OBJECTIVESurgical site infection (SSI) following a neurosurgical operation is a complication that impacts morbidity, mortality, and economics. Currently, machine learning (ML) algorithms are used for outcome prediction in various neurosurgical aspects. The implementation of ML algorithms to learn from medical data may help in obtaining prognostic information on diseases, especially SSIs. The purpose of this study was to compare the performance of various ML models for predicting surgical infection after neurosurgical operations.METHODSA retrospective cohort study was conducted on patients who had undergone neurosurgical operations at tertiary care hospitals between 2010 and 2017. Supervised ML algorithms, which included decision tree, naive Bayes with Laplace correction, k-nearest neighbors, and artificial neural networks, were trained and tested as binary classifiers (infection or no infection). To evaluate the ML models from the testing data set, their sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), as well as their accuracy, receiver operating characteristic curve, and area under the receiver operating characteristic curve (AUC) were analyzed.RESULTSData were available for 1471 patients in the study period. The SSI rate was 4.6%, and the type of SSI was superficial, deep, and organ/space in 1.2%, 0.8%, and 2.6% of cases, respectively. Using the backward stepwise method, the authors determined that the significant predictors of SSI in the multivariable Cox regression analysis were postoperative CSF leakage/subgaleal collection (HR 4.24, p < 0.001) and postoperative fever (HR 1.67, p = 0.04). Compared with other ML algorithms, the naive Bayes had the highest performance with sensitivity at 63%, specificity at 87%, PPV at 29%, NPV at 96%, and AUC at 76%.CONCLUSIONSThe naive Bayes algorithm is highlighted as an accurate ML method for predicting SSI after neurosurgical operations because of its reasonable accuracy. Thus, it can be used to effectively predict SSI in individual neurosurgical patients. Therefore, close monitoring and allocation of treatment strategies can be informed by ML predictions in general practice.

Background Prognosis of low-grade glioma are currently determined by genetic markers that are limited in some countries. This study aimed to use clinical parameters to develop a nomogram to predict survival of patients with diffuse astrocytoma (DA) which is the most common type of low-grade glioma. Materials and Methods Retrospective data of adult patients with DA from three university hospitals in Thailand were analyzed. Collected data included clinical characteristics, neuroimaging findings, treatment, and outcomes. Cox's regression analyses were performed to determine associated factors. Significant associated factors from the Cox regression model were subsequently used to develop a nomogram for survival prediction. Performance of the nomogram was then tested for its accuracy. Results There were 64 patients with DA with a median age of 39.5 (interquartile range [IQR] = 20.2) years. Mean follow-up time of patients was 42 months (standard deviation [SD] = 34.3). After adjusted for three significant factors associated with survival were age ≥60 years (hazard ratio [HR] = 5.8; 95% confidence interval [CI]: 2.09-15.91), motor response score of Glasgow coma scale < 6 (HR = 75.5; 95% CI: 4.15-1,369.4), and biopsy (HR = 0.45; 95% CI: 0.21-0.92). To predict 1-year mortality, sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and area under the curve our nomogram was 1.0, 0.50, 0.45, 1.0, 0.64, and 0.75, respectively. Conclusions This study provided a nomogram predicting prognosis of DA. The nomogram showed an acceptable performance for predicting 1-year mortality. AbstractKeywords ► diffuse astrocytoma ► nomogram ► survival analysis

Background: Primary spinal cord oligodendroglioma is extremely rare. In an extensive review of this disease, 53 cases were reported. Furthermore, the authors summarize the characteristics of the primary spinal cord oligodendroglioma; chronological presentation , neurological imaging, treatment and the outcome obtained in the present case as well as review the literature. Case Presentation: A 46-year-old male who had progressive neck pain for a year. Magnetic resonance imaging showed an intramedullary mass from level C2 to T4. A radical resection was performed. Histology revealed oligodendroglioma. Thereafter, the patient was treated with adjuvant radiotherapy. A year later, tumor developed recurrence. The patinet died in 3 years and 6 months. Conclusions: The available data of this disease was limited. Base on 11 published papers and the present case, surgical resection is the treatment of choice although recurrence of the tumor tends to occur after partial resection with or without radiotherapy. From the literature, the management of the recurrent disease is still surgery. Moreover, Temozolomide may be an advantage in recurrent situations.

Hemangiomas have rarely been found in the spinal cord. A few cases of spinal capillary hemangioma have been reported since 1987. The authors reported the two cases of capillary hemangioma including the tumor at conus medullaris and the another mimicked von Hippel-Lindau disease. A 15-year-old man was presented with coccydynia and left leg pain. A magnetic resonance imaging (MRI) revealed an intradural extramedullary enhancing mass at conus medullaris. Another case, a 31-year-old man was presented with a history of familial history of brain tumor, retinal hemangioma both eyes, multiple pancreatic cyst and syringobulbia with syringohydromyelia. On MRI, a well-circumscribed intramedullary nodule was detected at C5-6 level and multiple subpial nodule along cervicothoracic spinal cord. All patients underwent surgery, and the histological diagnosis confirmed capillary hemangioma. Although rare and indistinguishable from other tumors, capillary hemangioma should be in the differential diagnosis of the spinal cord tumor.

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Objective: The authors aimed to evaluate the necessity of in-hospital neurological observation for mild traumatic brain injury (TBI) patients, who did not have any evidence of intracranial injury from initial computed tomography (CT) brain scans. Material and Methods: We retrospectively reviewed mild TBI patients with initial negative CT brain scans, receiving treatment at Songklanagarind hospital between January and December, 2018. All patients were observed in the emergency department short stay observation unit for 24 hours after injury. Patients’ medical records, initial and official CT brain scan interpretation were collected and analyzed. Results: This study included 493 cases. No patient deteriorated from intracranial injury, while one patient deteriorated from hypoglycemia, associated with his underlying adrenal insufficiency. However, one patient was admitted to the in patient ward, due to a missed diagnosis of acute subdural hematoma from his initial CT interpretation. The incidence of missed intracranial injury from initial CT brain scan interpretation was 1.6%. The need for neurosurgical intervention (in-patient ward admission, anticonvulsant and repeat brain imaging) was 0.2% (1/493). No patient required surgical intervention.Conclusion: Mild TBI patients, with initial negative CT brain scans, have very low risk for deterioration or need of neurosurgical intervention. Patient's underlying major comorbidity may be considered as an indication for in-hospital observation.

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Background:With the advancement of neuronavigation technologies, frameless stereotactic brain biopsy has been developed. Previous studies proved that frameless stereotactic brain biopsy was as effective and safe as frame-based stereotactic brain biopsy. The authors aimed to find the factors associated with diagnostic yield and complication rate of frameless intracranial biopsy.Materials and Methods:Frameless stereotactic brain biopsy procedures, between March 2009 and April 2017, were retrospectively reviewed from medical records including imaging studies. Using logistic regression analysis, various factors were analyzed for association with diagnostic yield and postoperative complications.Results:Eighty-nine frameless stereotactic brain biopsy procedures were performed on 85 patients. The most common pathology was primary central nervous system lymphoma (43.8%), followed by low-grade glioma (15.7%), and high-grade glioma (15%), respectively. The diagnostic yield was 87.6%. Postoperative intracerebral hematoma occurred in 19% of cases; however, it was symptomatic in only one case. The size of the lesion was associated with both diagnostic yield and postoperative intracerebral hematoma complication. Lesions, larger than 3 cm in diameter, were associated with a higher rate of positive biopsy result (P = 0.01). Lesion 3 cm or smaller than 3 cm in diameter, and intraoperative bleeding associated with a higher percentage of postoperative intracerebral hematoma complications (P = 0.01).Conclusions:For frameless stereotactic brain biopsy, the size of the lesion is the essential factor determining diagnostic yield and postoperative intracerebral hematoma complication.