Patient-specific prediction model for clinical and quality-of-life outcomes after lumbar spine surgery

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  • 1 Department of Neurosurgery, Johns Hopkins Hospital, Baltimore, Maryland;
  • 2 Cleveland Clinic Lerner College of Medicine, Cleveland;
  • 3 Department of Quantitative Health Science, Cleveland Clinic, Cleveland, Ohio;
  • 4 Department of Neurosurgery, Indiana University School of Medicine, Indianapolis, Indiana;
  • 5 Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, Texas; and
  • 6 Department of Neurosurgery and the Cleveland Clinic Center for Spine Health, Cleveland Clinic, Cleveland, Ohio
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OBJECTIVE

Patient demographics, comorbidities, and baseline quality of life (QOL) are major contributors to postoperative outcomes. The frequency and cost of lumbar spine surgery has been increasing, with controversy revolving around optimal management strategies and outcome predictors. The goal of this study was to generate predictive nomograms and a clinical calculator for postoperative clinical and QOL outcomes following lumbar spine surgery for degenerative disease.

METHODS

Patients undergoing lumbar spine surgery for degenerative disease at a single tertiary care institution between June 2009 and December 2012 were retrospectively reviewed. Nomograms and an online calculator were modeled based on patient demographics, comorbidities, presenting symptoms and duration of symptoms, indication for surgery, type and levels of surgery, and baseline preoperative QOL scores. Outcomes included postoperative emergency department (ED) visit or readmission within 30 days, reoperation within 90 days, and 1-year changes in the EuroQOL-5D (EQ-5D) score. Bootstrapping was used for internal validation.

RESULTS

A total of 2996 lumbar surgeries were identified. Thirty-day ED visits were seen in 7%, 30-day readmission in 12%, 90-day reoperation in 3%, and improvement in EQ-5D at 1 year that exceeded the minimum clinically important difference in 56%. Concordance indices for the models predicting ED visits, readmission, reoperation, and dichotomous 1-year improvement in EQ-5D were 0.63, 0.66, 0.73, and 0.84, respectively. Important predictors of clinical outcomes included age, body mass index, Charlson Comorbidity Index, indication for surgery, preoperative duration of symptoms, and the type (and number of levels) of surgery. A web-based calculator was created, which can be accessed here: https://riskcalc.org/PatientsEligibleForLumbarSpineSurgery/.

CONCLUSIONS

The prediction tools derived from this study constitute important adjuncts to clinical decision-making that can offer patients undergoing lumbar spine surgery realistic and personalized expectations of postoperative outcome. They may also aid physicians in surgical planning, referrals, and counseling to ultimately lead to improved patient experience and outcomes.

ABBREVIATIONS ALIF = anterior lumbar interbody fusion; AUC = area under the curve; BMI = body mass index; CCI = Charlson Comorbidity Index; c index = concordance index; ED = emergency department; EQ-5D = EuroQOL-5D; MCID = minimum clinically important difference; NSQIP = National Surgical Quality Improvement Program; PDQ = Pain and Disability Questionnaire; PLIF = posterior lumbar interbody fusion; QOL = quality of life; TLIF = transforaminal lumbar interbody fusion.

Supplementary Materials

    • Supplemental Tables 1–4 (PDF 492 KB)

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Contributor Notes

Correspondence Thomas E. Mroz: Neurological Institute, Cleveland Clinic Center for Spine Health, The Cleveland Clinic, Cleveland, OH. mrozt@ccf.org.

INCLUDE WHEN CITING Published online January 29, 2021; DOI: 10.3171/2020.8.SPINE20577.

D.L. and J.F. contributed equally to this work.

Disclosures Dr. Mroz receives royalties from Stryker. Dr. Sciubba is a consultant for DePuy-Synthes, Medtronic, Stryker, and Baxter. Dr. Steinmetz receives royalties from Zimmer-Biomet and Elsevier, and honoraria from Stryker and Globus.

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