Back to Search
Start Over
Predicting Clinical Outcomes Following Surgical Correction of Adult Spinal Deformity.
- Source :
-
Neurosurgery [Neurosurgery] 2019 Mar 01; Vol. 84 (3), pp. 733-740. - Publication Year :
- 2019
-
Abstract
- Background: Deformity reconstruction surgery has been shown to improve quality of life (QOL) in cases of adult spinal deformity (ASD) but is associated with significant morbidity.<br />Objective: To create a preoperative predictive nomogram to help risk-stratify patients and determine which would likely benefit from corrective surgery for ASD as measured by patient-reported health-related quality of life (HRQoL).<br />Methods: All patients aged 25-yr and older with radiographic evidence of ASD and QOL data that underwent thoracolumbar fusion between 2008 and 2014 were identified. Demographic and clinical parameters were obtained. The EuroQol 5 dimensions questionnaire (EQ-5D) was used to measure HRQoL preoperatively and at 12-mo postoperative follow-up. Logistic regression of preoperative variables was used to create the prognostic nomogram.<br />Results: Our sample included data from 191 patients. Fifty-one percent of patients experienced clinically relevant postoperative improvement in HRQoL. Seven variables were included in the final model: preoperative EQ-5D score, sex, preoperative diagnosis (degenerative, idiopathic, or iatrogenic), previous spinal surgical history, obesity, and a sex-by-obesity interaction term. Preoperative EQ-5D score independently predicted the outcome. Sex interacted with obesity: obese men were at disproportionately higher odds of improving than nonobese men, but obesity did not affect odds of the outcome among women. Model discrimination was good, with an optimism-adjusted c-statistic of 0.739.<br />Conclusion: The predictive nomogram that we developed using these data can improve preoperative risk counseling and patient selection for deformity correction surgery.<br /> (Copyright © 2018 by the Congress of Neurological Surgeons.)
Details
- Language :
- English
- ISSN :
- 1524-4040
- Volume :
- 84
- Issue :
- 3
- Database :
- MEDLINE
- Journal :
- Neurosurgery
- Publication Type :
- Academic Journal
- Accession number :
- 29873763
- Full Text :
- https://doi.org/10.1093/neuros/nyy190