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Greater improvement in Neck Disability Index scores in women after surgery for cervical myelopathy: an analysis of the Quality Outcomes Database

Arati Patel, Sravani Kondapavulur, Gray Umbach, Andrew K. Chan, Vivian P. Le, Erica F. Bisson, Mohamad Bydon, Dean Chou, Steve D. Glassman, Kevin T. Foley, Christopher I. Shaffrey, Eric A. Potts, Mark E. Shaffrey, Domagoj Coric, John J. Knightly, Paul Park, Michael Y. Wang, Kai-Ming Fu, Jonathan Slotkin, Anthony L. Asher, Michael S. Virk, Regis W. Haid, Oren Gottfried, Scott Meyer, Cheerag D. Upadhyaya, Luis M. Tumialán, Jay D. Turner, and Praveen V. Mummaneni

OBJECTIVE

There is a high prevalence of cervical myelopathy that requires surgery; as such, it is important to identify how different groups benefit from surgery. The American Association of Neurological Surgeons launched the Quality Outcomes Database (QOD), a prospective longitudinal registry, that includes demographic, clinical, and patient-reported outcome data to measure the safety and quality of neurosurgical procedures. In this study, the authors assessed the impact of gender on patient-reported outcomes in patients who underwent surgery for cervical myelopathy.

METHODS

The authors analyzed 1152 patients who underwent surgery for cervical myelopathy and were included in the QOD cervical module. Univariate comparison of baseline patient characteristics between males and females who underwent surgery for cervical spondylotic myelopathy was performed. Baseline characteristics that significantly differed between males and females were included in a multivariate generalized linear model comparing baseline and 1-year postoperative Neck Disability Index (NDI) scores.

RESULTS

This study included 546 females and 604 males. Females demonstrated significantly greater improvement in NDI score 1 year after surgery (p = 0.036). In addition to gender, the presence of axial neck pain and insurance status were also significantly predictive of improvement in NDI score after surgery (p = 0.0013 and p = 0.0058, respectively).

CONCLUSIONS

Females were more likely to benefit from surgery for cervical myelopathy compared with males. It is important to identify gender differences in postoperative outcomes after surgery in order to deliver more personalized and patient-centric care.

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Which supervised machine learning algorithm can best predict achievement of minimum clinically important difference in neck pain after surgery in patients with cervical myelopathy? A QOD study

Christine Park, Praveen V. Mummaneni, Oren N. Gottfried, Christopher I. Shaffrey, Anthony J. Tang, Erica F. Bisson, Anthony L. Asher, Domagoj Coric, Eric A. Potts, Kevin T. Foley, Michael Y. Wang, Kai-Ming Fu, Michael S. Virk, John J. Knightly, Scott Meyer, Paul Park, Cheerag Upadhyaya, Mark E. Shaffrey, Avery L. Buchholz, Luis M. Tumialán, Jay D. Turner, Brandon A. Sherrod, Nitin Agarwal, Dean Chou, Regis W. Haid Jr., Mohamad Bydon, and Andrew K. Chan

OBJECTIVE

The purpose of this study was to evaluate the performance of different supervised machine learning algorithms to predict achievement of minimum clinically important difference (MCID) in neck pain after surgery in patients with cervical spondylotic myelopathy (CSM).

METHODS

This was a retrospective analysis of the prospective Quality Outcomes Database CSM cohort. The data set was divided into an 80% training and a 20% test set. Various supervised learning algorithms (including logistic regression, support vector machine, decision tree, random forest, extra trees, gaussian naïve Bayes, k–nearest neighbors, multilayer perceptron, and extreme gradient boosted trees) were evaluated on their performance to predict achievement of MCID in neck pain at 3 and 24 months after surgery, given a set of predicting baseline features. Model performance was assessed with accuracy, F1 score, area under the receiver operating characteristic curve, precision, recall/sensitivity, and specificity.

RESULTS

In total, 535 patients (46.9%) achieved MCID for neck pain at 3 months and 569 patients (49.9%) achieved it at 24 months. In each follow-up cohort, 501 patients (93.6%) were satisfied at 3 months after surgery and 569 patients (100%) were satisfied at 24 months after surgery. Of the supervised machine learning algorithms tested, logistic regression demonstrated the best accuracy (3 months: 0.76 ± 0.031, 24 months: 0.773 ± 0.044), followed by F1 score (3 months: 0.759 ± 0.019, 24 months: 0.777 ± 0.039) and area under the receiver operating characteristic curve (3 months: 0.762 ± 0.027, 24 months: 0.773 ± 0.043) at predicting achievement of MCID for neck pain at both follow-up time points, with fair performance. The best precision was also demonstrated by logistic regression at 3 (0.724 ± 0.058) and 24 (0.780 ± 0.097) months. The best recall/sensitivity was demonstrated by multilayer perceptron at 3 months (0.841 ± 0.094) and by extra trees at 24 months (0.817 ± 0.115). Highest specificity was shown by support vector machine at 3 months (0.952 ± 0.013) and by logistic regression at 24 months (0.747 ± 0.18).

CONCLUSIONS

Appropriate selection of models for studies should be based on the strengths of each model and the aims of the studies. For maximally predicting true achievement of MCID in neck pain, of all the predictions in this balanced data set the appropriate metric for the authors’ study was precision. For both short- and long-term follow-ups, logistic regression demonstrated the highest precision of all models tested. Logistic regression performed consistently the best of all models tested and remains a powerful model for clinical classification tasks.

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Defining the minimum clinically important difference for grade I degenerative lumbar spondylolisthesis: insights from the Quality Outcomes Database

Anthony L. Asher, Panagiotis Kerezoudis, Praveen V. Mummaneni, Erica F. Bisson, Steven D. Glassman, Kevin T. Foley, Jonathan R. Slotkin, Eric A. Potts, Mark E. Shaffrey, Christopher I. Shaffrey, Domagoj Coric, John J. Knightly, Paul Park, Kai-Ming Fu, Clinton J. Devin, Kristin R. Archer, Silky Chotai, Andrew K. Chan, Michael S. Virk, and Mohamad Bydon

OBJECTIVE

Patient-reported outcomes (PROs) play a pivotal role in defining the value of surgical interventions for spinal disease. The concept of minimum clinically important difference (MCID) is considered the new standard for determining the effectiveness of a given treatment and describing patient satisfaction in response to that treatment. The purpose of this study was to determine the MCID associated with surgical treatment for degenerative lumbar spondylolisthesis.

METHODS

The authors queried the Quality Outcomes Database registry from July 2014 through December 2015 for patients who underwent posterior lumbar surgery for grade I degenerative spondylolisthesis. Recorded PROs included scores on the Oswestry Disability Index (ODI), EQ-5D, and numeric rating scale (NRS) for leg pain (NRS-LP) and back pain (NRS-BP). Anchor-based (using the North American Spine Society satisfaction scale) and distribution-based (half a standard deviation, small Cohen’s effect size, standard error of measurement, and minimum detectable change [MDC]) methods were used to calculate the MCID for each PRO.

RESULTS

A total of 441 patients (80 who underwent laminectomies alone and 361 who underwent fusion procedures) from 11 participating sites were included in the analysis. The changes in functional outcome scores between baseline and the 1-year postoperative evaluation were as follows: 23.5 ± 17.4 points for ODI, 0.24 ± 0.23 for EQ-5D, 4.1 ± 3.5 for NRS-LP, and 3.7 ± 3.2 for NRS-BP. The different calculation methods generated a range of MCID values for each PRO: 3.3–26.5 points for ODI, 0.04–0.3 points for EQ-5D, 0.6–4.5 points for NRS-LP, and 0.5–4.2 points for NRS-BP. The MDC approach appeared to be the most appropriate for calculating MCID because it provided a threshold greater than the measurement error and was closest to the average change difference between the satisfied and not-satisfied patients. On subgroup analysis, the MCID thresholds for laminectomy-alone patients were comparable to those for the patients who underwent arthrodesis as well as for the entire cohort.

CONCLUSIONS

The MCID for PROs was highly variable depending on the calculation technique. The MDC seems to be a statistically and clinically sound method for defining the appropriate MCID value for patients with grade I degenerative lumbar spondylolisthesis. Based on this method, the MCID values are 14.3 points for ODI, 0.2 points for EQ-5D, 1.7 points for NRS-LP, and 1.6 points for NRS-BP.

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Women fare best following surgery for degenerative lumbar spondylolisthesis: a comparison of the most and least satisfied patients utilizing data from the Quality Outcomes Database

Andrew K. Chan, Erica F. Bisson, Mohamad Bydon, Steven D. Glassman, Kevin T. Foley, Eric A. Potts, Christopher I. Shaffrey, Mark E. Shaffrey, Domagoj Coric, John J. Knightly, Paul Park, Kai-Ming Fu, Jonathan R. Slotkin, Anthony L. Asher, Michael S. Virk, Panagiotis Kerezoudis, Silky Chotai, Anthony M. DiGiorgio, Alvin Y. Chan, Regis W. Haid, and Praveen V. Mummaneni

OBJECTIVE

The American Association of Neurological Surgeons launched the Quality Outcomes Database (QOD), a prospective longitudinal registry that includes demographic, clinical, and patient-reported outcome (PRO) data, to measure the safety and quality of neurosurgical procedures, including spinal surgery. Differing results from recent randomized controlled trials have established a need to clarify the groups that would most benefit from surgery for degenerative lumbar spondylolisthesis. In the present study, the authors compared patients who were the most and the least satisfied following surgery for degenerative lumbar spondylolisthesis.

METHODS

This was a retrospective analysis of a prospective, national longitudinal registry including patients who had undergone surgery for grade 1 degenerative lumbar spondylolisthesis. The most and least satisfied patients were identified based on an answer of “1” and “4,” respectively, on the North American Spine Society (NASS) Satisfaction Questionnaire 12 months postoperatively. Baseline demographics, clinical variables, surgical parameters, and outcomes were collected. Patient-reported outcome measures, including the Numeric Rating Scale (NRS) for back pain, NRS for leg pain, Oswestry Disability Index (ODI), and EQ-5D (the EuroQol health survey), were administered at baseline and 3 and 12 months after treatment.

RESULTS

Four hundred seventy-seven patients underwent surgery for grade 1 degenerative lumbar spondylolisthesis in the period from July 2014 through December 2015. Two hundred fifty-five patients (53.5%) were the most satisfied and 26 (5.5%) were the least satisfied. Compared with the most satisfied patients, the least satisfied ones more often had coronary artery disease (CAD; 26.9% vs 12.2%, p = 0.04) and had higher body mass indices (32.9 ± 6.5 vs 30.0 ± 6.0 kg/m2, p = 0.02). In the multivariate analysis, female sex (OR 2.9, p = 0.02) was associated with the most satisfaction. Notably, the American Society of Anesthesiologists (ASA) class, smoking, psychiatric comorbidity, and employment status were not significantly associated with satisfaction. Although there were no significant differences at baseline, the most satisfied patients had significantly lower NRS back and leg pain and ODI scores and a greater EQ-5D score at 3 and 12 months postoperatively (p < 0.001 for all).

CONCLUSIONS

This study revealed that some patient factors differ between those who report the most and those who report the least satisfaction after surgery for degenerative lumbar spondylolisthesis. Patients reporting the least satisfaction tended to have CAD or were obese. Female sex was associated with the most satisfaction when adjusting for potential covariates. These findings highlight several key factors that could aid in setting expectations for outcomes following surgery for degenerative lumbar spondylolisthesis.

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Abstracts of the 2015 Annual Meeting of the AANS/CNS Section on Disorders of the Spine and Peripheral Nerves Phoenix, Arizona • March 4–7, 2015

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Abstracts of the 2017 AANS/CNS Joint Section on Disorders of the Spine and Peripheral Nerves Las Vegas, Nevada • March 8–11, 2017

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Abstracts of the 10th Annual Meeting of the Lumbar Spine Research Society Chicago, Illinois • April 6 & 7, 2017