Creation of a Risk Calculator for Predicting New-Onset Cardiac Arrhythmias in Patients Undergoing Lumbar Fusion

Abstract

Introduction: As an increasing number of lumbar fusion procedures are being conducted at specialty hospitals and surgery centers, appropriate patient selection and risk stratification is critical to minimizing patient transfers. Postoperative cardiac arrhythmia has been linked to worse patient outcomes and is a common cause of patient transfer. Therefore, we created a risk calculator to predict a patient's likelihood of developing a new-onset postoperative cardiac arrhythmia after lumbar spinal fusion, which may improve preoperative facility selection.

Methods: A retrospective review was conducted of patients who undergoing lumbar fusion from 2017 to 2021 at a single academic center. Patients were excluded if they had any medical history of a cardiac arrhythmia. Multivariable regression was conducted to determine independent predictors of inpatient arrhythmias. The final regression was applied to a bootstrap to validate an arrhythmia prediction model. A risk calculator was created to determine a patient's risk of new-onset cardiac arrhythmia.

Results: A total of 1,622 patients were included, with 45 patients developing a new-onset postoperative arrhythmia. Age (OR = 1.05; 95% CI, 1.02 to 1.09; P = 0.003), history of beta-blocker use (OR = 2.01; 95% CI, 1.08 to 3.72; P = 0.027), and levels fused (OR = 1.59; 95% CI, 1.20 to 2.00; P = 0.001) were all independent predictors of having a new-onset inpatient arrhythmia. This multivariable regression produced an area under the curve of 0.742. The final regression was applied to a bootstrap prediction modeling technique to create a risk calculator including the male sex, age, body mass index, beta-blocker use, and levels fused (OR = 1.04, [CI = 1.03 to 1.06]) that produced an area under the curve of 0.733.

Conclusion: A patient's likelihood of developing postoperative cardiac arrhythmias may be predicted by comorbid conditions and demographic factors including age, sex, body mass index, and beta-blocker use. Knowledge of these risk factors may improve appropriate selection of an outpatient surgical center or orthopaedic specialty hospital versus an inpatient hospital for lumbar fusions.