Object The purpose of this study was to develop an artificial neural network (ANN) model for predicting 2-year surgical satisfaction, and to compare the new model with traditional predictive tools in patients with lumbar spinal canal stenosis. Methods The 2 prediction models included an ANN and a logistic regression (LR) model. The patient age, sex, duration of symptoms, walking distance, visual analog scale scores of leg pain or numbness, the Japanese Orthopaedic Association score, the Neurogenic Claudication Outcome Score, and the stenosis ratio values were determined as the input variables for the ANN and LR models that were developed. Patient surgical satisfaction was recorded using a standardized measure. The ANNs were fed patient data to predict 2-year surgical satisfaction based on several input variables. Sensitivity analysis was applied to the ANN model to identify the important variables. The receiver operating characteristic–area under curve (ROC-AUC), Hosmer-Lemeshow statistics, and accuracy rate were calculated for evaluating the 2 models. Results A total of 168 patients (59 male, 109 female; mean age 59.8 ± 11.6 years) were divided into training (n = 84), testing (n = 42), and validation (n = 42) data sets. Postsurgical satisfaction was 88.7% at 2-year follow-up. The stenosis ratio was the important variable selected by the ANN. The ANN model displayed a better accuracy rate in 96.9% of patients, a better Hosmer-Lemeshow statistic in 42.4% of patients, and a better ROC-AUC in 80% of patients, compared with the LR model. Conclusions The findings show that an ANN can predict 2-year surgical satisfaction for use in clinical application and is more accurate compared with an LR model.

Artificial neural networks (ANNs) effectively analyze non-linear data sets. The aimed was A review of the relevant published articles that focused on the application of ANNs as a tool for assisting clinical decision-making in neurosurgery. A literature review of all full publications in English biomedical journals (1993-2013) was undertaken. The strategy included a combination of key words 'artificial neural networks', 'prognostic', 'brain', 'tumor tracking', 'head', 'tumor', 'spine', 'classification' and 'back pain' in the title and abstract of the manuscripts using the PubMed search engine. The major findings are summarized, with a focus on the application of ANNs for diagnostic and prognostic purposes. Finally, the future of ANNs in neurosurgery is explored. A total of 1093 citations were identified and screened. In all, 57 citations were found to be relevant. Of these, 50 articles were eligible for inclusion in this review. The synthesis of the data showed several applications of ANN in neurosurgery, including: (1) diagnosis and assessment of disease progression in low back pain, brain tumours and primary epilepsy; (2) enhancing clinically relevant information extraction from radiographic images, intracranial pressure processing, low back pain and real-time tumour tracking; (3) outcome prediction in epilepsy, brain metastases, lumbar spinal stenosis, lumbar disc herniation, childhood hydrocephalus, trauma mortality, and the occurrence of symptomatic cerebral vasospasm in patients with aneurysmal subarachnoid haemorrhage; (4) the use in the biomechanical assessments of spinal disease. ANNs can be effectively employed for diagnosis, prognosis and outcome prediction in neurosurgery.

The findings show that an ANNs can be used to predict the diagnostic statues of recurrent and nonrecurrent group of LDH patients before the first or index microdiscectomy.

Various factors related to predict surgical success were studied; however, a standard cut-off point for the Pain Sensitivity Questionnaire (PSQ) measure has not yet been established for a favorable surgical outcome for lumbar disc herniation (LDH). This study was to find the optimal cut-off point on the PSQ to distinguish surgical success in patients with LDH. A total of 154 patients with LDH consecutively referred to our clinic were enrolled into this prospective study between February 2011 and January 2014. All participants completed the PSQ. Patients completed the Oswestry Disability Index (ODI) score before surgery, and at 2 years after surgery. Surgical success was defined as a 13-point improvement from the baseline ODI scores. The cut-off value for PSQ was determined by the receiver-operating characteristic curve (ROC). The mean age of patients was 49.3±9.6 years, and there were 80 women. The mean time for follow-up assessment was 31±5 months (range 24–35). Post-surgical success was 79.9% (n = 123) at 2 years follow up. The mean score for the total PSQ, PSQ-minor, and PSQ-moderate were 6.0 (SD = 1.6), 5.4 (SD = 1.9) and 6.5 (SD = 1.7), respectively. Total PSQ score was also significantly correlated with the total scores of the ODI. The optimal total PSQ cut-off point was determined as > 5.2 to predict surgical success in LDH patients, with 80.0% sensitivity and 75.6% specificity (AUC-0.814, 95% CI 0.703–0.926). This study showed that the PSQ could be considered a parameter for predicting surgical success in patients with LDH, and can be useful in clinical practice.

Background: To prospectively explore the incidence and risk factors for postoperative delirium in elderly patients following lumbar spine surgery.Methods: This prospective study enrolled 148 consecutive patients over the age of 65 who were scheduled to undergo spine surgery. Patients were screened for delirium using the short Confusion Assessment Method (CAM) postoperatively. Patient demographics and relevant medical information were collected. Logistic regression analysis was used to identify the risk factors associated with postoperative delirium.Results: Eighty-three patients (56.1%) who underwent lumbar spine surgery (not coexisting with cervical or thoracic spine surgery) were enrolled in our study. Post-operative delirium was noted in 14.5% of patients over 65 years old. The presence of preoperative Parkinsonism was significantly higher in the delirium group (41.7% vs. 8.5%, P=0.002), as was a higher preoperative C-reactive protein (CRP) (7.0±15.2 vs. 1.3±2.3 mg/L, P=0.017) when compared with the non-delirium group. Of the risk factors, male sex [odds ratio (OR) =0.10, 95% confidence interval (CI): 0.01-0.66, P=0.017], Parkinsonism (OR =5.83, 95% CI: 1.03-32.89, P=0.046), and lower baseline MMSE score (OR =0.71, 95% CI: 0.52-0.97, P=0.032) were independently associated with postoperative delirium in elderly patients undergoing lumbar spine surgery.Conclusions: Post-operative delirium occurred in 14.5% of elderly patients who underwent lumbar spine surgery. Male sex, Parkinsonism, and lower baseline MMSE score were identified as independent risk factors for postoperative delirium in elderly patients following lumbar surgery.

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Study DesignCross-sectional.PurposeTo develop a strategy to determine a sound method for decision-making based on postoperative clinical outcome satisfaction.Overview of LiteratureThe ideal management of thoracolumbar and lumbar burst fractures (TLBF) without neurological compromise remains controversial.MethodsThis was a prospective study. Patients with thoracolumbar injury severity and classification score (TLICS) <4 were treated nonoperatively, with bed rest and bracing until the pain decreased sufficiently to allow mobilization. Surgery was undertaken in patients with intractable pain despite an appropriate nonoperative treatment (surgery group). The Oswestry disability index (ODI) measure was observed at baseline and at the last follow-up. Clinically success was defined at least a 30% improvement from the baseline ODI scores in both the conservative and surgery groups. All case records were assessed for gender, age, residual canal and angulations at the site of the fracture in order to determine which patients benefited from surgery or conservative treatment and which did not.ResultsIn all 113 patients with T11–L5, TLBFs were treated. The patients' mean age was 49.2 years. Patients successfully completed either nonoperative (n=99) or surgical (n=14) treatment based on ODI. Clinical examinations revealed that all of the patients had intact neurology. The mean follow-up period was 29.5 months. There was a significant difference between the two groups based on age and residual canal. The mean ODI score significantly improved for both groups (p <0.01). According to the findings, a decision matrix was proposed.ConclusionsThe findings confirm that TLICS <4, age, and residual canal can be used to guide the treatment of TLBF in conservative decision-making.

Study DesignCross-sectional.PurposeTo translate and culturally adapt an Iranian version of the Pain Sensitivity Questionnaire (PSQ) in Iran.Overview of LiteratureInstruments measuring patient reported outcomes should satisfy certain psychometric properties.MethodsThe PSQ was translated following cross-cultural adaptation guidelines. A total of 101 patients with lumbar disc herniation (LDH), and 39 healthy cases were included in the study. All participants completed the PSQ and the Pain Catastrophizing Scale (PCS). The internal consistency, test-retest reliability, known group comparison, criterion validity and item-scale correlations were assessed.ResultsThe mean age of participants was 51.7 years. Reliability, validity and correlation of PSQ and PCS showed satisfactory results. Cronbach's alpha coefficients were 0.81 for PSQ-total, 0.82 for PSQ-minor, and 0.82 for PSQ-moderate. The intraclass correlation coefficients value was 0.84 (0.616–0.932) indicating an excellent test-retest reliability. The instrument discriminated well between sub-groups of patients who differed in a standard predictive measure of LDH surgery (the Finneson–Cooper score). Total PSQ were also significantly correlated with the total scores of the PCS, lending support to its good convergent validity. Additionally, the correlation of each item with its hypothesized domain on the PSQ indicated acceptable results, suggesting that the items had a substantial relationship with their own domains.ConclusionsThe adapted Iranian PSQ is a valid and reliable questionnaire for the assessment of pain in patients with LDH.