Neurosurgery
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Deep learning (DL) is a powerful machine learning technique that has increasingly been used to predict surgical outcomes. However, the large quantity of data required and lack of model interpretability represent substantial barriers to the validity and reproducibility of DL models. The objective of this study was to systematically review the characteristics of DL studies involving neurosurgical outcome prediction and to assess their bias and reporting quality. ⋯ The use of DL for neurosurgical outcome prediction remains nascent. Lack of appropriate data sets poses a major concern for bias. Although studies have demonstrated promising results, greater transparency in model development and reporting is needed to facilitate reproducibility and validation.
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Increases in the extent of resection of both contrast-enhanced (CE) and non-contrast-enhanced (NCE) tissue are associated with substantial survival benefits in patients with isocitrate dehydrogenase wild-type glioblastoma. The fact, however, remains that these lesions exist within the framework of complex neural circuitry subserving cognition, movement, and behavior, all of which affect the ultimate survival outcome. The prognostic significance of the interplay between CE and NCE cytoreduction and neurological morbidity is poorly understood. ⋯ Our data provide novel evidence for management strategies that prioritize safe and complete resection of CE tissue.
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Comparative effectiveness research has a vital role in recent health reform and policies. Specialty training is one of these provider-side variables, and surgeons who were trained in different specialties may have different outcomes on performing the same procedure. ⋯ Our analysis found significant differences in early perioperative outcomes of patients undergoing ACDF by neurosurgeons and orthopedic surgeons. These differences might have significant clinical and cost implications for patients, physicians, program directors, payers, and health systems.
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Malignant cerebral edema (MCE) and intracranial hemorrhage (ICH) are associated with poor neurological outcomes despite revascularization after mechanical thrombectomy (MT). The factors associated with the development of MCE and ICH after MT are not well understood. ⋯ Elevated iSGR significantly increases the risk of MCE and ICH and is an independent predictor of poor functional outcome. Thrombolysis in cerebral infarction 2C/3 revascularization is associated with reduced risk of MCE, ICH, and poor functional outcome. Whether stress hyperglycemia represents a modifiable risk factor is uncertain, and further investigation is warranted.