Surgical site infection (SSI) following a neurosurgical operation is complication that impacts morbidity, mortality, and economics. Currently, machine learning (ML) algorithms are used for outcome prediction in various aspects. The implementation of ML to learn from medical data may help obtaining prognostic information on diseases, especially SSIs. purpose this study was compare the performance models predicting surgical after operations.A retrospective cohort conducted patients who had...

Traumatic brain injury (TBI) generally causes mortality and disability, particularly in children. Machine learning (ML) is a computer algorithm, applied as clinical prediction tool. The present study aims to assess the predictability of ML for functional outcomes pediatric TBI. A retrospective cohort was performed targeting children with TBI who were admitted trauma center southern Thailand between January 2009 July 2020. patient excluded if he/she (1) did not undergo CT scan brain, (2) died...

Multiple, primary brain tumors with different histological types occurring in the same patient are extremely rare. Several hypotheses have been proposed, and pathophysiology of coexisting has long debated; however, due to low incidence, standard practices for this scenario still inconclusive.The authors describe 6 cases tumors. By conducting a literature research focused on computed tomography (CT) era patients without prior radiation or phakomatosis. Sixty-five such reported were...

With the advancement of neuronavigation technologies, frameless stereotactic brain biopsy has been developed. Previous studies proved that was as effective and safe frame-based biopsy. The authors aimed to find factors associated with diagnostic yield complication rate intracranial biopsy.Frameless procedures, between March 2009 April 2017, were retrospectively reviewed from medical records including imaging studies. Using logistic regression analysis, various analyzed for association...

Globally, blood donation has been disturbed due to the pandemic. Consequently, optimization of preoperative preparation should be a point concern. Machine learning (ML) is one modern approaches that have applied by physicians help decision-making. The main objective this study was identify cost differences ML-based strategy compared with other strategies in products preparation. A secondary compare effectiveness indexes among strategies.The utilized retrospective cohort design conducted on...

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 intracranial from initial computed tomography (CT) scans. Material and Methods: We retrospectively reviewed TBI patients with negative CT scans, receiving treatment at Songklanagarind hospital between January December, 2018. All were observed in emergency department short stay unit 24 hours after injury. Patients’ medical...

Hemangiomas have rarely been found in the spinal cord. A few cases of capillary hemangioma reported since 1987. The authors two including tumor at conus medullaris and another mimicked von Hippel-Lindau disease. 15-year-old man was presented with coccydynia left leg pain. magnetic resonance imaging (MRI) revealed an intradural extramedullary enhancing mass medullaris. Another case, a 31-year-old history familial brain tumor, retinal both eyes, multiple pancreatic cyst syringobulbia...

Abstract Background Prognosis of low-grade glioma are currently determined by genetic markers that limited in some countries. This study aimed to use clinical parameters develop a nomogram predict survival patients with diffuse astrocytoma (DA) which is the most common type glioma. Materials and Methods Retrospective data adult DA from three university hospitals Thailand were analyzed. Collected included characteristics, neuroimaging findings, treatment, outcomes. Cox’s regression analyses...

Genomic-based tools have been used to predict poor prognosis high-grade glioma (HGG). As genetic technologies are not generally available in countries with limited resources, clinical parameters may be still necessary use predicting the of disease. This study aimed identify prognostic factors associated survival patients HGG. We also proposed a validated nomogram using HGG.A multicenter retrospective was conducted who were diagnosed anaplastic astrocytoma (WHO III) or glioblastoma IV)....

The pathologies implicate the bilateral corpus callosum that builds butterfly pattern on axial view. These tumors have seldom been investigated for both clinical manifestations and outcome.The objective of this study was to describe characteristics outcomes tumor identify predictive factors associated with survival outcome.A retrospective 50 conducted between 2003 2016. characteristics, imaging, outcome were assessed purpose descriptive analysis. Using Kaplan-Meier method, median overall...

Background: Glioblastoma (GBM) is the poorest prognosis for a malignant brain tumor; however, postoperative chemoradiotherapy has been reported to improve survival time. Therefore, high-cost treatment prolonged time led health, economic burden, and catastrophic costs in limited-resource setting. Various immune-nutritional indexes can indicate patient status; both nutritional inflammatory status may help predict prognosis. The primary objective was evaluate prognostication of GBM patients....

Background: Glioblastoma (GBM) is the poorest prognosis in glioma. Although Temozolomide (TMZ) with radiotherapy following tumor resection currently standard treatment, high cost has become an economic burden a limited-resource setting. In era of disruptive innovation, machine learning (ML) been recently performed to be clinical prediction tool for prognostication, especially GBM. The aim study was assess predictability ML algorithms 2-year survival patients Methods: A retrospective cohort...

Traumatic brain injury (TBI) in children has become the major cause of mortality and morbidity Thailand that had an impact with economic consequences. This study aimed to develop internally validate a nomogram for 6-month follow-up outcome prediction moderate or severe pediatric TBI.This retrospective cohort involved 104 TBI. Various clinical variables were reviewed. The functional was assessed at hospital discharge based on King's Outcome Scale Childhood Head Injury classification....

OBJECTIVE Traumatic cerebrovascular injury (TCVI) is a rare and serious complication of traumatic brain (TBI). Various forms TCVIs have been reported, including occlusions, arteriovenous fistulas, pseudoaneurysms, transections. They can present at variety intervals after TBI may manifest as sudden episodes, progressive symptoms, even delayed fatal events. The purpose this study was to analyze cases TCVI identified single institution further explore types characteristics these complications...

Listeria monocytogenes (L. monocytogenes) infection is a rare cause of meningoencephalitis. Brain abscess represents only 1–10% central nervous system (CNS) manifestations. The typical magnetic resonance image (MRI) the brain finding ring enhancement after contrast administration. No previous study reported an atypical MRI from this that mimics migratory worm such as sparganosis in tunnel sign and bead-like serpiginous tubular lesion. Thus we report 36-year-old female patient with systemic...

Background: Glioblastoma is an aggressive primary brain tumor with a poor prognosis. At present, time-to-event machine learning (ML) approaches have been used for prognostication in neuro-oncology. The present study aimed to compare the predictive performances among Cox hazard regression, parametric survival and ML algorithms. In addition, secondary objective was deploy personalized curve each patient’s condition.