Neurospine.  2023 Dec;20(4):1337-1345. 10.14245/ns.2346840.420.

A Predictive Model of Failure to Rescue After Thoracolumbar Fusion

Affiliations
  • 1Topiwala National Medical College, Mumbai, India
  • 2Bowers Neurosurgical Frailty and Outcomes Data Science Lab, Sandy, UT, USA
  • 3Department of Neurosurgery, University of New Mexico Hospital (UNMH), Albuquerque, NM, USA
  • 4Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
  • 5School of Medicine, Georgetown University, Washington, DC, USA

Abstract


Objective
Although failure to rescue (FTR) has been utilized as a quality-improvement metric in several surgical specialties, its current utilization in spine surgery is limited. Our study aims to identify the patient characteristics that are independent predictors of FTR among thoracolumbar fusion (TLF) patients.
Methods
Patients who underwent TLF were identified using relevant diagnostic and procedural codes from the National Surgical Quality Improvement Program (NSQIP) database from 2011–2020. Frailty was assessed using the risk analysis index (RAI). FTR was defined as death, within 30 days, following a major complication. Univariate and multivariable analyses were used to compare baseline characteristics and early postoperative sequelae across FTR and non-FTR cohorts. Receiver operating characteristic (ROC) curve analysis was used to assess the discriminatory accuracy of the frailty-driven predictive model for FTR.
Results
The study cohort (N = 15,749) had a median age of 66 years (interquartile range, 15 years). Increasing frailty, as measured by the RAI, was associated with an increased likelihood of FTR: odds ratio (95% confidence interval [CI]) is RAI 21–25, 1.3 [0.8–2.2]; RAI 26–30, 4.0 [2.4–6.6]; RAI 31–35, 7.0 [3.8–12.7]; RAI 36–40, 10.0 [4.9–20.2]; RAI 41– 45, 21.5 [9.1–50.6]; RAI ≥ 46, 45.8 [14.8–141.5]. The frailty-driven predictive model for FTR demonstrated outstanding discriminatory accuracy (C-statistic = 0.92; CI, 0.89–0.95).
Conclusion
Baseline frailty, as stratified by type of postoperative complication, predicts FTR with outstanding discriminatory accuracy in TLF patients. This frailty-driven model may inform patients and clinicians of FTR risk following TLF and help guide postoperative care after a major complication.

Keyword

Frailty; Outcomes; Risk analysis index; Spine surgery; Thoracolumbar fusion; NSQIP
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