Acute myocardial infarction among patients undergoing elective spinal fusion, total hip arthroplasty, and total knee arthroplasty in the United States: a retrospective cohort study

Acute myocardial infarction (AMI) is an uncommon but fatal complication among patients undergoing elective spinal fusion surgery (SF), total hip arthroplasty (THA), and total knee arthroplasty (TKA). Our objective was to estimate the incidence of AMI among adults undergoing elective SF, THA, and TKA in different post-operative risk windows and characterize high-risk sub-populations in the United States. A retrospective cohort study was conducted using data from a longitudinal electronic healthcare record (EHR) database from January 1, 2007 to June 30, 2018. ICD codes were used to identify SF, THA, TKA, AMI, and selected clinical characteristics. Incidence proportions (IPs) and 95% condence intervals were estimated in the following risk windows: index hospitalization, ≤ 30, ≤ 90, ≤ 180, and ≤ 365 days post-operation. A total of 67,533 SF patients, 87,572 THA patients, and 167,480 TKA patients were eligible for the study. The IP of AMI after SF, THA, and TKA ranged from 0.36%, 0.28%, and 0.25% during index hospitalization to 1.05%, 0.93%, and 0.85% ≤ 365 days post-operation, respectively. The IP of AMI was higher among patients who were older, male, with longer hospital stays, had a history of AMI, and had a history of diabetes. these ndings improved identify This study estimated the incidence of AMI using an EHR database among adults undergoing elective SF, THA, and TKA during various post-operative risk windows and among different sub-groups. The IP of AMI following these elective procedures was generally highest among the SF cohort compared to the THA and TKA cohorts. When stratied by relevant demographic and clinical characteristics, we found that the IP of post-operative AMI was higher among patients who were older, male, with longer hospital stays, had a history of AMI, and had a history of diabetes. Future studies are warranted to conrm these ndings via improved confounder control and to identify effect measure modiers.

International Classi cation of Diseases (ICD), Ninth Revision, Procedure Classi cation System (ICD-9-PCS) codes used to de ne exposures  To select for a relatively healthy cohort that underwent inpatient elective surgeries, patients were excluded if they 1) underwent a major surgical procedure that occurred within 90 days prior to the index surgery; 2) had a surgical indication that was for an emergency procedure; 3) were pregnant; or 4) had cancer or end (13.91% for SF, 12.17% for THA, and 16.22% for TKA), cardiac dysrhythmias (9.12% for SF, 12.45% for THA, and 13.09% for TKA), chronic ischemic disease (8.86% for SF, 8.91% for THA, and 9.36% for TKA), hypothyroidism (7.06% for SF, 9.56% for THA, and 10.80% for TKA), and anemia (7.14% for SF, 15.14% for THA, and 12.84% for TKA). Within all three surgical cohorts, a history of AMI was rare (i.e., between 0.52 and 0.62% across cohorts). Dementia, deep vein thrombosis, and pulmonary embolism were also rare among all three surgical cohorts. The average length of hospital stay (LHS) (for the index hospitalization) was 3.41, 2.69, and 2.89 days for SF, THA, and TKA, respectively. Lastly, although less than 1.00% of SFs were revisional, 39.88% of THAs and 37.66% of TKAs were revisional surgeries. Table 3 shows the baseline demographics and clinical/surgical characteristics of the elective SF, THA, and TKA patient population.  Table 5, and Table 6 show the IP information for AMI among patients undergoing elective SF, THA, and TKA, respectively.   days post-operation was 0.37% (95% CI: 0.26%, 0.48%) for black patients and 0.33% (95% CI: 0.30%, 0.36%) for white patients. Generally, SF patients with same day revisional surgery had higher IPs of AMI across risk windows compared to patients who did not have same day revisional surgery; however, the opposite association was observed for THA and TKA patients (i.e., the IP of AMI was lower for those with same day revisional surgery compared to those who did not have same day revisional surgery across risk windows).
Detailed incidence rate information can be found in the Appendix (i.e., S Table 1, S Table 2, and S  found that the IP of cardiovascular complications during hospitalization increased with age: 0.52% for those aged 20 to 24 years, 0.52% for those aged 35 to 49 years, 1.06% for those aged 50 to 64 years, 2.32% for those aged 64 to 74 years, and 3.20% for those aged 75 years or more; 13 although we used different age categorizations, we too found a similar relationship between age and the incidence of post-operative AMI. Moreover, Chung et al. performed a retrospective cohort study of 15,618 patients undergoing elective SF in the ACS NSQIP between 2006 and 2013 and concluded that patients with metabolic syndrome had increased incidence of post-operative MI (0.5%) compared to those without metabolic syndrome (0.3%). 6 Likewise, Memstoudis et al. also investigated the relation between post-operative MI and metabolic syndrome, but these authors used the NIS database from 1998 to 2008 and patients undergoing primary posterior lumbar fusion; nonetheless, Metmstoudis et al. also found that patients with metabolic syndrome had increased incidence of post-operative MI (0.6%) compared to those without metabolic syndrome (0.3%). 14 Although we did not look at this condition explicitly, metabolic syndrome is a composite condition that includes diabetes; we found that patients with type 2 diabetes had increased incidence of post-operative AMI compared to those without type 2 diabetes, so our nding is  15 This nding somewhat aligns with the association that we found: the 30-day incidence of AMI was 0.75% among patients who underwent revisional SF and 0.48% among patients who did not undergo revisional SF; however, less than 600 patients underwent revisional SF in our cohort; therefore, the IP estimate may not be stable.
Total hip arthroplasty and total knee arthroplasty cohorts Kreder at al. evaluated 26,320 patients who underwent primary THA and TKA by performing a retrospective cohort study of administrative data in Ontario, Canada; the authors reported that the incidence of AMI increased with age among both THA patients (0.47% for those aged 65 to 79 years and 1.28% for those aged 80 years or greater) and TKA patients (0.45% for those aged 65 to 79 years and 1.09% for those aged 80 years or greater). 16 Likewise, Koenig et al.
performed a retrospective review of 306 patients who underwent revision THA; the authors found that the 90-day incidence of post-operative MI was 0.0% for those aged less than 65 years and 1.6% for those aged 65 to 79 years. 17 As was the case with SF cohort, we also found that the incidence of post-operative  18 we found a similar relationship in that the men in our study generally had higher incidences of AMI compared to women across all risk windows for both THA and TKA.
Furthermore, Pulido et al. performed an institutional review of their prospective database of patients undergoing elective joint arthroplasty and identi ed 15,383 patients who had THA or TKA; the authors found that the incidence of in-hospital MI was higher among revisional surgery than among primary surgery patients for both THA (0.35% vs. 0.16%) and TKA (0.62% and 0.33%). 19 We found an opposite association for both TKA (0.23% for revisional surgery and 0.26% for non-revisional surgery) and THA (0.21% for revisional surgery and 0.32% for non-revisional surgery) during index hospitalization. However, it should be noted that their analysis comprised of one institution (as opposed to our hospital network-based analysis revision TKA and determined that the 90-day incidence of post-operative MI was 0.8% for primary TKA and 1.0% for revisional TKA. 21 We again see that our 90-day incidence nding (0.39% for revisional TKA compared to 0.43% for primary TKA) is not in line with the literature. Although Mohamed et al. also used a national database, they used both ICD-9 and Current Procedural Terminology (CPT) codes to identify TKA and only looked at data for the year 2000 (as opposed to the eleven-year period analyzed here). 21 Recurrent AMI Although no studies looked at the incidence of post-operative AMI among patients with a history of AMI, it is well-established that patients who survive an AMI episode have an increased risk of a future AMI. 22 Thus, our analysis (among those with a history of AMI) agree with such a relationship as we found that patients with a history of AMI had a drastically higher incidence than those without such a history; for example, the IP of post-operative AMI during index hospitalization among the TKA cohort was 10.76% for those with a medical history of AMI compared to 0.19% for those without such a history.

Database considerations
It is noteworthy that our study used Optum EHR database while most studies in the literature used NSQIP or NIS. Because of differences in these data sources, it may not be surprising that our results would not exactly align with the incidence information found in the literature. For instance, a 2016 study evaluated the variability in standard outcomes of posterior lumbar fusion between the University HealthSystem Consortium (UHC) and the NIS and found that the databases had similar patient populations undergoing posterior lumbar fusion, but that the UHC database reported signi cantly higher MI rates as well as longer lengths of hospital stay. 23 Another study by Jain et al. compared similar patient populations between a multicenter, surgeon-maintained database (SMD) and a Centers for Medicare & Medicaid Services claims database (MCD); the authors ultimately found that the incidence of post-operative AMI was slightly higher in the SMD (2.0%) than in the MCD (1.8%). 24 Additionally, recent studies have also shown that certain variables have changed over time within both NIS and NSQIP; [25][26][27][28]

Strengths and limitations
The Optum EHR database has both inpatient and outpatient data as well as a large sample size that enabled us to generate real-world incidence estimates that are generalizable to a segment of the commercially insured US population (i.e., those in the Optum network). However, our patient population was selected to be relatively healthy, so this selection may affect the overall generalizability.
Nonetheless, this study provides additional information about AMI in a variety of risk windows. Most studies identi ed in the literature analyzed AMI events during index hospitalization or in the 30-or 90-day risk windows. Our study thus builds on previous work by not only estimating AMI incidences during index hospitalization and the 30-and 90-day risk windows but also by generating data on AMI incidence in the 180-and 365-day risk windows; it is important to have data in these longer risk windows to ensure no incident AMI events are missed (even though it is more likely for AMI to occur in the shorter risk windows). Lastly, our study adds to the existing literature about AMI incidence by presenting such information in the form of incidence rates; most of the AMI incidence information in the literature is presented in the form of IPs (which can be more biased due to censoring for longer follow-up periods), and thus there is a paucity of data in the form of incidence rates.
Still, it must be noted that EHR data were originally developed to improve patient care/modernize billing procedures and thus were not designed as research resources. As a result, EHR data tend to have more missing data (when compared to data obtained from clinical trials and/or prospective studies with primary data collection), and this missingness can potentially bias results. 30 However, given that elective surgery and AMI events generally require medical encounters, they would have been recorded in Optum EHR; therefore, the likelihood of missing information for these key variables would be very low. Like other studies utilizing secondary data sources without validation (e.g., medical chart review), exposure and outcome misclassi cation are possible. Furthermore, patients may have sought healthcare outside Optum EHR prior to the index surgery, so it is possible that a patient developed an AMI prior to the index surgery; similarly, some incident events may have been missed if a patient sought care outside the system after surgery.
Lastly, this study employed a descriptive analysis approach; thus, comparisons within strati ed analyses may be subject to confounding factors that were not properly controlled. As a result, these comparisons must be interpreted with caution. Future studies in this area should consider multiple regression modeling and/or multivariable strati cation techniques to better account for potential confounding. Future researchers should also consider the impact of effect measure modi cation on their results.

Conclusion
This study estimated the incidence of AMI using an EHR database among adults undergoing elective SF, THA, and TKA during various post-operative risk windows and among different sub-groups. The IP of AMI following these elective procedures was generally highest among the SF cohort compared to the THA and TKA cohorts. When strati ed by relevant demographic and clinical characteristics, we found that the IP of post-operative AMI was higher among patients who were older, male, with longer hospital stays, had a history of AMI, and had a history of diabetes. Future studies are warranted to con rm these ndings via improved confounder control and to identify effect measure modi ers.

Declarations
Authors' contribution PJA, JM, and KH contributed to the study design. PJA, KH, XZ, QL, RG, CS, and SM contributed to data analyses. PJA and KH drafted the manuscript with input from JM, XZ, QL, RG, CS, and SM. All authors read and approved the nal manuscript.
Ethical approval and consent to participate As this study involved anonymized structured data, which according to applicable legal requirements do not contain data subject to privacy laws, obtaining informed consent from patients was not required.

Consent for publication
Not applicable.

Availability of materials
The data that support the ndings of this study are available from Optum but restrictions apply to the availability of these data and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Optum.

Competing interests
All authors are employees of P zer Inc., New York, NY, USA.

Funding
This work was funded by P zer Inc.