Risk Factors for Readmission Following Surgical Decompression for Spinal Epidural Abscesses: An Analysis of 4595 Patients.

Abstract

Retrospective cohort study. The study aimed to (1) compare baseline demographics of patients undergoing surgery for SEA who were/were not readmitted; (2) identify risk factors for 90-day readmissions; and (3) quantify 90-day episode-of-care health care costs. Spinal epidural abscess (SEA), while rare, occurring ~2.5-5.1/10,000 admissions, may lead to permanent neurologic deficits and mortality. Definitive treatment often involves surgical intervention via decompression. A search of the PearlDiver database from 2010 to 2021 for patients undergoing decompression for SEA identified 4595 patients. Cohorts were identified through the International Classification of Disease, Ninth Revision (ICD-9), ICD-10, and Current Procedural Terminology codes. Baseline demographics of patients who were/were not readmitted within 90 days following decompression were aggregated/compared, identifying factors associated with readmission. Using Bonferroni correction, a P-value<0.001 was considered statistically significant. Readmission within 90 days of surgical decompression occurred in 36.1% (1659/4595) of patients. While age/gender were not associated with readmission rate, alcohol use disorder, arrhythmia, chronic kidney disease, ischemic heart disease, and obesity were associated with readmission. Readmission risk factors included fluid/electrolyte abnormalities, obesity, paralysis, tobacco use, and pathologic weight loss (P<0.0001). Mean same-day total costs ($17,920 vs. $8204, P<0.001) and mean 90-day costs ($46,050 vs. $15,200, P<0.001) were significantly higher in the readmission group. A substantial proportion of patients (36.1%) are readmitted within 90 days following surgical decompression for SEA. The top 5 risk factors in descending order are fluid/electrolyte abnormalities, pathologic weight loss, tobacco use, pre-existing paralysis, and obesity. This study highlights areas for perioperative medical optimization that may reduce health care utilization.