Patients and Methods
Institutional review board approval was obtained prior to undertaking
this study. All percutaneous transfemoral TAVR cases performed at the
North Florida/South Georgia Veterans Affairs Medical Center (NF/SG VAMC)
from January 2014 to December 2019 were retrospectively reviewed. TAVR
patients were identified through a query of the local Veterans Affairs
Surgery Quality Improvement Program (VASQIP) database, which contains
baseline patient characteristics and clinical outcomes data for every
cardiac surgical procedure performed. Valve-in-valve procedures and
cases with missing cost data were excluded. The valve types changed with
the evolving technology. The Edwards Sapien and Sapien XT valves used
primarily between 2014-2015, and Edwards Sapien 3 from 2016-2019. The
Medtronic Evolut R and Evolut Pro were used in a minority of cases.
Patients were categorized by anesthesia type into MAC versus GA groups
based on the utilization of endotracheal intubation. The decision to
administer MAC or GA for each case was made in a multidisciplinary team
format which included input from anesthesiologists, cardiologists, and
cardiac surgeons. The analysis was performed on an as-treated basis.
Demographics, baseline medical history, and outcome data points were
collected according to VASQIP definitions. Diabetes was defined as any
outpatient preoperative hyperglycemia requiring oral medications or
insulin. History of cardiac surgery was defined as any history of
cardiac surgery, on or off pump, such as coronary artery bypass graft,
valve replacement, or other procedures. Preoperative atrial fibrillation
was defined as the presence of atrial fibrillation or atrial flutter in
the two weeks preceding surgery. Preoperative myocardial infarction (MI)
was defined as any prior history of MI, regardless of timeframe, prior
to surgery. Thirty-day postoperative morbidity and mortality estimates
were calculated by the VASQIP risk score.
Complications and outcomes were defined as follows: postoperative renal
failure was defined as the development of new renal failure requiring
renal replacement therapy, or an exacerbation of preoperative renal
failure requiring initiation of renal replacement therapy within 30 days
postoperatively. Postoperative atrial fibrillation included new-onset
atrial fibrillation or atrial flutter requiring any treatment.
Postoperative MI included any MI that occurred within 30 days
postoperatively. Postoperative cerebrovascular accident (CVA) was
defined as any new objective neurologic deficit lasting more than 72
hours with onset immediately post-operatively or occurring within the 30
days after surgery. Intraoperative cardiac arrest was defined as any
cardiac arrest requiring external or open cardiopulmonary resuscitation
(CPR) in the operating room, whereas postoperative cardiac arrest
included any cardiac arrest requiring CPR within 30 days
postoperatively. All lab values represent the results reported closest
to the date of the surgery and exclude any lab values collected beyond
30 days before surgery.
Direct cost data was derived from the local VA Managerial Cost
Accounting system, which collects and stores direct cost data associated
with every VA hospitalization. Costs were reported under the following
categories: direct operating room (OR) cost, direct intensive care unit
(ICU) cost, and overall direct costs. Direct costs are defined as costs
directly associated with patient care, such as anesthesia services,
nursing services, drugs, medical supplies, and hospitalization. Indirect
costs, commonly referred to as overhead costs, encompass the expenses
not directly tied to a patient’s care, such as administrative expenses,
medical records, and information services. Indirect costs were not
analyzed in this study, and all costs subsequently mentioned are direct
costs only. The types and costs of the valve prostheses used for each
patient were extracted from a local VA prosthetics database. Total
hospital cost was calculated, which included physician charges, labs,
imaging, operating room, intensive care unit, step-down unit, and
hospital floor costs. Overall cost included all these inpatient charges,
plus the cost of the prosthetic valve.
A non-matched analysis was initially performed. Patient characteristics,
ICU LOS, total hospital LOS, and costs were compared using Fisher’s
exact test for binary data and Wilcoxon rank sum test for continuous
data. Propensity score matching was then performed. The R package
“matchit” was used to match patients who received GA with those who
received MAC according to their propensity for receiving either. To
assess propensity, a logistic regression model with MAC as the outcome
and VASQIP estimated mortality, age, sex, and BMI as covariates was
used. History of diabetes, history of COPD, creatinine, and hemoglobin
were excluded from the model because these factors are integrated into
the VASQIP estimated mortality. Additionally, only preoperative
variables were utilized, and no procedure-related variables, including
postoperative echocardiogram findings (gradient, presence/absence of
paravalvular leaks, postoperative ejection fraction), EKG changes and/or
pacer requirement, were integrated. Patients were matched using a 1-to-1
matching with a caliper width of 0.1 (meaning that matched pairs were
within 0.1 standard deviations of each other on propensity score). This
process resulted in the matching of 83 of 105 GA recipients with 83 of
244 MAC recipients. To assess the effect of anesthesia type on outcomes,
mixed-effects models (logistic or linear regression as appropriate) with
anesthesia type as a fixed factor and a random factor for a matched pair
were used to account for the dependency introduced by matching. For
outcomes that were too sparse for a logistic regression model, McNemar’s
test for paired data was used. Finally, to assess whether OR times were
significantly shorter with MAC due to the anesthesia modality itself or
due to increased institutional experience (as MAC was used increasingly
in later years), OR time was compared between MAC and GA groups for the
year 2016 only. All analyses were performed using R (V.4.0.2, The R
Foundation for Statistical Computing, Vienna, Austria).