We report the largest study to date using a near-infrared device (NIRD) to detect traumatic intracranial bleeds.

The authors sought to characterize the population of patients with NTDs, maternal characteristics, and referral patterns of these patients, and to quantify the burden of NTDs in southwestern Uganda.

This review sought to characterize neurosurgical capacity building efforts in low- and middle-income countries and the challenges they face and identify factors that predict higher engagement, better training, and performance of high-impact activities.

This study aimed to describe pediatric TBI patients presenting to one regional referral hospital in Uganda and identify factors contributing to unfavorable outcomes.

The high unmet neurosurgical burden in low- and middle-income countries has necessitated multiple global neurosurgical collaborations. We identified and evaluated these collaborations and their peer-reviewed journal publications using a modified version of the Framework for Assessment of InteRNational Surgical Success (FAIRNeSS).

We evaluate the evolution and growth of global neurosurgery publications over time, focusing on authors' contributions and impact in low- and middle-income countries (LMICs).

Africa contributes significantly to the global neurosurgical disease burden but has only 1% of the neurosurgery workforce. This study appraises Africa's neurosurgical workforce and training capacity and projects the workforce capacity by 2030.

To generate machine learning (ML) models with a strong predictive capacity for trichotomized discharge disposition, an outcome not previously used in TBI prognostic models. The outcome can be a proxy for patients' functional status, even in mild and moderate patients with TBI.

To develop ML models to predict in-hospital mortality for both the high-income country (HIC) and the low- and middle-income country (LMIC) settings.

With the ultimate goal of enhancing TBI triage in LMICs, we aim to develop the first deep-learning model to predict outcomes after TBI and compare its performance with that of less complex algorithms.

We aim to externally validate CRASH and IMPACT on our TBI registry and compare their performances to that of the locally derived model (from the Kilimanjaro Christian Medical Center [KCMC]).

In this chapter, we explore the history, current work, and future directions for nonprofit and academic institutions in global neurosurgery. While we have tried to be holistic, we have undoubtedly left out efforts that deserve to be mentioned. Thus, this chapter is not meant to capture every example of the amazing work done worldwide; rather, the examples are pulled by the authors to illustrate the key points.

Over the past two decades, our Duke Global Neurosurgery and Neurology (DGNN) team has strived to live up to these ideals. We are constantly adapting and evolving our collaborative approach.

The purpose of this study was to investigate whether neurosurgical intervention for traumatic brain injury (TBI) is associated with reduced risks of death and clinical deterioration in a low-income country with a relatively high neurosurgical capacity. The authors further aimed to assess whether the association between surgical intervention and acute poor outcomes differs according to TBI severity and various patient factors.

Traumatic brain injury (TBI) disproportionately affects low- and middle-income countries (LMICs). In these low-resource settings, effective triage of patients with TBI-including the decision of whether or not to perform neurosurgery-is critical in optimizing patient outcomes and healthcare resource utilization.

This study seeks to determine the factors that impact TBI patient caretakers' health literacy and examine how these factors influence delays in care.

Using a scalable phone-centered survey, this study attempted to investigate factors associated with both mortality and quality of life in Ugandan patients with TBI.

This scoping review aims to characterize the field of global neurosurgery by identifying partnerships between high-income countries (HICs) and low- and/or middle-income countries (LMICs) that seek to increase neurosurgical capacity.

We previously developed a prognostic model and Web-based application for in-hospital TBI care in low-resource settings. In this study, we tested the feasibility, acceptability, and usability of the application with potential end-users.

The authors' current study objective was to better understand in-hospital decision-making for TBI patients and determine whether data from the CRASH risk calculator influenced provider assessment of prognosis.