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Objective: To describe an intuitive and useful method for measuring the global impact of a medical scholar's research ideas by examining cross-border citations (CBCs) of peer-reviewed neurosurgical publications., Methods: Publication and citation data for a random sample of the top 50 most academically productive neurosurgeons were obtained from Scopus Application Programming Interface. We characterized an author-level global impact index analogous to the widely used h-index, the h global -index, defined as the number of published peer-reviewed manuscripts with at least the same number of CBCs. To uncover socioeconomic insights, we explored the h global -index for high-, middle-, and low-income countries., Results: The median (interquartile range) number of publications and CBCs were 144 (62-255) and 2704 (959-5325), respectively. The median (interquartile range) h-index and h global -index were 42 (23-61) and 32 (17-38), respectively. Compared with neurosurgeons in the random sample, the 3 global neurosurgeons had the highest h global -indices in low-income countries at 17, 13, and 9, despite below-average h-index scores of 33, 38, and 19, respectively., Conclusion: This intuitive update to the h-index uses CBCs to measure the global impact of scientific research. The h global -index may provide insight into global diffusion of medical ideas, which can be used for social science research, author self-assessment, and academic promotion., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Snakebite envenoming (SBE) affects nearly three million people yearly, causing up to 180,000 deaths and 400,000 cases of permanent disability. Brazil's state of Amazonas is a global hotspot for SBE, with one of the highest annual incidence rates per 100,000 people, worldwide. Despite this burden, snake antivenom remains inaccessible to a large proportion of SBE victims in Amazonas. This study estimates the costs, and health and economic benefits of scaling up antivenom to community health centers (CHCs) and hospitals in the state., Methods: We built a decision tree model to simulate three different antivenom scale-up scenarios: (1) scale up to 95% of hospitals, (2) scale up to 95% of CHCs, and (3) scale up to 95% of hospitals and 95% of CHCs. We consider each scenario with and without a 10% increase in demand for antivenom among SBE victims. For each scenario, we model the treatment costs averted, deaths averted, and disability-adjusted life years (DALYs) averted from a societal, health system, and patient perspective relative to the status quo and over a time horizon of one year. For each scenario and perspective, we also calculate the incremental cost per DALY averted and per death averted. We use a willingness to pay threshold equal to the 2022 gross domestic product (GDP) per capita of Brazil., Findings: Scaling up antivenom to 95% of hospitals averts up to 2022 DALYs, costs up to USD $460 per DALY averted from a health system perspective, but results in net economic benefits up to USD $4.42 million from a societal perspective. Scaling up antivenom to 95% of CHCs averts up to 3179 DALYs, costs up to USD $308 per DALY averted from a health system perspective, but results in net economic benefits up to USD $7.35 million from a societal perspective. Scaling up antivenom to 95% of hospitals and CHCs averts up to 3922 DALYs, costs up to USD $328 per DALY averted from a health system perspective, but results in net economic benefits up to USD $8.98 million from a societal perspective., Interpretation: All three antivenom scale up scenarios - scale up to 95% of hospitals, scale up to 95% of CHCs, and scale up to 95% of hospitals and 95% of CHCs - avert a substantial proportion of the SBE burden in Amazonas and are cost-saving from a societal perspective and cost-effective from a health system perspective., Funding: W.M. and J.S. were funded by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq productivity scholarships). W.M. was funded by Fundação de Amparo à Pesquisa do Estado do Amazonas (PRÓ-ESTADO, call n. 011/2021-PCGP/FAPEAM, call n. 010/2021-CT&I ÁREAS PRIORITÁRIAS, call n. 003/2022-PRODOC/FAPEAM, POSGRAD/FAPEAM) and by the Ministry of Health, Brazil (Proposal No. 733781/19-035). Research reported in this publication was supported by the Fogarty International Center of the National Institutes of Health under Award Number R21TW011944. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health., Competing Interests: CJG reports research funding from Ophirex Inc. for other studies., (© 2023 The Authors.)

Introduction: Effective out-of-hospital administration of naloxone in opioid overdoses is dependent on timely arrival of naloxone. Delays in emergency medical services (EMS) response time could potentially be overcome with drones to deliver naloxone efficiently to the scene for bystander use. Our objective was to evaluate a mathematical optimization simulation for geographical placement of drone bases in reducing response time to opioid overdose. Methods: Using retrospective data from a single EMS system from January 2016-February 2019, we created a geospatial drone-network model based on current technological specifications and potential base locations. Genetic optimization was then used to maximize county coverage by drones and the number of overdoses covered per drone base. From this model, we identified base locations that minimize response time and the number of drone bases required. Results: In a drone network model with 2,327 opioid overdoses, as the number of modeled drone bases increased the calculated response time decreased. In a geospatially optimized drone network with four drone bases, response time compared to ambulance arrival was reduced by 4 minutes 38 seconds and covered 64.2% of the county. Conclusion: In our analysis we found that in a mathematical model for geospatial optimization, implementing four drone bases could reduce response time of 9-1-1 calls for opioid overdoses. Therefore, drones could theoretically improve time to naloxone delivery., Competing Interests: Conflicts of Interest: By the WestJEM article submission agreement, all authors are required to disclose all affiliations, funding sources and financial or management relationships that could be perceived as potential sources of bias. No author has professional or financial relationships with any companies that are relevant to this study. There are no conflicts of interest or sources of funding to declare.

For universal surgical, obstetric, trauma, and anesthesia care by 2030, the Lancet Commission on Global Surgery (LCoGS) suggested tracking six indicators. We reviewed academic and policy literature to investigate the current state of LCoGS indicators in India. There was limited primary data for access to timely essential surgery, risk of impoverishing and catastrophic health expenditures due to surgery, though some modeled estimates are present. Surgical specialist workforce estimates are heterogeneous across different levels of care, urban and rural areas, and diverse health sectors. Surgical volumes differ widely across demographic, socio-economic, and geographic cohorts. Perioperative mortality rates vary across procedures, diagnoses, and follow-up time periods. Available data suggest India falls short of achieving global targets. This review highlights the evidence gap for India's surgical care planning. India needs a systematic subnational mapping of indicators and adaptation of targets as per the country's health needs for equitable and sustainable planning., Competing Interests: The authors declare no competing interests., (© 2023 The Author(s).)

In the Brazilian Amazon, deaths and disabilities from snakebite envenomations (SBEs) are a major and neglected problem for the indigenous population. However, minimal research has been conducted on how indigenous peoples access and utilize the health system for snakebite treatment. A qualitative study was conducted to understand the experiences of health care professionals (HCPs) who provide biomedical care to indigenous peoples with SBEs in the Brazilian Amazon. Focus group discussions (FGDs) were carried out in the context of a three-day training session for HCPs who work for the Indigenous Health Care Subsystem. A total of 56 HCPs participated, 27 in Boa Vista and 29 in Manaus. Thematic analysis resulted in three key findings: Indigenous peoples are amenable to receiving antivenom but not to leaving their villages for hospitals; HCPs require antivenom and additional resources to improve patient care; and HCPs strongly recommend a joint, bicultural approach to SBE treatment. Decentralizing antivenom to local health units addresses the central barriers identified in this study (e.g., resistance to hospitals, transportation). The vast diversity of ethnicities in the Brazilian Amazon will be a challenge, and additional studies should be conducted regarding preparing HCPs to work in intercultural contexts.

Competing Interests: Competing interests: None declared.

After discharge from the hospital for traumatic injury, patients and their caregivers face a period of increased vulnerability. This adjustment phase is poorly characterized, especially in low- and middle-income countries. We explored the experiences of patients and their caregivers in Northern Tanzania after hospitalization for a traumatic injury. Patients who received care for traumatic injury at the Kilimanjaro Christian Medical Center and their caregivers were selected as part of a convenience sample from January 2019 to December 2019. Analysts developed a codebook; content and analytic memos were subsequently created. We then applied the biopsychosocial model to further characterize our findings. Participants included 26 patients and 11 caregivers. Patients were mostly middle-aged (mean age 37.7) males (80.8%), residing in urban settings (57.7%), injured in road traffic accidents (65.4%), and who required surgery (69.2%). Most caregivers were female. Seven major themes arose: pain, decreased physical functioning, poor emotional health, lack of support, challenges with daily activities, financial strain, and obstacles to accessing healthcare. This study describes some of the difficulties transitioning back into the community after hospitalization for traumatic injury. Our work demonstrates the importance of mixed methods approaches in characterizing and addressing transitions of care challenges., Competing Interests: Conflicts of Interest: The authors declare no conflict of interest.

Hospitals in low- and middle-income countries (LMICs) could benefit from decision support technologies to reduce time to triage, diagnosis, and surgery for patients with traumatic brain injury (TBI). Corticosteroid Randomization after Significant Head Injury (CRASH) and International Mission for Prognosis and Clinical Trials in Traumatic Brain Injury (IMPACT) are robust examples of TBI prognostic models, although they have yet to be validated in Sub-Saharan Africa (SSA). Moreover, machine learning and improved data quality in LMICs provide an opportunity to develop context-specific, and potentially more accurate, prognostic models. 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]). We developed a machine learning-based prognostic model from a TBI registry collected at a regional referral hospital in Moshi, Tanzania. We also used the core CRASH and IMPACT online risk calculators to generate risk scores for each patient. We compared the discrimination (area under the curve [AUC]) and calibration before and after Platt scaling (Brier, Hosmer-Lemeshow Test, and calibration plots) for CRASH, IMPACT, and the KCMC model. The outcome of interest was unfavorable in-hospital outcome defined as a Glasgow Outcome Scale score of 1-3. There were 2972 patients included in the TBI registry, of whom 11% had an unfavorable outcome. The AUCs for the KCMC model, CRASH, and IMPACT were 0.919, 0.876, and 0.821, respectively. Prior to Platt scaling, CRASH was the best calibrated model (χ 2  = 68.1) followed by IMPACT (χ 2  = 380.9) and KCMC (χ 2  = 1025.6). We provide the first SSA validation of the core CRASH and IMPACT models. The KCMC model had better discrimination than either of these. CRASH had the best calibration, although all model predictions could be successfully calibrated. The top performing models, KCMC and CRASH, were both developed using LMIC data, suggesting that locally derived models may outperform imported ones from different contexts of care. Further work is needed to externally validate the KCMC model.

Background: The new coronavirus disease (COVID-19) has claimed thousands of lives worldwide and disrupted the health system in many countries. As the national emergency care capacity is a crucial part of the COVID-19 response, we evaluated the Brazilian Health Care System response preparedness against the COVID-19 pandemic. Methods: A retrospective and ecological study was performed with data retrieved from the Brazilian Information Technology Department of the Public Health Care System. The numbers of intensive care (ICU) and hospital beds, general or intensivist physicians, nurses, nursing technicians, physiotherapists, and ventilators from each health region were extracted. Beds per health professionals and ventilators per population rates were assessed. A health service accessibility index was created using a two-step floating catchment area (2SFCA). A spatial analysis using Getis-Ord Gi * was performed to identify areas lacking access to high-complexity centers (HCC). Results: As of February 2020, Brazil had 35,682 ICU beds, 426,388 hospital beds, and 65,411 ventilators. In addition, 17,240 new ICU beds were created in June 2020. The South and Southeast regions have the highest rates of professionals and infrastructure to attend patients with COVID-19 compared with the northern region. The north region has the lowest accessibility to ICUs. Conclusions: The Brazilian Health Care System is unevenly distributed across the country. The inequitable distribution of health facilities, equipment, and human resources led to inadequate preparedness to manage the COVID-19 pandemic. In addition, the ineffectiveness of public measures of the municipal and federal administrations aggravated the pandemic in Brazil., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Silva, Carvalho Dutra, Andrade, Iora, Rodrigues Ramajo, Peres Gualda, Costa Scheidt, Vasconcelos Maia do Amaral, Hernandes Rocha, Staton, Nickenig Vissoci and Fressatti Cardoso.)

Introduction: The COVID-19 pandemic stressed the importance of healthcare personnel. However, there is evidence of an increase in violence against them, which brings consequences, such as anxiety. The aim of this study was to analyze the anxiety levels of health professionals who have or not suffered violence during the COVID-19 pandemic, and verify the variables associated with the risk of starting to take medication for anxiety. Methods: We assessed the anxiety profile of health professionals in Brazil through an online questionnaire, using the Generalized Anxiety Disorder 7-item Scale (GAD-7), in relation to groups of participants who have or not suffered violence during the COVID-19 pandemic. We used Cronbach's alpha reliability coefficient to check the consistency of the responses, and the effect size using the r coefficient. Principal Component Analysis was used to verify the differences in anxiety scores between the two groups. Logistic regression analysis was also used to verify the variables associated with the risk of starting medication for anxiety and considered statistically significant when p < 0.05. Results: A total of 1,166 health professionals participated in the study, in which 34.13% had a normal anxiety profile, 40.14% mild, 15.78% moderate, and 9.95% severe. The mean score of the sum of the GAD-7 was 7.03 (SD 5.20). The group that suffered violence had a higher mean (8.40; SD 5.42) compared to the group that did not (5.70; SD 4.60). In addition, the median between both groups was significantly different (7.0 vs. 5.0; p < 0.01). Approximately 18.70% of the participants reported having started taking medication to treat anxiety during the pandemic. The factors that increased the chances of these professionals starting medication for anxiety p < 0.05 were having suffered violence during the pandemic (OR 1.97; 95% CI 1.42-2.77), being nurses (OR 1.61; 95% CI 1.04-2.47) or other types of health professionals (OR 1.58; 95% CI 1.04-2.38), and having a mild (OR 2.11; 95% CI 1.37-3.34), moderate (OR 4.05; 95% CI 2.48-6.71) or severe (OR 9.08; 95% CI 5.39-15.6) anxiety level. Conclusion: Brazilian healthcare professionals who have suffered violence during the pandemic have higher anxiety scores and higher risk to start taking anxiety medication., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Bitencourt, Silva, Alarcão, Dutra, Bitencourt, Garcia, de Andrade, Nickenig Vissoci, Pelloso and Carvalho.)

Introduction: Most patients with COVID-19 have mild or moderate manifestations; however, there is a wide spectrum of clinical presentations and even more severe repercussions that require high diagnostic suspicion. Vital sign acquisition and monitoring are crucial for detecting and responding to patients with COVID-19., Objective: Thus, we conducted this study to demonstrate the impact of using a tool called Smart Check on the triage time of patients with suspected COVID-19 and to identify the main initial clinical manifestations in these patients., Methodology: We assessed triage times before and after the use of Smart Check in 11 466 patients at Hospital Nossa Senhora da Conceição in Porto Alegre, Brazil, from 1 June to 31 July 2020. In this group, we identified 220 patients for the identification of COVID-19 clinical manifestations in a case-control analysis., Results: Smart Check was able to decrease the triage time by 33 seconds on average (P < .001), with 75% of the exams being performed within 5 minutes, whereas with the usual protocol these steps were performed within 6 minutes. A range of clinical presentations made up the COVID-19 initial manifestations. Those with the highest frequency were dry cough (46.4%), fever (41.3%), dyspnoea (35.8%), and headache (31.8%). Loss of appetite was the manifestation that had a statistically significant association with the SARS-CoV-2 presence (univariate analysis). When analysed together, loss of appetite associated with dyspnoea and/or ageusia and/or fever was related to the diagnosis of COVID-19., Conclusions: Smart Check, a simple clinical evaluation tool, along with the targeted use of rapid PCR testing, can optimise triage time for patients with and without COVID-19. In triage centres, a number of initial signs and symptoms should be cause for SARS-CoV-2 infection suspicion, in particular the association of respiratory, neurological, and gastrointestinal manifestations., (© 2021 John Wiley & Sons Ltd.)

Rationale and Objectives: Two-dimensional (2D) ultrasound (US) is operator dependent, requiring operator skill and experience to selectively identify and record planes of interest for subsequent interpretation. This limits the utility of US in settings in which expert sonographers are unavailable. Three-dimensional (3D) US acquisition of an anatomic target, which enables reconstruction of any plane through the acquired volume, might reduce operator dependence by providing any desired image plane for interpretation, without identification of target planes of interest at the time of acquisition. We applied a low-cost 3DUS technology because of the wider potential application compared with dedicated 3DUS systems. We chose second trimester fetal biometric parameters for study because of their importance in maternal-fetal health globally. We hypothesized that expert and novice interpretations of novice-acquired 3D volumes would not differ from each other nor from expert measurements of expert-acquired 2D images, the clinical reference standard., Materials and Methods: This was a prospective, blinded, observational study. Expert sonographers blinded to 3DUS volumes acquired 2DUS images of second trimester fetuses from 32 subjects, and expert readers performed interpretation, during usual care. A novice sonographer blinded to other clinical data acquired oriented 3DUS image volumes of the same subjects on the same date. Expert readers blinded to other data assessed placental location (PL), fetal presentation (FP), and amniotic fluid volume (AFV) in novice-acquired 3D volumes. Novice and expert raters blinded to other data independently measured biparietal diameter (BPD), humerus length (HL), and femur length (FL) for each fetus from novice-acquired 3D volumes. Corresponding gestational age (GA) estimates were calculated. Inter-rater reliability of measurements and GAs (expert 3D versus expert 2D, novice 3D versus expert 2D, and expert 3D versus novice 3D) were assessed by intraclass correlation coefficient (ICC). Mean inter-rater measurement differences were analyzed using one-way ANOVA., Results: 3D volume acquisition and reconstruction required mean 30.4 s (±5.7) and 70.0 s (±24.0), respectively. PL, FP, and AFV were evaluated from volumes for all subjects; mean time for evaluation was 16 s (±0.0). PL, FP, and AFV could be evaluated for all subjects. At least one biometric measurement was possible for 31 subjects (97%). Agreement between rater pairs for a composite of all measures was excellent (ICCs ≥ 0.95), and for individual measures was good to excellent (ICCs ≥ 0.75). Inter-rater differences were not significant ( p  > .05)., Conclusions: Expert and novice interpretations of novice-acquired 3DUS volumes of second trimester fetuses provided reliable biometric measures compared with expert interpretation of expert-acquired 2DUS images. 3DUS volume acquisition with a low-cost system may reduce operator dependence of ultrasound.

Global suicide rates have increased in recent decades becoming a serious social and public health problem. In Brazil, rates have been increasing annually. We aimed to analyze the correlation between suicide mortality rates and global economic and political crisis periods of 2008 and 2014 in Brazil. The analysis of suicide mortality in Brazil was done using a time-series segmented linear regression model that estimated the trend of rates over time. To obtain the model, changes in the trend of both abrupt and gradual suicide rates were investigated. The results indicate statistically significant changes showing an upward trend of suicide rates during the world economic crisis (2008-2013) and during the economic and political crisis in Brazil (2014-2017) compared to previous periods, especially at the extremes of schooling (3 < years and > 8 years). Among white and parda, there were significant trend rates increases in both periods and in different regions. In the Northeast and South regions, we observed a significant increase in the trend rate for males after the Brazilian economic and political crisis (2014 to 2017). We can conclude that the national suicide rates were influenced by the economic and political instability that our country has been going through since 2008, affecting each region differently. Further studies are needed to explore the reasons for interregional differences and the relation of suicide with unemployment rates and possible economic predictors., (© 2021 The Author(s).)

Background: The Kilimanjaro region has one of the highest levels of reported alcohol intake per capita in Tanzania. Age at first drink has been found to be associated with alcohol problems in adulthood, but there is less information on the age of first drink in the Kilimanjaro region and its associations with alcohol-related consequences later in life. Furthermore, local alcohol cost and availability may influence the prevalence of alcohol use and alcohol use disorders., Methods: Data on the age of first drink, alcohol use disorder identification tool (AUDIT), number and type of alcohol consequences (DrInC), and perceived alcohol at low cost and high availability for children and adolescents were collected from an alcohol and health behavior survey of injury patients (N = 242) in Moshi, Tanzania. Generalized linear models were used to test age at first drink, perceived alcohol cost and availability, and their association with the AUDIT and DrInC scores, and current alcohol use, respectively., Results: Consuming alcohol before age 18 was significantly associated with higher AUDIT and DrInC scores, with odds ratios of 1.22 (CI: 1.004, 1.47) and 1.72 (CI: 1.11, 2.63), respectively. Female gender is strongly associated with less alcohol use and alcohol consequences, represented by an odds ratio of 3.70 (CI: 1.72, 8.33) for an AUDIT score above 8 and an odds ratio of 3.84 (CI: 2.13, 6.67) with the DrInC score. Perceived high availability of alcohol for children is significantly related to higher alcohol use quantity, with the odds ratio of 1.6 (CI: 1.17, 2.20)., Conclusions: The first use of alcohol before the age of 18 is associated with higher alcohol use and alcohol-related adverse consequences. In Tanzania, age at first drink is an important target for interventions aiming to prevent negative alcohol-related consequences later in life., (© 2020 by the Research Society on Alcoholism.)

Background: Alcohol is a leading risk factor for road traffic injury in low- and middle-income countries, such as Tanzania. This research seeks to explore the drinking patterns, perceptions, and stigma of drink driving behavior of injury patients at Kilimanjaro Christian Medical Center in Moshi, Tanzania., Methods: This mixed methods study incorporated the Perceived Alcohol Stigma (PAS), an additive Likert scale, and the Alcohol Use Disorders Identification Test (AUDIT). Results are reported as medians with IQRs. Additionally, focus groups with injury patients, their families, and community members (n = 104) were conducted and analyzed in pairs using an inductive thematic content analysis approach., Results: Those who self-reported driving after ingesting 3 or more alcoholic drinks had a median AUDIT score (median = 11.0) significantly higher than those who denied drink driving (median = 5.5, p < 0.01). The PAS showed a high overall stigma against those who use alcohol but differed for drink drivers, drinkers, and abstainers (median = 20.8, 23.9, 34.9, p < 0.01). Thematic content analysis highlighted a 'disapproving of drink drivers', that 'problematic drinking is a drinking behavior which negatively affects others', and a 'passiveness toward drinking and drink driving'., Conclusions: Stigma against those who use alcohol is present in Tanzania. Perceived stigma is significantly lower among those who drink drive than those who do not. Overall, there appears to be a community-wide disapproval of drinking and driving, which is coupled with feeling unable to change this risky behavior., Competing Interests: Declaration of Competing Interest The authors declare that there are no competing interests related to this manuscript., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objective: The Kilimanjaro region has one of the highest rates of reported alcohol use per capita in Tanzania. Alcohol-related risky behaviors pose substantial threats to the health and well-being of alcohol users and the people around them. This study seeks to understand how alcohol-related risky behaviors co-occur with other risky behaviors., Method: Latent class analysis (LCA) was applied to examine alcohol-related risky behaviors. The optimal number of latent classes was confirmed by using model fit indices. Negative binomial models were used to test latent classes and their association with harmful and hazardous drinking and perceived alcohol stigma. With the model defined, we explored each class's drinking patterns and risky behavior patterns., Results: A total of 622 (60% male) of 841 participants were included in these analyses because they drank alcohol at least once in their lifetime. Three classes of risky behavior patterns were identified: Class 1, "Limited risk behaviors" (59.7%); Class 2, "Primarily foolish behaviors" (25.6%); and Class 3, "Pervasive risk behaviors" (13.1%). Class 3 had the most alcohol use quantity and frequency. No association between classes and alcohol stigma was found. Compared with males, females are less likely to be classified in Class 2 and 3., Conclusions: Three different classes of risky behaviors became apparent and were distinguished by gender, age, and personal alcohol use. Our findings suggest a potential role for personalized interventions based on latent classes specifically to reduce risk behaviors.

Introduction : In Rwanda, major depressive disorder affects 11.9% of the population and up to 35% of genocide survivors. Mental health services remain underutilized due to stigma and lack of awareness. Increasing the ability and capacity to diagnose and treat mental disorders is considered important to close this gap. We describe the translation, validity, and reliability assessment of the Hamilton Depression Rating Scale (HDRS) as a diagnostic tool for moderate to severe depression in Rwanda. Methods : The HDRS-21 was translated by a multi-group taskforce. We validated the translation against expert assessment in a comparative study on a sample of patients living with depression and of healthy volunteers. Psychometric properties, namely internal structure, reliability, and external validity were assessed using confirmatory factor analysis, three reliability calculations, and correlation analysis, respectively. Maximized Youden's index was used for determining diagnostic cut-off. Results : The translated version demonstrated a kappa of 0.93. We enrolled 105 healthy volunteers and 105 patients with confirmed mild to severe depression. In the confirmatory factor analysis, HDRS had good factor loadings of 0.32-0.80. Reliability coefficients above 0.92 indicated strong internal consistency. External validity was shown by good sensitivity (0.95) and specificity (0.94) to differentiate depression from absence of depression. At a cut-off point of 17 for the diagnosis of depression, sensitivity and specificity were both 0.95 relative to gold standard. Conclusion : The validated HDRS in Kinyarwanda with diagnostic cut-off provides mental healthcare staff with an accurate tool to diagnose moderate to severe depression, enabling closure of the diagnosis and treatment gap., (Copyright © 2020 Dedeken, Vissoci, Sebera, Boon, Rutembesa and Teuwen.)

Background: Traumatic brain injury (TBI) prognostic models are potential solutions to severe human and technical shortages. Although numerous TBI prognostic models have been developed, none are widely used in clinical practice, largely because of a lack of feasibility research to inform implementation. 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., Methods: We performed our feasibility assessment with providers involved in TBI care at both a regional and national referral hospital in Uganda. We collected qualitative and quantitative data on decision support needs, application ease of use, and implementation design., Results: We completed 25 questionnaires on potential uses of the app and 11 semistructured feasibility interviews. Top-cited uses were informing the decision to operate, informing the decision to send the patient to intensive care, and counseling patients and relatives. Participants affirmed the potential of the application to support difficult triage situations, particularly in the setting of limited access to diagnostics and interventions, but were hesitant to use this technology with end-of-life decisions. Although all participants were satisfied with the application and agreed that it was easy to use, several expressed a need for this technology to be accessible by smartphone and offline., Conclusions: We elucidated several potential uses for our app and important contextual factors that will support future implementation. This investigation helps address an unmet need to determine the feasibility of TBI clinical decision support systems in low-resource settings., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objective: Road traffic injuries (RTI) cause ∼1.2 million deaths and 50 million injuries annually, disproportionately occurring in low- and middle-income countries. Although policy changes and infrastructural developments have continued to contribute to the decrease in RTI-related deaths, limited studies have investigated the relationship between motorcycle taxi driver behaviors and RTIs in Rwanda. This study aims to describe the safety behaviors of commercial motorcyclists in Kigali, Rwanda. Methods: We surveyed 609 commercial motorcyclists in January 2014 then conducted a cross-sectional analysis of the results, including descriptive and bivariate logistic regression analyses. Results: We found that 38.7% of surveyed motorcycle drivers experienced a crash during their lifetime, of which, more than half (n = 134, 56.8%) suffered injuries. Of all injuries, 38.8% (n = 52) resulted in hospitalization, and 14.2% (n = 19) in disability. Among motorcyclists, 100% reported always wearing a helmet, 99% reported always wearing a chin strap, and 98.8% reported always having a passenger helmet. There was an association between sustaining a crash and believing that helmets (p = 0.08) and chin straps (p = 0.05) reduced crash risk. Conclusions: Rwandan commercial motorcyclists demonstrate generally proper safety behaviors, but remain a high-risk occupational group. Road safety policy initiatives have been effective in changing driver behavior regardless of driver safety beliefs.

Objective: Traumatic brain injury (TBI), a burgeoning global health concern, is one condition that could benefit from prognostic modeling. Risk stratification of TBI patients on presentation to a health facility can support the prudent use of limited resources. The CRASH (Corticosteroid Randomisation After Significant Head Injury) model is a well-established prognostic model developed to augment complex decision-making. 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., Methods: The authors performed a choice experiment using a simulated TBI case. All participant doctors received the same case, which included a patient history, vitals, and physical examination findings. Half the participants also received the CRASH risk score. Participants were asked to estimate the patient prognosis and decide the best next treatment step. The authors recruited a convenience sample of 28 doctors involved in TBI care at both a regional and a national referral hospital in Uganda., Results: For the simulated case, the CRASH risk scores for 14-day mortality and an unfavorable outcome at 6 months were 51.4% (95% CI 42.8%, 59.8%) and 89.8% (95% CI 86.0%, 92.6%), respectively. Overall, participants were overoptimistic when estimating the patient prognosis. Risk estimates by doctors provided with the CRASH risk score were closer to that score than estimates made by doctors in the control group; this effect was more pronounced for inexperienced doctors. Surgery was selected as the best next step by 86% of respondents., Conclusions: This study was a novel assessment of a TBI prognostic model's influence on provider estimation of risk in a low-resource setting. Exposure to CRASH risk score data reduced overoptimistic prognostication by doctors, particularly among inexperienced providers.

Alcohol is one of the leading causes of death and disability worldwide. Rates of alcohol abuse in Moshi, Tanzania, are about 2.5 times higher than the Tanzanian average. We sought to qualitatively assess the perceptions of alcohol use among injury patients in Moshi, including availability, consumption patterns, abuse, and treatments. Participants were Emergency Department injury patients, their families, and community advisory board members. Participants were included if they were ≥18 years of age, a patient or patient's family member seeking care at the Kilimanjaro Christian Medical Center Emergency Department, Moshi, Tanzania, for an acute injury, clinically sober at the time of enrollment, medically stable, able to communicate in Swahili and consented to participate. Focus group discussions were audiotaped, transcribed, translated, and analyzed in parallel using an inductive thematic content analysis approach. Resultant themes were then reanalyzed to ensure internal homogeneity and external heterogeneity. Fourteen focus group discussions, with a total of 104 participants (40 patients, 50 family members, 14 community advisory board members), were conducted. Major themes resulting from the analysis included: 1) Early/repeated exposure; 2) Moderate use as a social norm with positive attributes; 3) Complications of abuse are widely stigmatized; and 4) Limited knowledge of availability of treatment. Our findings suggest that, among our unique injury population and their families, despite the normalization of alcohol-related behaviors, there is strong stigma toward complications stemming from excess alcohol use. Overall, resources for alcohol treatment and cessation, although broadly desired, are unknown to the injury population., Competing Interests: Conflicts of interests No conflicts declared., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background: Brazil faces huge health inequality challenges since not all municipalities have access to primary care physicians. The More Doctors Programme (MDP), which started in 2013, was born out of this recognition, providing more than 18 000 doctors in the first few years. However, the programme faced a restructuring at the end of 2018., Methods: We construct a panel municipality-level data between 2008 and 2017 for 5570 municipalities in Brazil. We employ a difference-in-differences empirical approach, combined with propensity score matching, to study the impacts of the programme on hospitalisations for ambulatory care sensitive conditions and its costs. We explore heterogeneous impacts by age of the patients, type of admissions, and municipalities that were given priority., Findings: The MDP reduced ambulatory admissions by 2.9 per cent (p value <0.10) and the costs by 3.7 per cent (p value <0.01) over the mean. The reduction was driven by infectious gastroenteritis, bacterial pneumonias, asthma, kidney and urinary infections, and pelvic inflammatory disease. The results held on the subsample of municipalities targeted by the programme. By comparing the benefits of the programme from the reduction in the costs of ambulatory admissions to the total financial costs of the MDP, the impacts allowed the government to save at least BRL 27.88 (US$ 6.9 million) between 2014 and 2017., Conclusion: Addressing inequalities in the distribution of the medical workforce remains a global challenge. Our results inform the discussion on the current strategy adopted in Brazil to increase access to primary healthcare in underserved areas., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: 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., Methods: 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., Results: 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., Conclusions: 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.

Objective: 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., Methods: 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., Results: 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., Conclusions: 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.

Background: Significant care continuum delays between acute traumatic brain injury (TBI) and definitive surgery are associated with poor outcomes. Use of the "3 delays" model to evaluate TBI outcomes in low- and middle-income countries has not been performed., Objective: To describe the care continuum, using the 3 delays framework, and its association with TBI patient outcomes in Kampala, Uganda., Methods: Prospective data were collected for 563 TBI patients presenting to a tertiary hospital in Kampala from 1 June to 30 November 2016. Four time intervals were constructed along 5 time points: injury, hospital arrival, neurosurgical evaluation, computed tomography (CT) results, and definitive surgery. Time interval differences among mild, moderate, and severe TBI and their association with mortality were analyzed., Results: Significant care continuum differences were observed for interval 3 (neurosurgical evaluation to CT result) and 4 (CT result to surgery) between severe TBI patients (7 h for interval 3 and 24 h for interval 4) and mild TBI patients (19 h for interval 3 and 96 h for interval 4). These postarrival delays were associated with mortality for mild (P = .05) and moderate TBI (P = .03) patients. Significant hospital arrival delays for moderate TBI patients were associated with mortality (P = .04)., Conclusion: Delays for mild and moderate TBI patients were associated with mortality, suggesting that quality improvement interventions could target current triage practices. Future research should aim to understand the contributors to delays along the care continuum, opportunities for more effective resource allocation, and the need to improve prehospital logistical referral systems.

Objective: In addition to the rising burden of surgical disease globally, infrastructure and human resources for health remain a great challenge for low- and middle-income countries, especially in Uganda. In this study, the authors aim to explore the trends of neurosurgical care at a regional referral hospital in Uganda and assess the long-term impact of the institutional collaboration between Mulago National Referral Hospital and Duke University., Methods: An interrupted time series is a quasi-experimental design used to evaluate the effects of an intervention on longitudinal data. The authors applied this design to evaluate the trends in monthly mortality rates for neurosurgery patients at Mbarara Regional Referral Hospital (MRRH) from March 2013 to October 2015. They used segmented regression and autoregressive integrated moving average models for the analysis., Results: Over the study timeframe, MRRH experienced significant increases in referrals received (from 117 in 2013 to 211 in 2015), neurosurgery patients treated (from 337 in 2013 to 625 in 2015), and operations performed (from 61 in 2013 to 173 in 2015). Despite increasing patient volumes, the hospital achieved a significant reduction in hospital mortality during 2015 compared to prior years (p value = 0.0039)., Conclusions: This interrupted time series analysis study showed improving trends of neurosurgical care in Western Uganda. There is a steady increase in volume accompanied by a sharp decrease in mortality through the years. Multiple factors are implicated in the significant increase in volume and decrease in mortality, including the addition of a part-time neurosurgeon, improvement in infrastructure, and increased experience. Further in-depth prospective studies exploring seasonality and long-term outcomes are warranted.

Background: In Uganda, TBI constitute the majority of neurosurgical admissions and deaths specially in the pediatric population. This study aims to determine the factors associated with poor outcome among pediatric TBI cases at a major referral hospital in western Uganda., Methods: This study was conducted at Mbarara Regional Referral Hospital (MRRH) in western Uganda. All pediatric neurosurgical cases between 2012 and 2015 were reviewed. In-hospital mortality and discharge GCS were the main outcomes of interest. Multivariable logistic regression with backward elimination was used to determine the factors significantly associated with outcome., Results: A total of 381 pediatric TBI patients were admitted to MRRH between 2012 and 2015. The mean age was 8.6 (SD 5.6) with a male predominance (62.0%). The most common mechanism of injury overall was RTI, which was responsible for 71% of all TBI cases. In the multivariable logistic regression model, admission GCS < 13 was a strong predictor of poor outcome and in-hospital mortality compared to admission GCS ≥ 13, with patients demonstrating an odds ratio of 30 (95%CI: 7-132) and OR of 18 (95%CI: 4-79), respectively., Conclusion: Given the lack of published literature on pediatric TBI in LMICs, this study was the first to describe and evaluate risk factors associated with TBI severity among pediatric patients at a major referral hospital in western Uganda. Injury severity on admission was the only variable found to be significantly associated with discharge outcome. This study ultimately highlights the need for more effective preventative measures to decrease admission severity., (Copyright © 2017. Published by Elsevier Ltd.)

Introduction: There is a significant burden of unmet surgical need in many low- and middle-income countries (>80% in parts of Africa). This need is even larger for specialties such as neurosurgery. Surgical capacity tools have been developed and used to assess needs and plan for resource allocation. This study piloted a new tool to assess neurosurgical capacity and describes its use., Methods: A surgical capacity tool was adapted to assess neurosurgical capacity. An expert panel of neurosurgeons and researchers reviewed the Surgeons OverSeas PIPES (personnel, infrastructure, procedures, equipment, and supplies) assessment and added additional items essential to perform common neurosurgery procedures. This tool was then piloted at 3 public hospitals in Uganda and each hospital was given a score of neurosurgical capacity. At 1 hospital, 3 respondents were asked to answer the survey to assess reliability., Results: The hospital with the largest neurosurgery caseload and 5 neurosurgeons scored the highest on our survey, followed by a regional hospital with 1 practicing neurosurgeon. The third hospital, without a neurosurgeon, scored the lowest on the scale. At the hospital that completed the reliability assessment, scores were varied between respondents., Conclusions: NeuroPIPES survey scores were in keeping with the number of neurosurgeons and respective caseloads of each hospital. However, the variation in scores between respondents at the same hospital suggests that adaptations could be made to the tool that may improve reliability and validity. The methodology used to create NeuroPIPES may be successfully applied to a variety of other surgical subspecialties for similar assessments., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Objective: Traumatic brain injury (TBI) is a leading cause of death and disability. Patients with TBI in low and middle-income countries have worse outcomes than patients in high-income countries. We evaluated important clinical indicators associated with mortality for patients with TBI at University Teaching Hospital of Kigali, Kigali, Rwanda., Methods: A prospective consecutive sampling of patients with TBI presenting to University Teaching Hospital of Kigali Accident and Emergency Department was screened for inclusion criteria: reported head trauma, alteration in consciousness, headache, and visible head trauma. Exclusion criteria were age <10 years, >48 hours after injury, and repeat visit. Data were assessed for association with death using logistic regression. Significant variables were included in a multivariate logistic regression model and refined via backward elimination., Results: Between October 7, 2013, and April 6, 2014, 684 patients were enrolled; 14 (2%) were excluded because of incomplete data. Of patients, 81% were male with mean age of 31 years (range, 10-89 years; SD 11.8). Most patients (80%) had mild TBI (Glasgow Coma Scale [GCS] score 13-15); 10% had moderate (GCS score 9-12) and 10% had severe (GCS score 3-8) TBI. Multivariate logistic regression determined that GCS score <13, hypoxia, bradycardia, tachycardia, and age >50 years were significantly associated with death., Conclusions: GCS score <13, hypoxia, bradycardia, tachycardia, and age >50 years were associated with mortality. These findings inform future research that may guide clinicians in prioritizing care for patients at highest risk of mortality., (Copyright © 2017 Elsevier Inc. All rights reserved.)