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Could Machine Learning Better Predict Postoperative C5 Palsy of Cervical Ossification of the Posterior Longitudinal
Soo Heon Kim1, Sun Ho Lee2, Dong Ah Shin1
1Department of Neurosurgery, Yonsei University College of Medicine.
Study Design:
This was a retrospective cohort study.
Objective:
The objective of this study was to investigate whether machine learning (ML) can perform better than a conventional logistic regression in predicting postoperative C5 palsy of cervical ossification of the posterior longitudinal ligament (OPLL) patients.
Summary Of Background Data:
C5 palsy is one of the most common postoperative complications after surgical treatment of OPLL, with an incidence rate of 1.4%-18.4%. ML has recently been used to predict the outcomes of neurosurgery. To our knowledge there has not been a study to predict postoperative C5 palsy of cervical OPLL patient with ML.
Methods:
Four sampling methods were used for data balancing. Six ML algorithms and conventional logistic regression were used for model development. A total of 35 ML prediction model and 5 conventional logistic prediction models were generated. The performances of each model were compared with the area under the curve (AUC). Patients who underwent surgery for cervical OPLL at our institute from January 1998 to January 2012 were reviewed. Twenty-five variables of each patient were used to make a prediction model.
Results:
In total, 901 patients were included [651 male and 250 female, median age: 55 (49-63), mean±SD: 55.9±9.802]. Twenty-six (2.8%) patients developed postoperative C5 palsy. Age (P=0.043), surgical method (P=0.0112), involvement of OPLL at C1-3 (P=0.0359), and postoperative shoulder pain (P≤0.001) were significantly associated with C5 palsy. Among all ML models, a model using an adaptive reinforcement learning algorithm and downsampling showed the largest AUC (0.88; 95% confidence interval: 0.79-0.96), better than that of logistic regression (0.69; 95% confidence interval: 0.43-0.94).
Conclusions:
The ML algorithm seems to be superior to logistic regression for predicting postoperative C5 palsy of OPLL patient after surgery with respect to AUC. Age, surgical method, and involvement of OPLL at C1-C3 were significantly associated with C5 palsy. This study demonstrates that shoulder pain immediately after surgery is closely associated with postoperative C5 palsy of OPLL patient.
