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

Oswestry残疾指数 生活质量(医疗保健) 外科 最小临床重要差异 腰椎管狭窄症 腰椎 物理疗法 脊柱融合术 队列 背痛 回顾性队列研究 减压 患者报告的结果 神经外科
作者
Daniel Lubelski,James Feghali,Amy S. Nowacki,Vincent J. Alentado,Ryan Planchard,Kalil G. Abdullah,Daniel M. Sciubba,Michael P. Steinmetz,Edward C. Benzel,Thomas E. Mroz
出处
期刊:Journal of Neurosurgery [American Association of Neurological Surgeons]
卷期号:34 (4): 1-9 被引量:4
标识
DOI:10.3171/2020.8.spine20577
摘要

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.
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