Abstract
This was a national database study.To examine the role of comorbidities and demographics on inpatient complications in patients with lumbar degenerative conditions.Degenerative conditions of the lumbar spine account for the most common indication for spine surgery in the elderly population in the United States. Significant studies investigating demographic as predictors of surgical rates and health outcomes for degenerative lumbar conditions are lacking.Data were obtained from the National Inpatient Sample from 2010 to 2014 and International Classification of Diseases, 9th revision, Clinical Modification codes were used to identify patients with a primary diagnosis of degenerative lumbar condition. Patients were stratified based on demographic variables and comorbidity status. Multivariate regression analyses were used to determine whether any individual demographic variables, such as race, sex, insurance, and hospital status predicted postoperative complications.A total of 256,859 patients were identified for analysis. The rate of overall complications was found to be 16.1% with a mortality rate of 0.10%. Female, Black, Hispanic, and Asian/Pacific Islander patients had lower odds of receiving surgical treatment compared to White patients (P<.001). Medicare and Medicaid patients were less likely to be surgically managed than patients with private insurance (OR = 0.75, 0.37; P<.001, respectively). Urban hospitals were more likely to provide surgery when compared to rural hospitals (P < .001). Patients undergoing fusion had more complications than decompression alone (P < .001). Females, Medicare insurance status, Medicaid insurance status, urban hospital locations, and certain geographical locations were found to predict postoperative complications (P < .001).There were substantial differences in surgical management and postoperative complications among individuals of different sex, races, and insurance status. Further investigation evaluating the effect of demographics in spine surgery is warranted to fully understand their influence on patient complications.
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