Abstract
BACKGROUND: Ischemic optic neuropathy (ION) is a rare complication of anesthesia and surgery that causes vision loss in spine fusion. We sought to develop a predictive model based on known preoperative risk factors for perioperative ION to guide patient and physician preoperative decision-making. METHODS: In the National Inpatient Sample (NIS) for 1998-2012, discharges for posterior thoracic, lumbar, and sacral spine fusion were identified and classified by ION status. Variables were selected without weighting via variable clustering using Principal Component Analysis of Mixed Data (PCA-MIX). Hierarchical clustering with 4 clusters was performed, and the variable with largest squared loading in each cluster was chosen. By splitting our sample into a training and testing data set, we developed and internally validated a predictive model. The final model using variables known preoperatively was constructed to allow determination of relative and absolute risk of developing perioperative ION and was tested for calibration and discrimination. RESULTS: The final predictive model based on hierarchical clustering contained 3 preoperative factors, age, male or female sex, and the presence of obstructive sleep apnea (OSA). The predictive model based on these factors had an area under the receiver operating characteristic curve (AUC) of 0.65 and good calibration. A score cutoff of >1 had 100% sensitivity, while score of 3 had 96.5% specificity. The highest estimated absolute risk (844.5/million) and relative risk of ION (46.40) was for a man, age 40-64 years, with OSA. CONCLUSIONS: The predictive model could enable screening for patients at higher risk of ION to provide more accurate risk assessment and surgical and anesthetic planning for perioperative ION in spine fusion.