Objective
Spinal cord ischemia (SCI) is a devastating, but potentially preventable, complication of thoracic endovascular aortic repair (TEVAR). The purpose of this analysis was to determine what factors predict SCI after TEVAR.
Methods
All TEVAR procedures at a single institution were reviewed for patient characteristics, prior aortic repair history, aortic centerline of flow analysis, and procedural characteristics. SCI was defined as any lower extremity neurologic deficit that was not attributable to an intracranial process or peripheral neuropathy. Forty-three patient and procedural variables were evaluated individually for association with SCI. Those with the strongest relationships to SCI (P < .1) were included in a multivariable logistic regression model, and a stepwise variable elimination algorithm was bootstrapped to derive a best subset of predictors from this model.
Results
From 2002–13, 741 patients underwent TEVAR for various indications and 68 (9.2%) developed SCI (permanent: N = 38; 5.1%). Due to lack of adequate imaging for centerline analysis, 586 patients (any SCI, N = 43; 7.4%) were subsequently analyzed. Patients experiencing SCI after TEVAR were older (SCI 72±11 vs. No SCI, 65±15 years; P < .0001) and had significantly higher rates of multiple cardiovascular risk factors. The stepwise selection procedure identified five variables as the most important predictors of SCI: age (odds ratio, OR, multiplies by 1.3 per 10 years; 95% CI 0.9–1.8, P = .06), aortic coverage length (OR multiplies by 1.3 per 5cm; CI 1.1–1.6, P = .002), chronic obstructive pulmonary disease (OR, 1.9; CI .9–4.1, P = .1), chronic renal insufficiency(creatinine ≥ 1.6; OR, 1.9; CI .8–4.2, P = .1), and hypertension (defined as chart history and/or medication; OR, 6.4; CI 2.6–18, P < .0001). A logistic regression model with just these five covariates had excellent discrimination (AUC = .83) and calibration (χ2 = 9.8; P = .28).
Conclusion
This analysis generated a simple model that reliably predicts SCI after TEVAR. This clinical tool can assist decision-making regarding when to proceed with TEVAR, guide discussions about intervention risk, and help determine when maneuvers to mitigate SCI risk should be implemented.