The National Surgical Quality Improvement Program (NSQIP) 2005-2010

Kimon Bekelis, M.D

Abstract
Background and Context
There is increasing scrutiny by several regulatory bodies regarding the complications of spine surgery. Precise delineation of the risks contributing to those complications remains a topic of debate.

Purpose
We attempted to create a predictive model of complications in patients undergoing spine surgery.

Study Design/Setting. Retrospective cohort study.

Patient Sample
13,660 patients registered in the American College of Surgeons National Quality Improvement Project (NSQIP) database.

Outcome Measures
30-day postoperative risks of stroke, MI, death, infection, UTI, DVT, PE, and return to the OR.

Methods
We performed a retrospective cohort study involving patients who underwent spine surgery from 2005-2010 and were registered in NSQIP. A model for outcome prediction based on individual patient characteristics was developed.

Results
Of the 13,660 patients, 2719 underwent anterior approaches (19.9%), 565 corpectomies (4.1%), and 1757 fusions (12.9%). The respective 30-day postoperative risks were 0.05% for stroke, 0.2% for MI, 0.25% for death, 0.3% for infection, 1.37% for UTI, 0,6% for DVT, 029% for PE, and 3.15% for return to the OR. Multivariate analysis demonstrated that increasing age, more extensive operations (fusion, corpectomy), medical deconditioning (weight loss, dialysis, PVD, CAD, COPD, diabetes), increasing BMI, non-independent mobilization (preoperative neurologic deficit), and bleeding disorders were independently associated with a more than 3 days length of stay. A validated model for outcome prediction based on individual patient characteristics was developed. The accuracy of the model was estimated by the area under the receiver operating characteristic (ROC) curve, which was 0.95, 0.82, 0.87, 0.75, 0.74, 0.78, 0.76, 0.74 and 0.65 for postoperative risk of stroke, MI, death, infection, DVT, PE, UTI, length of stay of 3 days or longer, and return to the OR, respectively.

Conclusions
Our model can provide individualized estimates of the risks of post-operative complications based on pre-operative conditions, and can potentially be utilized as an adjunct in the decision-making for spine surgery.

Journal Abstract:  http://www.sciencedirect.com/science/article/pii/S1529943013014563