Around the world today, low- and middle-income countries (LMICs) have not benefited from advancements in neurosurgery; most have minimal or even no neurosurgical capacity in their entire country. In this paper, the authors examine in broad strokes the different ways in which individuals, organizations, and universities engage in global neurosurgery to address the global challenges faced in many LMICs. Key strategies include surgical camps, educational programs, training programs, health system strengthening projects, health policy changes/development, and advocacy. Global neurosurgery has begun coalescing with large strides taken to develop a coherent voice for this work. This large-scale collaboration via multilateral, multinational engagement is the only true solution to the issues we face in global neurosurgery. Key players have begun to come together toward this ultimate solution, and the future of global neurosurgery is bright.
JNSPG 75th Anniversary Invited Review Article
Michael M. Haglund and Anthony T. Fuller
Cyrus Elahi, Thiago Augusto Hernandes Rocha, Núbia Cristina da Silva, Francis M. Sakita, Ansbert Sweetbert Ndebea, Anthony Fuller, Michael M. Haglund, Blandina T. Mmbaga, João Ricardo Nickenig Vissoci and Catherine A. Staton
The purpose of this study was to determine if patients with traumatic brain injury (TBI) in low- and middle-income countries who receive surgery have better outcomes than patients with TBI who do not receive surgery, and whether this differs with severity of injury.
The authors generated a series of Kaplan-Meier plots and performed multiple Cox proportional hazard models to assess the relationship between TBI surgery and TBI severity. The TBI severity was categorized using admission Glasgow Coma Scale scores: mild (14, 15), moderate (9–13), or severe (3–8). The authors investigated outcomes from admission to hospital day 14. The outcome considered was the Glasgow Outcome Scale–Extended, categorized as poor outcome (1–4) and good outcome (5–8). The authors used TBI registry data collected from 2013 to 2017 at a regional referral hospital in Tanzania.
Of the final 2502 patients, 609 (24%) received surgery and 1893 (76%) did not receive surgery. There were significantly fewer road traffic injuries and more violent causes of injury in those receiving surgery. Those receiving surgery were also more likely to receive care in the ICU, to have a poor outcome, to have a moderate or severe TBI, and to stay in the hospital longer. The hazard ratio for patients with TBI who underwent operation versus those who did not was 0.17 (95% CI 0.06–0.49; p < 0.001) in patients with moderate TBI; 0.2 (95% CI 0.06–0.64; p = 0.01) for those with mild TBI, and 0.47 (95% CI 0.24–0.89; p = 0.02) for those with severe TBI.
Those who received surgery for their TBI had a lower hazard for poor outcome than those who did not. Surgical intervention was associated with the greatest improvement in outcomes for moderate head injuries, followed by mild and severe injuries. The findings suggest a reprioritization of patients with moderate TBI—a drastic change to the traditional practice within low- and middle-income countries in which the most severely injured patients are prioritized for care.
Thiago Augusto Hernandes Rocha, Cyrus Elahi, Núbia Cristina da Silva, Francis M. Sakita, Anthony Fuller, Blandina T. Mmbaga, Eric P. Green, Michael M. Haglund, Catherine A. Staton and Joao Ricardo Nickenig Vissoci
Traumatic brain injury (TBI) is a leading cause of death and disability worldwide, with a disproportionate burden of this injury on low- and middle-income countries (LMICs). Limited access to diagnostic technologies and highly skilled providers combined with high patient volumes contributes to poor outcomes in LMICs. Prognostic modeling as a clinical decision support tool, in theory, could optimize the use of existing resources and support timely treatment decisions in LMICs. The objective of this study was to develop a machine learning–based prognostic model using data from Kilimanjaro Christian Medical Centre in Moshi, Tanzania.
This study is a secondary analysis of a TBI data registry including 3138 patients. The authors tested nine different machine learning techniques to identify the prognostic model with the greatest area under the receiver operating characteristic curve (AUC). Input data included demographics, vital signs, injury type, and treatment received. The outcome variable was the discharge score on the Glasgow Outcome Scale–Extended.
The AUC for the prognostic models varied from 66.2% (k-nearest neighbors) to 86.5% (Bayesian generalized linear model). An increasing Glasgow Coma Scale score, increasing pulse oximetry values, and undergoing TBI surgery were predictive of a good recovery, while injuries suffered from a motor vehicle crash and increasing age were predictive of a poor recovery.
The authors developed a TBI prognostic model with a substantial level of accuracy in a low-resource setting. Further research is needed to externally validate the model and test the algorithm as a clinical decision support tool.
Anthony T. Fuller, Ariana Barkley, Robin Du, Cyrus Elahi, MScGH, Ali R. Tafreshi, Megan Von Isenburg and Michael M. Haglund
Global neurosurgery is a rapidly emerging field that aims to address the worldwide shortages in neurosurgical care. Many published outreach efforts and initiatives exist to address the global disparity in neurosurgical care; however, there is no centralized report detailing these efforts. 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.
A scoping review was conducted using the Arksey and O’Malley framework. A search was conducted in five electronic databases and the gray literature, defined as literature not published through traditional commercial or academic means, to identify studies describing global neurosurgery partnerships. Study selection and data extraction were performed by four independent reviewers, and any disagreements were settled by the team and ultimately the team lead.
The original database search produced 2221 articles, which was reduced to 183 final articles after applying inclusion and exclusion criteria. These final articles, along with 9 additional gray literature references, captured 169 unique global neurosurgery collaborations between HICs and LMICs. Of this total, 103 (61%) collaborations involved surgical intervention, while local training of medical personnel, research, and education were done in 48%, 38%, and 30% of efforts, respectively. Many of the collaborations (100 [59%]) are ongoing, and 93 (55%) of them resulted in an increase in capacity within the LMIC involved. The largest proportion of efforts began between 2005–2009 (28%) and 2010–2014 (17%). The most frequently involved HICs were the United States, Canada, and France, whereas the most frequently involved LMICs were Uganda, Tanzania, and Kenya.
This review provides a detailed overview of current global neurosurgery efforts, elucidates gaps in the existing literature, and identifies the LMICs that may benefit from further efforts to improve accessibility to essential neurosurgical care worldwide.