• Nathaniel T Ondeck, Daniel D Bohl, Patawut Bovonratwet, Ryan P McLynn, Jonathan J Cui, Blake N Shultz, Adam M Lukasiewicz, and Jonathan N Grauer.
• Department of Orthopaedics and Rehabilitation, Yale School of Medicine, 800 Howard Ave, New Haven, CT 06510, USA.
• Spine J. 2018 Jan 1; 18 (1): 44-52.

Background ContextAs research tools, the American Society of Anesthesiologists (ASA) physical status classification system, the modified Charlson Comorbidity Index (mCCI), and the modified Frailty Index (mFI) have been associated with complications following spine procedures. However, with respect to clinical use for various adverse outcomes, no known study has compared the predictive performance of these indices specifically following posterior lumbar fusion (PLF).PurposeThis study aimed to compare the discriminative ability of ASA, mCCI, and mFI, as well as demographic factors including age, body mass index, and gender for perioperative adverse outcomes following PLF.Study Design/SettingA retrospective review of prospectively collected data was performed.Patient SamplePatients undergoing elective PLF with or without interbody fusion were extracted from the 2011-2014 American College of Surgeons National Surgical Quality Improvement Program (NSQIP).Outcome MeasuresPerioperative adverse outcome variables assessed included the occurrence of minor adverse events, severe adverse events, infectious adverse events, any adverse event, extended length of hospital stay, and discharge to higher-level care.MethodsPatient comorbidity indices and characteristics were delineated and assessed for discriminative ability in predicting perioperative adverse outcomes using an area under the curve analysis from the receiver operating characteristics curves.ResultsIn total, 16,495 patients were identified who met the inclusion criteria. The most predictive comorbidity index was ASA and demographic factor was age. Of these two factors, age had the larger discriminative ability for three out of the six adverse outcomes and ASA was the most predictive for one out of six adverse outcomes. A combination of the most predictive demographic factor and comorbidity index resulted in improvements in discriminative ability over the individual components for five of the six outcome variables.ConclusionFor PLF, easily obtained patient ASA and age have overall similar or better discriminative abilities for perioperative adverse outcomes than numerically tabulated indices that have multiple inputs and are harder to implement in clinical practice.Copyright © 2017 Elsevier Inc. All rights reserved.

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