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Novotny et al. Vessel Plus 2022;6:51 https://dx.doi.org/10.20517/2574-1209.2021.139 Page 3 of 15

r-AVR patients’ records were extracted from the SPARCS database. For the 2005-2018 New York State
SPARCS database records, de-identified reports were generated by the Biostatistical Consulting Core Lab;
using only de-identified reports for this study, a “not human subjects research” written exemption for these
analyses was received by the Stony Brook University Committee on Research in Human Subjects (IRB 2021-
00563). The study’s protocol is available online at: https://commons.library.stonybrook.edu/dos-articles/1/.

Patient population
This study’s analyses relied upon a comprehensive list of billing codes (see Supplementary Table 1; using
coding manuals, these billing codes were identified by expert coders, the billing code details were extracted
by the study data analytics team. All billing codes used were validated by the study’s clinician team. Using
these codes, the inpatient records for adults (age > 18) undergoing a non-emergent AVR procedure from
January 2005 through November 2018 were extracted. Duplicate records (N = 23), records with unknown
gender (N = 1), and records missing unique personal identifiers (UPID; N = 193) were excluded. Patients
who had an r-AVR at least 30 days after the first AVR were identified. Due to the increased risk for an
adverse post-AVR event, patients with concomitant or prior coronary artery bypass graft or percutaneous
coronary intervention, prior thoracic aortic aneurysm, aortic dissection, active endocarditis, solid tumor
without metastasis, or metastatic cancer were also excluded. Demographics, baseline health conditions, and
Elixhauser comorbidity score (See Supplementary Table 2) at r-AVR were considered. The Elixhauser score
described patients’ risk of mortality and readmission based on pre-existing diagnoses .
[13]

Study outcomes
Co-primary study endpoints included the Society of Thoracic Surgeons’ (STS) composite endpoint [major
morbidity (MM); a composite comprised of 5 major complications and/or 30-day operative mortality] and
30-day readmission (READMIT). As secondary study endpoints, the STS composite’s individual 30-day
operative mortality and 5 major morbidity sub-components were separately examined; these included STS
major complications of a periprocedural permanent stroke, renal failure, prolonged ventilation, deep sternal
[14]
wound infection, and/or repeat procedure within 30 days of the first r-AVR procedure . The STS 30-day
operative mortality definition included both in-hospital death and all deaths within 30 days of the
procedure. Additional secondary outcomes were evaluated, including length of hospital stay [length of stay
(LOS); time from admission date to discharge date], post-procedure LOS (time from procedure date to
discharge date), as well as non-STS post-procedural clinically relevant SAVR/TAVR complications
including myocardial infarction, cardiac arrest, acute kidney injury, prosthetic valve endocarditis, major
stroke, transient ischemic attack, major bleeding, and vascular complications. As comorbidities are
commonly difficult to differentiate from post-procedural complications by exclusively using billing codes,
major complications were identified only if there had been no prior evidence of that condition for the two
years preceding the procedure. Following October 2015, new ICD-10 complication codes were also used to
differentiate complications from comorbidities [15,16] .

Statistical analysis
Statistical analyses were performed by an institutional biostatistical consulting core lab team member with
SPARCS data analytics expertise and SAS 9.4 (SAS Institute Inc., Cary, NC) biostatistics/database
programming experience; data extraction, analysis and manuscript writing tasks occurred from January
2021 to February 2022. Demographics, baseline health conditions, and Elixhauser comorbidity score (See
Supplementary Table 2) at r-AVR were considered. The Elixhauser score describes patients’ risk of
mortality and readmission based on pre-existing diagnoses. Chi-square tests with exact P-values based on
Monte Carlo simulation were utilized to examine the marginal association between categorical variables
(patients’ characteristics, risk factors, specific Elixhauser comorbidities) and AF/AFL+, as well as between
categorical variables and binary outcomes (e.g., MM and READMIT) . Welch’s t-tests were used to
[17]