Neurosurg Focus
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Surgical 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. ⋯ The 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.
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External ventricular drains (EVDs) are commonly used in the neurosurgical population. However, very few pediatric neurosurgery studies are available regarding EVD-associated infection rates with antibiotic-impregnated EVD catheters. The authors previously published a large pediatric cohort study analyzing nonantibiotic-impregnated EVD catheters and risk factors associated with infections. In this study, they aimed to analyze the EVD-associated infection rate after implementation of antibiotic-impregnated EVD catheters. ⋯ In their large pediatric cohort, the authors demonstrated a significant decline in ventriculostomy-associated CSF infection rate after implementation of antibiotic-impregnated EVD catheters at their institution.
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The authors sought to identify the relevance between pneumocephalus and postoperative intracranial infections, as well as bacteriological characteristics and risk factors for intracranial infections, in patients with pituitary adenomas after endoscopic endonasal transsphenoidal surgery. ⋯ In pituitary adenoma patients who underwent pure endoscopic endonasal transsphenoidal surgeries, intraoperative saddle reconstruction has a crucial role for patients with postoperative intracranial infections. Additionally, postoperative pneumocephalus plays an important role in predicting intracranial infections that must not be neglected. Therefore, neurosurgeons should pay close attention to the discovery of postoperative intracranial pneumocephalus because this factor is as important as a postoperative CSF leak. Pneumocephalus (maximum bubble diameter of ≥ 1 cm), diaphragmatic defects (an intraoperative CSF leak, Kelly grade ≥ 1), and a postoperative CSF leak were risk factors predictive of postoperative intracranial infections. In addition, it is essential that operative procedures be carefully performed to avoid diaphragmatic defects, to reduce exposure to the external environment, and to decrease patients' suffering.