A predictive model of perioperative myocardial infarction following elective spine surgery. (January 2022)

• Record Type: Journal Article
• Authors: Passias, Peter G; Pierce, Katherine E; Alas, Haddy; Bortz, Cole; Brown, Avery E; Vasquez-Montes, Dennis; Oh, Cheongeun; Wang, Erik; Jain, Deeptee; O'Connell, Brooke K; Raad, Micheal; Diebo, Bassel G.; Soroceanu, Alexandra; Gerling, Michael C.
• Is Part Of: Journal of clinical neuroscience. Volume 95(2022)
• Page Start: 112
• Page End: 117
• Publication Date: 2022-01
• Subjects: Myocardial infarction -- MI -- Spine surgery -- Perioperative complications -- Predictive model; Brain -- Surgery -- Periodicals; Neurosciences -- Periodicals; Nervous system -- Surgery -- Periodicals; Brain -- surgery -- Periodicals; Neurosurgical Procedures -- Periodicals; Neurosciences -- Periodicals; Electronic journals; 616.8
• DOI: 10.1016/j.jocn.2021.11.032
• Languages: English
• ISSNs: 0967-5868

Abstract

Highlights: Examined the predictors of myocardial infarction (MI) following elective spine procedures. 436 patients had an acute MI out of 196, 523 elective spine surgery patients. MI predictors included diabetes, cardiac arrest and PVD, blood transfusion, dialysis-dependence, low preop platelet count, SSI and days from operation to discharge. This can aid in the risk stratification of preoperative patients prior to spinal operations. Abstract: Myocardial infarction (MI), and its predictive factors, has been an understudied complication following spine operations. The objective was to assess the risk factors for perioperative MI in elective spine surgery patients as a retrospective case control study. Elective spine surgery patients with a perioperative MI were isolated in the NSQIP. The relationship between MI and non-MI spine patients was assessed using chi-squared and independent samples t-tests. Univariate/multivariate analyses assessed predictive factors of MI. Logistic regression with stepwise model selection was employed to create a model to predict MI occurrence. The study included 196, 523 elective spine surgery patients (57.1 yrs, 48%F, 30.4 kg/m 2 ), and 436 patients with acute MI (Spine-MI). Incidence of MI did not change from 2010 to 2016 (0.2%–0.3%, p = 0.298). Spine-MI patients underwent more fusions than patients without MI (73.6% vs 58.4%, p < 0.001), with an average of 1.03 levels fused. Spine-MI patients also had significantly more SPO (5.0% vs 1.8%, p < 0.001) and 3CO (0.9% vs 0.2%, p < 0.001), but less decompression-only procedures (26.4% vs 41.6%, p < 0.001). Spine-MI underwent more revisions (5.3% vs 2.9%, p = 0.003), had greater invasiveness scores (3.41 vs 2.73, p < 0.001) and longer operative times (211.6 vs 147.3 min, p < 0.001). Mortality rate for Spine-MI patients was 4.6% versus 0.05% (p < 0.001). Multivariate modeling for Spine-MI predictors yielded an AUC of 83.7%, and included history of diabetes, cardiac arrest and PVD, past blood transfusion, dialysis-dependence, low preoperative platelet count, superficial SSI and days from operation to discharge. A model with good predictive capacity for MI after spine surgery now exists and can aid in risk-stratification of patients, consequently improving preoperative patient counseling and optimization in the peri-operative period.