Neurosurgery
-
Low- and middle-income countries (LMICs) face higher incidences and burdens of care for neural tube defects (NTDs) and hydrocephalus compared with high-income countries (HICs), in part due to limited access to neurosurgical intervention. In this scoping review, we aim to integrate studies on prenatal care, counseling, and surgical management for families of children with spinal dysraphism and hydrocephalus in LMICs and HICs. ⋯ NTDs have become a widely acknowledged public health problem in many LMICs. Prenatal counseling and care and folate fortification are critical in the prevention of spinal dysraphism. However, high-quality, standardized studies reporting their epidemiology, prevention, and management remain scarce. Compared with NTDs, research on the prevention and screening of hydrocephalus is even further limited. Future studies are necessary to quantify the burden of disease and identify strategies for improving global outcomes in treating and reducing the prevalence of NTDs and hydrocephalus. Surgical management of NTDs in LMICs is currently limited, but pediatric neurosurgeons may be uniquely equipped to address disparities in the care and counseling of families of children with spinal dysraphism and hydrocephalus.
-
To establish normative anatomic measurements of lumbar segmental angulation (SA) and disk space height (DSH) in relation to neuroforaminal dimensions (NFDs), and to uncover the influence of patient demographic and anthropometric characteristics on SA, DSH, and NFDs. ⋯ This study describes 48 450 normative measurements of L1-S1 SA, DSH, and NFDs. These measurements serve as representative models of normal anatomic dimensions necessary for several applications including surgical planning and diagnosis of foraminal stenosis. Normative values of SA and DSH are not moderately or strongly associated with NFDs. SA, DSH, and NFDs are influenced by sex and ethnicity, but are not strongly or moderately influenced by patient anthropometric factors.
-
The emergence of machine learning models has significantly improved the accuracy of surgical outcome predictions. This study aims to develop and validate an artificial neural network (ANN) model for predicting facial nerve (FN) outcomes after vestibular schwannoma (VS) surgery using the proximal-to-distal amplitude ratio (P/D) along with clinical variables. ⋯ ANN models incorporating P/D can be a valuable tool for predicting FN outcomes after VS surgery. Refining the model to include P/D with latencies between 6 and 8 ms further improves the model's prediction. A user-friendly interface is provided to facilitate the implementation of this model.