• Spine · Mar 2018

    Multicenter Study

    Predictors of Thirty Day Hospital Readmission Following Posterior Cervical Fusion in 3401 Patients.

    • Winward Choy, Sandi K Lam, Zachary A Smith, and Nader S Dahdaleh.
    • Department of Neurological Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL.
    • Spine. 2018 Mar 1; 43 (5): 356-363.

    Study DesignRetrospective cohort study.ObjectiveThe aim of the study was to determine readmission rates and predictors of readmission after posterior cervical fusion (PCF).Summary Of Background DataPCFs are common spinal operations for a variety of spinal disorders including cervical myelopathy, unstable fractures, cervical deformity, and tumors. Data elaborating on risk factors for 30-day readmission are limited.MethodsData were collected from the 2006 to 2013 American College of Surgeons National Surgical Quality Improvement Program database. Predictors of 30-day readmission comprising patient demographics, comorbidities, operative features, and postoperative complications were identified through logistic multivariable regression.ResultsA total of 3401 patients met study criteria. Rate of 30-day readmission was 6.20%. Multilevel fusion was performed in 69.16% of patients. Postoperative infection was the most reason, accounting for 17.06% of all readmissions. Age older than 70 years (odds ratio [OR] = 1.61, P = 0.012), renal failure requiring dialysis (OR = 3.69, P = 0.011), anemia (OR = 1.57, P = 0.006), multilevel fusion (OR = 1.61, P = 0.012), surgical site infections (OR = 20.4, P < 0.001), wound dehiscence (OR = 19.08, P < 0.001), postoperative pneumonia (OR = 2.75, P = 0.01), pulmonary embolism (OR = 15.39, P < 0.001), and progressing renal insufficiency (OR = 10.13, P = 0.061) were significant predictors of hospital readmission.ConclusionThe identified predictors of readmission after PCF can improve patient counseling, identification of high-risk patients, and guide changes in healthcare delivery pathways. Patients with modifiable risk factors such as anemia and kidney failure may benefit from preoperative optimization. In addition, postoperative complications represent a key target for intervention.Level Of Evidence3.

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