Can the American College of Surgeons Risk Calculator Predict 30-Day Complications After Cervical Spine Surgery?
Authors: McCarthy Michael H. , Singh Partik , Maslak Joseph , Nayak Rusheel , Jenkins Tyler J. , Hsu Wellington K. , Patel Alpesh A. 
Published: September 2019

Study Design:

This was a retrospective cohort study.

Objective:

The objective of this study was to assess the American College of Surgeons (ACS) Risk Calculator’s ability to accurately predict complications after cervical spine surgery.

Summary of Background Data:

Surgical risk calculators exist in many fields and may assist in the identification of patients at increased risk for complications and readmissions. Risk calculators may allow for improved outcomes, an enhanced informed consent process, and management of modifiable risk factors. The American College of Surgeons National Surgery Quality Improvement Program (ACS NSQIP) Risk Calculator was developed from a cohort of over 1.4 million patients, using 2805 unique Current Procedural Terminology (CPT) codes. The risk calculator uses 21 patient predictors (eg, age, American Society of Anesthesiologists class, body mass index, hypertension) and the planned procedure (CPT code) to predict the chance that patients will have any of 12 different outcomes (eg, death, any complication, serious complication, reoperation) within 30 days following surgery. The purpose of this study is to determine if the ACS NISQIP risk calculator can predict 30-day complications after cervical fusion.

Methods:

A retrospective chart review was performed on patients that underwent primary cervical fusions between January 2009 and 2015 at a single institution, utilizing cervical fusion CPT codes. Patients without 30 days of postoperative follow-up were excluded. Descriptive statistics were calculated for the overall sample, anterior versus posterior fusion, and single versus multilevel fusion. Logistic regression models were fit with actual complication occurrence as the dependent variable in each model and ACS estimated risk as the independent variable. The c-statistic was used as the measure of concordance for each model. Receiver operating characteristic curves were plotted to visually depict the predictive ability of the estimated risks. Acceptable concordance was set at c>0.80. All analyses were conducted using SAS, v9.4.

Results:

A total of 404 patients met the inclusion criteria for this study. Age, body mass index, sex, and a number of levels of fusion were gathered as input data the ACS NSQIP Risk Calculator. Results of Risk Calculator were compared with observed complication rates. Descriptive statistics of the Risk Calculator risk estimates showed a significant prediction of “any complication” and “discharge to skilled nursing facility” among the cohort. Because there were no deaths or urinary tract infections, no models were fit for these outcomes.

Conclusions:

The ACS Risk Calculator accurately predicted complications in the categories of “any complication” (P<0.0001) and “discharge to the skilled nursing facility” (P<0.001) for our cohort. We conclude that the ACS Risk Calculator was unable to accurately predict specific complications on a more granular basis for the patients of this study. Although the ACS risk calculator may be useful in the field of general surgery and in the development of new institutional strategies for risk mitigation, our findings demonstrate that it does not necessarily provide accurate information for patients undergoing cervical spinal surgery.