TY - JOUR
T1 - Preoperative Nomograms Predict Patient-Specific Cervical Spine Surgery Clinical and Quality of Life Outcomes
AU - Lubelski, Daniel
AU - Alentado, Vincent
AU - Nowacki, Amy S.
AU - Shriver, Michael
AU - Abdullah, Kalil G.
AU - Steinmetz, Michael P.
AU - Benzel, Edward C.
AU - Mroz, Thomas E.
N1 - Publisher Copyright:
© 2017 by the Congress of Neurological Surgeons.
PY - 2018/7/1
Y1 - 2018/7/1
N2 - BACKGROUND: Clinical and quality of life (QOL) outcomes vary depending onthe patient's demographics, comorbidities, presenting symptoms, pathology, and surgical treatment used. While there have been individual predictors identifed, no comprehensive method incorporates a patient's complex clinical presentation to predict a specifc individual postoperative outcome. OBJECTIVE: To create tool that predicts patient-specifc outcomes among those undergoing cervical spine surgery. METHODS: A total of 952 patients at a single tertiary care institution who underwent anterior or posterior cervical decompression/fusion between 2007 and 2013 were retrospectively reviewed. Outcomes included postoperative emergency department visit or readmission within 30 d, reoperation within 90 d for infection, and changes in QOL outcomes. Nomograms were modeled based on patient demographics and surgical variables. Bootstrap was used for internal validation. RESULTS: Bias-corrected c-index for emergency department visits, readmission, and reoperation were 0.63, 0.78, and 0.91, respectively. For the QOL metrics, the bias-corrected adjusted R-squared was EQ-5D (EuroQOL): 0.43, for PHQ-9 (Patient Health Questionnaire-9): 0.35, and for PDQ (Pain/Disability Questionnaire): 0.47. Variables predicting the clinical outcomes varied, but included race and median income, body mass index, comorbidities, presenting symptoms, indication for surgery, surgery type, and levels. For the QOL nomograms, the predictors included similar variables, but were signifcantly more affected by the preoperative QOL of the patient. CONCLUSION: These prediction models enable referring physicians and spine surgeons to provide patients with personalized expectations regarding postoperative clinical and QOL outcomes following a cervical spine surgery. After appropriate validation, use of patientspecifc prediction tools, such as nomograms, has the potential to lead to superior spine surgery outcomes and more cost effective care.
AB - BACKGROUND: Clinical and quality of life (QOL) outcomes vary depending onthe patient's demographics, comorbidities, presenting symptoms, pathology, and surgical treatment used. While there have been individual predictors identifed, no comprehensive method incorporates a patient's complex clinical presentation to predict a specifc individual postoperative outcome. OBJECTIVE: To create tool that predicts patient-specifc outcomes among those undergoing cervical spine surgery. METHODS: A total of 952 patients at a single tertiary care institution who underwent anterior or posterior cervical decompression/fusion between 2007 and 2013 were retrospectively reviewed. Outcomes included postoperative emergency department visit or readmission within 30 d, reoperation within 90 d for infection, and changes in QOL outcomes. Nomograms were modeled based on patient demographics and surgical variables. Bootstrap was used for internal validation. RESULTS: Bias-corrected c-index for emergency department visits, readmission, and reoperation were 0.63, 0.78, and 0.91, respectively. For the QOL metrics, the bias-corrected adjusted R-squared was EQ-5D (EuroQOL): 0.43, for PHQ-9 (Patient Health Questionnaire-9): 0.35, and for PDQ (Pain/Disability Questionnaire): 0.47. Variables predicting the clinical outcomes varied, but included race and median income, body mass index, comorbidities, presenting symptoms, indication for surgery, surgery type, and levels. For the QOL nomograms, the predictors included similar variables, but were signifcantly more affected by the preoperative QOL of the patient. CONCLUSION: These prediction models enable referring physicians and spine surgeons to provide patients with personalized expectations regarding postoperative clinical and QOL outcomes following a cervical spine surgery. After appropriate validation, use of patientspecifc prediction tools, such as nomograms, has the potential to lead to superior spine surgery outcomes and more cost effective care.
KW - Cervical spine
KW - EQ-5D
KW - Modeling
KW - Nomogram
KW - Prediction tool
KW - Quality of life
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U2 - 10.1093/neuros/nyx343
DO - 10.1093/neuros/nyx343
M3 - Article
C2 - 29106662
AN - SCOPUS:85051355301
SN - 0148-396X
VL - 83
SP - 104
EP - 113
JO - Clinical neurosurgery
JF - Clinical neurosurgery
IS - 1
ER -