (IRB 2000027551). The study followed the
Strengthening the Reporting of Observational Studies in Epidemiology
(STROBE) reporting guidelines for cohort studies.

\textbf{Results}

\emph{Demographics, Comorbidities, and ADI}

Mean clinical follow-up was 5.1 \selectlanguage{ngerman}± 2.1 years (\textbf{Table 1} ) and
median ATAA size on index CT scan was 4.3 (4.1, 4.5) cm (\textbf{Table
2} ), and were similar between ADI quartiles. The mean age of the study
population was 69.6 ± 9.2 years old, with the most disadvantaged
quartile (Q4) being significantly younger (p=0.04). The majority of
patients were male (77.8\%), and there were no differences in the
proportions of sex between quartiles. Race was predominately White
(73.1\%) but Black race was more common in more disadvantaged quartiles
(p\textless{}0.001).

COPD was more prevalent in the most disadvantaged quartile (N=31, 27\%),
ranging from 13-16\% in the lower ADI quartiles (p=0.02). There were
also significant differences in presence of bicuspid aortic valve (BAV)
and mitral valve pathologies between quartiles, but without clear
directionality of these trends (p=0.03 and p=0.049, respectively). There
were no significant differences between quartiles for other
comorbidities obtained. Connective tissue disease was only present in 5
patients and was not included in statistical modeling.

\emph{Clinical Follow-Up}

There were significant interquartile differences in rates of clinical
follow-up (new or previously established) with a cardiologist or cardiac
surgeon following diagnosis of ATAA aneurysm (p\textless{}0.001 and
p=0.002, respectively), shown in \textbf{Figure 1} . Patients in the top
three quartiles (Q1-Q3) were significantly more likely to have
previously established follow-up with a cardiologist for their ATAA
aneurysm, compared to those in Q4 (p\textless{}0.001). In addition,
among those who were not already established with a cardiologist, rates
of new encounters were similar between Q1, Q2, and Q3, at 36.3\% (N=16),
46.3\% (N=25), and 29.8\% (N=17), respectively. However, only 16\%
(N=18) of previously unestablished patients in Q4 were seen by a
cardiologist during the study period (p\textless{}0.001).

23.4\% (N=109) of patients had previously established or new follow-up
with a cardiac surgeon during the study period. ADI quartile was also
significantly associated with follow-up with a cardiac surgeon
(p\textless{}0.002), with statistically significant differences between
the least disadvantage quartile (Q1) and most disadvantaged quartile
(Q4) on pairwise testing (Q1: 33\% vs. Q4: 16\%).

47 (10.1\%) patients underwent aortic repair surgery during the study
period, at an average ATAA size of 5.0 (4.6, 5.2) cm (\textbf{Table 2}
). There were no significant interquartile differences in ATAA size at
time of surgery, but 92\% (N=12) of patients in the most disadvantaged
quartile were symptomatic at presentation for surgery, compared to only
25\% (N=3) patients in the least disadvantage quartile
(p\textless{}0.001).

\emph{Imaging Follow-Up}

313 (67.3\%) and 374 (80.4\%) patients received at least one
echocardiogram or chest CT within 12- and 24-months post-index scan,
respectively (\textbf{Table 2} ). Only 124 (33.2\%) of patients imaged
before 24 months were done so for thoracic aneurysm-related indications.
Less disadvantaged quartiles were more likely to receive imaging at 24
months compared to the most disadvantaged quartile (Q2: 88\% vs Q4:
71\%, p\textless{}0.001). Conversely, active malignancy (4.12 {[}2.37,
7.57{]}, p\textless{}0.001) and COPD (2.47 {[}1.21, 5.75{]}, p=0.011)
were associated with increased odds of imaging (\textbf{Table 3} ). The
trend for more disadvantaged quartiles being less likely to receive
follow-up imaging persisted even after adjusting for family history of
TAA, active malignancy, prior smoking history, congestive heart failure,
and COPD on multivariate analysis (p=0.006 for Q4), \textbf{Table 3} .

\emph{Competing Risks Model}

Among the 224 patients without previously established follow-up,
follow-up with a cardiologist or cardiac surgeon occurred in 68 patients
with a median time-to-event of 0.62 (0.13, 1.94) years (\textbf{Figure
2} ). The competing event of death occurred in 60 patients with a median
time-to-death of 1.76 (0.95, 3.02) years. In the least disadvantaged
quartile (Q1), 11 patients reached the competing event of death in the
study period with a median time-to-event of 1.91 (1.49, 3.08) years. In
the most disadvantaged quartile (Q4), 26 patients reached the competing
event of death with a median time-to-event of 1.5 (0.95, 2.29) years. On
competing risks regression adjusted for age, ATAA size at index scan,
active malignancy, sex, and race, only the most disadvantaged quartile
was significantly less likely to receive follow-up prior to death (HR
0.46 {[}0.34, 0.62{]}, p\textless{}0.001), compared to the least
disadvantaged quartile (\textbf{Table 4} ).

\textbf{Comment}

In this retrospective study of patients diagnosed with ATAA, we found
that patients with lower socioeconomic status had lower rates of
follow-up with a cardiovascular specialist and were less likely to
receive timely follow-up imaging. In turn, these patients suffered worse
outcomes in that they were more likely to present with symptoms at time
of aortic surgery or die before ever being followed up. To date, there
have been no studies that we know of examining the influence of SES on
thoracic aortic aneurysm surveillance.

The majority of patients in our cohort had moderate-sized aneurysms
(\textless{}5cm) without other significant risk factors (i.e. genetic
syndromes), a population in which the appropriate interval for
surveillance imaging is currently debated.\textsuperscript{16, 19,
20}The 2010 ACCF/AHA Task Force guidelines recommend all patients with
TAA be managed by a cardiologist or cardiac surgeon; however, they leave
the imaging interval to the discretion of the
provider.\textsuperscript{4}While annual CT scan is reasonable after
initial aneurysm detection or in genetically predisposed patients with
stable ATAA size, we expect that intervals will be longer for those
without associated risk factors. For this reason, we used a conservative
interval of 2 years from last CT scan to evaluate whether patients were
receiving regular surveillance with CT or echocardiography. We observed
that patients in the ADI quartile with lowest SES were less likely to
receive surveillance imaging for ATAA aneurysm within 2 years of last CT
scan, even after adjusting for common comorbidities that warrant
thoracic imaging. While we are unable to establish a causal
relationship, the observed difference in successful referral to a
cardiovascular specialist indicates the need for improved systems for
establishing longitudinal follow-up in individuals with decreased access
to care.

Several studies have linked lower patient socioeconomic status with
disparities in cardiovascular healthcare.\textsuperscript{6, 21,
22}While our study lacks information about previously employed measures
of SES, such as insurance status and income level, the use of ADI in
health outcomes research is growing as it provides a more comprehensive
measure of disadvantaged status while offering greater granularity than
estimates based on zip code alone. Within cardiac surgery, a study by
Patrick et al. utilized ADI to show that lower SES is associated with
receipt of fewer arterial conduits during CABG, resulting in worse
long-term survival.\textsuperscript{10} Lower income patients with
coronary artery disease also face significant financial barriers to
accessing routine care, such as medical checkups, Hgb A1c and lipid
measurement, and antihypertensive treatment.\textsuperscript{23} This is
particularly important for patients with TAA as a higher incidence of
TAAs has been observed in more socioeconomically deprived individuals,
perhaps due to the greater prevalence of uncontrolled hypertension which
is a known risk factor for adverse outcomes in TAA.\textsuperscript{20,
24} Prior to this, the understanding of how socioeconomic barriers
impact outcomes in patients with TAA was limited to only to survival
after aortic dissection.\textsuperscript{13, 14} This catastrophic
outcome is avoidable with periodic monitoring and elective intervention.

Several previous studies have observed Black patients to experience
poorer cardiovascular healthcare and outcomes.\textsuperscript{25-27}The
low number of non-white patients in our sample made it difficult to
evaluate differences in care associated with race. The lack of
statistically significant association between surveillance care and race
may be due to the collinearity between ADI and race, with ADI being a
variable accounting for a larger variation in the care.

Ultimately, in our study, patients of lower SES experienced inadequate
aneurysm surveillance and follow-up and greater likelihood of presenting
for surgery with symptoms. This finding is supported by another recent
study of 51,282 patients from the Society for Thoracic Surgeons (STS)
Database, which found that both uninsured as well as Medicaid patients
were significantly more likely to undergo nonelective thoracic aortic
operation than privately insured patients (RR 1.77 {[}1.70-1.83{]} and
1.18 {[}1.10-1.26{]}, respectively).\textsuperscript{12} Though our
study lacks data on cause of mortality, the worrisome observation that
92\% of patients in the lowest SES quartile (Q4) presented with symptoms
is concerning for the subset of patients who may have died from aneurysm
complications before having a chance to be seen.

Healthcare institutions must be proactive in engaging marginalized
populations via interventions targeted at both patients and providers.
This may take the form of automatically generated alerts to ordering
providers when radiographic scans detect aneurysms above a certain size.
In addition, public health initiatives should expand outreach to
marginalized communities with education regarding the significant
mortality associated with TAAs and the treatable nature of the disease.

\emph{Limitations}

The present study is limited by its retrospective nature and that
follow-up information was limited to data from a single healthcare
network. As a result, it is possible that some patients were followed by
cardiovascular specialists at outside institutions. We attempted to fill
this gap using an automated inter-organization records exchange software
(Care Everywhere), though we recognize that this is only available for
patients who opt in. Furthermore, we did not assess whether patients
were referred to a cardiologist or cardiac surgeon and were not seen. We
did not include patient insurance status in our analysis, which would
influence whether is patient is able to afford specialty care and
imaging at regular intervals, regardless of income/SES. Lastly, cause of
mortality is not reliably reported for patients dying outside the
hospital setting, making it difficult to determine whether lack of
surveillance resulted in increased mortality due to aortic-related
events.

\emph{Conclusion}

Lower SES among ATAA patients is associated with decreased surveillance
imaging, decreased follow-up with cardiovascular specialists, and
greater odds of symptomatic presentation for aortic repair. Patients may
benefit from systematic approaches to identify when inadequate aneurysm
monitoring is occurring in order to improve the existing disparities in
outcome.

\emph{Acknowledgements}

The authors thank the Joint Data Analytics Team (JDAT) at Yale
University for their assistance in obtaining the data for this study.

\emph{Disclosures}

The authors have no disclosures to report.

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disparities in outcomes after cardiac surgery: the role of hospital
quality. \emph{JAMA Surg} . 2014;149:223-7.

27. Rumsfeld, J.S., M.E. Plomondon, E.D. Peterson, et al. The impact of
ethnicity on outcomes following coronary artery bypass graft surgery in
the Veterans Health Administration. \emph{J Am Coll Cardiol} .
2002;40:1786-93.

\emph{Tables}

\textbf{Table 1: Patient demographics and comorbidities by ADI quartile}\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
& \textbf{ADI Quartile (1=least disadvantaged)} & \textbf{ADI Quartile
(1=least disadvantaged)} & \textbf{ADI Quartile (1=least disadvantaged)}
& \textbf{ADI Quartile (1=least disadvantaged)} & \textbf{ADI Quartile
(1=least disadvantaged)}\tabularnewline
\midrule
\endhead
\textbf{Characteristic} & \textbf{1}, N = 117 & \textbf{2}, N = 116 &
\textbf{3}, N = 116 & \textbf{4}, N = 116 &
\textbf{p-value}\tabularnewline
\textbf{ADI (national percentile)} & 13 (6) & 25 (5) & 39 (7) & 61 (12)
& \textbf{\textless{}0.001}\tabularnewline
\textbf{Clinical follow-up (years)} & 5.14 (2.12) & 4.88 (2.03) & 5.13
(2.11) & 5.06 (2.26) & 0.4\tabularnewline
\textbf{Age (years)} & 71 (8) & 69 (9) & 71 (9) & 68 (10) &
\textbf{0.017}\tabularnewline
\textbf{Sex} & & & & & \textbf{0.039}\tabularnewline
Female & 24 (21\%) & 17 (15\%) & 27 (23\%) & 35 (30\%) &\tabularnewline
Male & 93 (79\%) & 99 (85\%) & 89 (77\%) & 81 (70\%) &\tabularnewline
\textbf{Race} & & & & & \textbf{\textless{}0.001}\tabularnewline
Black & 1 (0.9\%) & 5 (4.4\%) & 7 (6.1\%) & 25 (22\%) &\tabularnewline
Other & 21 (18\%) & 14 (12\%) & 19 (17\%) & 24 (21\%) &\tabularnewline
White & 93 (81\%) & 94 (83\%) & 88 (77\%) & 65 (57\%) &\tabularnewline
\textbf{Smoking} & 38 (32\%) & 55 (47\%) & 51 (44\%) & 54 (47\%) &
0.077\tabularnewline
\textbf{Hypertension} & 78 (67\%) & 85 (73\%) & 84 (72\%) & 91 (78\%) &
0.3\tabularnewline
\textbf{Diabetes Mellitus} & 18 (15\%) & 22 (19\%) & 22 (19\%) & 33
(28\%) & 0.081\tabularnewline
\textbf{Chronic Heart Failure} & 13 (11\%) & 11 (9.5\%) & 15 (13\%) & 16
(14\%) & 0.7\tabularnewline
\textbf{Chronic Kidney Disease} & 14 (12\%) & 12 (10\%) & 8 (6.9\%) & 14
(12\%) & 0.5\tabularnewline
\textbf{Connective Tissue Disease} & 2 (1.7\%) & 2 (1.7\%) & 0 (0\%) & 1
(0.9\%) & 0.6\tabularnewline
\textbf{Myocardial Infarction} & 6 (5.1\%) & 11 (9.5\%) & 9 (7.8\%) & 6
(5.2\%) & 0.5\tabularnewline
\textbf{Bicuspid Aortic Valve} & 4 (3.4\%) & 13 (11\%) & 16 (14\%) & 8
(6.9\%) & \textbf{0.027}\tabularnewline
\textbf{Aortic Valve Disorder} & 17 (15\%) & 13 (11\%) & 14 (12\%) & 10
(8.6\%) & 0.6\tabularnewline
\textbf{Mitral Valve Disorder} & 12 (10\%) & 3 (2.6\%) & 7 (6.0\%) & 4
(3.4\%) & \textbf{0.049}\tabularnewline
\textbf{Liver Disease} & 4 (3.4\%) & 4 (3.4\%) & 11 (9.5\%) & 10 (8.6\%)
& 0.1\tabularnewline
\textbf{COPD} & 15 (13\%) & 15 (13\%) & 19 (16\%) & 31 (27\%) &
\textbf{0.015}\tabularnewline
\textbf{Dyslipidemia} & 59 (50\%) & 63 (54\%) & 52 (45\%) & 52 (45\%) &
0.4\tabularnewline
\textbf{Active Malignancy} & & & & & \textgreater{}0.9\tabularnewline
Thoracic & 15 (13\%) & 18 (16\%) & 17 (15\%) & 17 (15\%)
&\tabularnewline
Extra-Thoracic & 35 (30\%) & 30 (26\%) & 28 (24\%) & 31 (27\%)
&\tabularnewline
\textbf{Prior cardiac surgery} & 20 (17\%) & 13 (11\%) & 17 (15\%) & 14
(12\%) & 0.6\tabularnewline
\textbf{FH of aneurysm} & 5 (4.3\%) & 7 (6.0\%) & 2 (1.7\%) & 2 (1.7\%)
& 0.2\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 1 Legend:} Categorical variables are expressed as N (\%)
and continuous variables are expressed as mean (standard deviation).
Increasing ADI corresponds with increasing socioeconomic deprivation.

ADI: area deprivation index, COPD: chronic obstructive pulmonary
disorder, FH: family history\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
& \textbf{ADI Quartile (1=least disadvantaged)} & \textbf{ADI Quartile
(1=least disadvantaged)} & \textbf{ADI Quartile (1=least disadvantaged)}
& \textbf{ADI Quartile (1=least disadvantaged)} & \textbf{ADI Quartile
(1=least disadvantaged)}\tabularnewline
\midrule
\endhead
\textbf{Characteristic} & \textbf{1}, N = 117 & \textbf{2}, N = 116 &
\textbf{3}, N = 116 & \textbf{4}, N = 116 &
\textbf{p-value}\tabularnewline
\textbf{Indication for index scan} & & & & & 0.11\tabularnewline
Aneurysm-related & 32 (27\%) & 23 (20\%) & 33 (28\%) & 20 (17\%)
&\tabularnewline
Unrelated/Incidental & 85 (73\%) & 93 (80\%) & 83 (72\%) & 96 (83\%)
&\tabularnewline
\textbf{ATAA size (cm)} & 4.30 (4.20,4.60) & 4.30 (4.20,4.50) & 4.30
(4.10,4.50) & 4.25 (4.10,4.40) & 0.2\tabularnewline
\textbf{Cardiology follow-up} & 89 (76\%)\textsuperscript{4} & 87
(75\%)\textsuperscript{4} & 76 (66\%)\textsuperscript{4} & 45 (39\%) &
\textbf{\textless{}0.001}\tabularnewline
Previously established & 73 (62.4\%)\textsuperscript{4} & 62
(53.4\%)\textsuperscript{4} & 59 (50.9\%)\textsuperscript{4} & 35
(30.2\%) & \textbf{\textless{}0.001}\tabularnewline
New\textsuperscript{a} & 16 (36.3\%)\textsuperscript{4} & 25
(46.3\%)\textsuperscript{4} & 17 (29.8\%) & 10 (12.3\%) &
\textbf{\textless{}0.001}\tabularnewline
\textbf{Cardiac Surgery follow-up} & 39 (33\%)\textsuperscript{4} & 27
(23\%) & 25 (22\%) & 18 (16\%) & \textbf{0.002}\tabularnewline
\textbf{Imaging at 12 months (any indication)} & 88
(75\%)\textsuperscript{4} & 86 (74\%) & 72 (62\%) & 67 (58\%) &
\textbf{\textless{}0.001}\tabularnewline
Aneurysm-related & 36 (41\%) & 18 (21\%) & 20 (28\%) & 13 (19\%)
&\tabularnewline
Unrelated/Incidental & 52 (59\%) & 68 (79\%) & 52 (72\%) & 54 (81\%)
&\tabularnewline
\textbf{Imaging at 24 months (any indication)} & 99 (85\%) & 102
(88\%)\textsuperscript{4} & 91 (78\%) & 82 (71\%) &
\textbf{0.002}\tabularnewline
Aneurysm-related & 45 (45\%) & 29 (28\%) & 31 (34\%) & 19 (23\%)
&\tabularnewline
Unrelated/Incidental & 54 (55\%) & 73 (72\%) & 60 (66\%) & 63 (77\%)
&\tabularnewline
\textbf{Aortic Repair Surgery} & 13 (11\%) & 13 (11\%) & 8 (6.9\%) & 13
(11\%) & 0.75\tabularnewline
\textbf{ATAA size at surgery} & 4.90 (4.50,5.00) & 5.00 (4.60,5.20) &
4.85 (4.70,5.05) & 5.00 (4.70,5.10) & 0.94\tabularnewline
\textbf{Symptomatic at surgery} & 3 (23\%)\textsuperscript{4} & 3
(23\%)\textsuperscript{4} & 3 (38\%)\textsuperscript{4} & 12 (92\%) &
\textbf{\textless{}0.001}\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 2: Aneurysm characteristics and follow up outcomes by ADI
Quartile}

\textbf{Table 2 Legend:} Categorical variables are expressed as N (\%)
and continuous variables are expressed as median (interquartile range).
Increasing ADI corresponds with increasing socioeconomic deprivation.
Superscript numbers represent which quartiles were significantly
different on post-hoc pairwise testing. Symptoms at surgery is defined
as presence of chest/back pain, shortness of breath, or dysphagia at
time of surgical repair of the aorta. Aneurysm-related and
unrelated/incidental describe whether the imaging was performed
specifically for aneurysm surveillance or for a separate indication.

ADI: area deprivation index, ATAA: ascending thoracic aortic aneurysm

a. proportion among patients who were not previously established
(without prior appointments)

4. Statistically significant difference compared to Q4 on pair-wise
testing.

\textbf{Table 3: Univariate and multivariate analyses of factors
associated with surveillance imaging prior to 24 months.}\selectlanguage{english}
\begin{longtable}[]{@{}lllllllll@{}}
\toprule
& Univariate & Univariate & Univariate & & Multivariate & Multivariate &
Multivariate & Multivariate\tabularnewline
\midrule
\endhead
\textbf{Characteristic} & \textbf{OR} & \textbf{95\% CI} &
\textbf{p-value} & & \textbf{OR} & \textbf{OR} & \textbf{95\% CI} &
\textbf{p-value}\tabularnewline
\textbf{ADI (quartile)} & & & & & & & &\tabularnewline
2 & 1.32 & 0.63, 2.85 & 0.46 & & 1.25 & 1.25 & 0.58, 2.76 &
0.57\tabularnewline
3 & 0.66 & 0.33, 1.29 & 0.23 & & 0.62 & 0.62 & 0.31, 1.25 &
0.18\tabularnewline
4 & 0.44 & 0.23, 0.82 & \textbf{0.012} & & 0.38 & 0.38 & 0.19, 0.76 &
\textbf{0.006}\tabularnewline
\textbf{Sex (male)} & 0.64 & 0.34, 1.14 & 0.14 & & & & &\tabularnewline
\textbf{Age (years)} & 1.02 & 1.00, 1.05 & \textbf{0.093} & & 1.01 &
1.01 & 0.99, 1.04 & 0.29\tabularnewline
\textbf{Race} & & & 0.2 & & & & &\tabularnewline
Black & --- & --- & & & & & &\tabularnewline
Other & 0.39 & 0.11, 1.15 & & & & & &\tabularnewline
White & 0.47 & 0.14, 1.23 & & & & & &\tabularnewline
\textbf{ATAA Size (cm)} & 1.12 & 0.58, 2.33 & 0.7 & & & &
&\tabularnewline
\textbf{Family History of TAA} & 3.76 & 0.75, 68.4 & 0.12 & & & &
&\tabularnewline
\textbf{Malignancy} & 4.12 & 2.37, 7.57 & \textbf{\textless{}0.001} & &
4.24 & 4.24 & 2.39, 7.94 & \textbf{\textless{}0.001}\tabularnewline
\textbf{Smoking History} & 1.47 & 0.92, 2.39 & 0.11 & & 0.97 & 0.97 &
0.57, 1.66 & 0.90\tabularnewline
\textbf{Aortic Valve Disorder} & 1.25 & 0.61, 2.82 & 0.6 & & & &
&\tabularnewline
\textbf{Mitral Valve Disorder} & 1.02 & 0.40, 3.13 & \textgreater{}0.9 &
& & & &\tabularnewline
\textbf{Hypertension} & 0.88 & 0.51, 1.46 & 0.6 & & & & &\tabularnewline
\textbf{Diabetes Mellitus} & 1.26 & 0.71, 2.34 & 0.4 & & & &
&\tabularnewline
\textbf{Congestive Heart Failure} & 1.77 & 0.82, 4.40 & 0.2 & & & &
&\tabularnewline
\textbf{COPD} & 2.47 & 1.21, 5.75 & \textbf{0.01} & \textbf{0.01} & &
2.87 & 1.29, 7.10 & \textbf{0.014}\tabularnewline
\textbf{Chronic Kidney Disease} & 1.48 & 0.68, 3.71 & 0.3 & 0.3 & & &
&\tabularnewline
\textbf{Bicuspid Aortic Valve} & 0.85 & 0.41, 1.96 & 0.7 & & & &
&\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 3 Legend:} Surveillance imaging status was defined as
having at least one echocardiogram or CT chest scan within 24 months
post-index scan. We used a permissive p-value [?]0.10 for inclusion in the
multivariate analysis. We also included smoking history in the
multivariate analysis as this a common indication for CT chest imaging.

ADI: area deprivation index, ATAA: ascending thoracic aortic aneurysm,
TAA: thoracic aortic aneurysm, COPD: chronic obstructive pulmonary
disease, CI: confidence interval



\textbf{Table 4: Adjusted competing risks regression of follow-up with a
cardiovascular specialist versus death after index CT scan}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\textbf{Variable} & \textbf{OR} & \textbf{95\% CI} &
\textbf{P-value}\tabularnewline
\midrule
\endhead
\textbf{ADI Quartile} & & &\tabularnewline
1 & - & - & -\tabularnewline
2 & 0.977 & 0.8, 1.19 & 0.82\tabularnewline
3 & 0.834 & 0.67, 1.03 & 0.095\tabularnewline
4 & 0.462 & 0.34, 0.62 & \textbf{\textless{}0.001}\tabularnewline
\textbf{Age (years)} & 1 & 0.99, 1.01 & 0.6\tabularnewline
\textbf{AAo Size (cm)} & 1.65 & 1.35, 2.01 &
\textbf{\textless{}0.001}\tabularnewline
\textbf{Active Malignancy} & 0.67 & 0.55, 0.80 &
\textbf{\textless{}0.001}\tabularnewline
\textbf{Sex (female)} & 1.02 & 0.82, 1.27 & 0.85\tabularnewline
\textbf{Race} & & &\tabularnewline
White & - & - & -\tabularnewline
Black & 0.9 & 0.61, 1.34 & 0.6\tabularnewline
Other & 0.9 & 0.71, 1.14 & 0.38\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 4 Legend:} Competing risks regression adjusted for ADI
quartile and clinical and demographic factors that would influence the
decision to refer patients to a cardiologist and/or cardiac surgeon.
Lowest socioeconomic quartile (Quartile 4), ascending aortic size, and
active malignancy were identified as independent predictors of death
prior to clinical follow-up.

OR: odds ratio, CI: confidence interval, ADI: area deprivation index,
AAo: ascending aorta

\emph{Figure Legends}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1: Cardiology and cardiac surgery follow-up status after
index scan.} Follow-up status is defined as having completed a
consultation appointment with either a cardiologist or cardiac surgeon,
specifically for aneurysm monitoring, at any date after the index
computed tomography scan identifying ascending thoracic aortic aneurysm.
Those with records of having attended an appointment with either
specialty in the past for aneurysm monitoring were included in a
separate category (`Previously established'). Increasing ADI quartile
corresponds with increasing socioeconomic deprivation. Percentages
represent proportion of patients within each category by quartile.

ADI: area deprivation index\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 2: Cumulative incidence function of follow-up versus
death for each ADI Quartile.} Generated from unadjusted competing risks
analysis of time-to-follow-up with a cardiologist or cardiac surgeon
following index scan identifying ATAA (solid line) against the competing
risk of death before follow-up (dotted line). Patients who already had
previously established follow-up were included with a time-to-follow-up
of 0. The third and fourth ADI quartiles had significantly greater
hazard of death before follow-up compared to the first ADI quartile.

ADI: area deprivation index, ATAA: ascending thoracic aortic aneurysm

\selectlanguage{english}
\FloatBarrier
\end{document}

