Traumatic brain injury (TBI) outcomes in an LMIC tertiary care centre and performance of trauma scores

The Australian Traumatic Brain Injury Initiative: Systematic Review of Clinical Factors Associated with Outcomes in People with Moderate-Severe Traumatic Brain Injury

The aim of the Australian Traumatic Brain Injury Initiative (AUS-TBI) is to design a data dictionary to inform data collection and facilitate prediction of outcomes for moderate-severe traumatic brain injury (TBI) across Australia. The process has engaged diverse stakeholders across six areas: social, health, clinical, biological, acute interventions, and long-term outcomes. Here, we report the results of the clinical review. Standardized searches were implemented across databases to April 2022. English-language reports of studies evaluating an association between a clinical factor and any clinical outcome in at least 100 patients with moderate-severe TBI were included. Abstracts, and full-text records, were independently screened by at least two reviewers in Covidence. The findings were assessed through a consensus process to determine inclusion in the AUS-TBI data resource. The searches retrieved 22,441 records, of which 1137 were screened at full text and 313 papers were included. The clinical outcomes identified were predominantly measures of survival and disability. The clinical predictors most frequently associated with these outcomes were the Glasgow Coma Scale, pupil reactivity, and blood pressure measures. Following discussion with an expert consensus group, 15 were recommended for inclusion in the data dictionary. This review identified numerous studies evaluating associations between clinical factors and outcomes in patients with moderate-severe TBI. A small number of factors were reported consistently, however, how and when these factors were assessed varied. The findings of this review and the subsequent consensus process have informed the development of an evidence-informed data dictionary for moderate-severe TBI in Australia.

The Use of Corticosteroid Randomisation after Significant Head Injury (CRASH) Prognostic Model as Mortality Predictor of Traumatic Brain Injury Patients Underwent Surgery in Low-Middle Income Countries

Background

Traumatic brain injury (TBI) is a disruption to normal brain functions caused by traumas such as collisions, blows, or penetrating injuries. There are factors affecting patient outcomes that also have a predictive value. Limited data from low-middle income countries showed a high number of poor outcomes in TBI patients. The corticosteroid randomisation after significant head injury (CRASH) prognostic model is a predictive model that uses such factors and is often used in developed countries. The model has an excellent discriminative ability. However, there is still a lack of studies on its use in surgical patients in low-middle income countries. This study aimed to evaluate the CRASH model's validity to predict 14-day mortality of TBI patients who underwent surgery in low-middle income countries.

Methods

This retrospective analytical observational study employed total sampling including all TBI patients who underwent surgery with general anesthesia from January to December 2022. Statistical analysis was performed by applying Mann-Whitney and Fisher exact tests, while the model's discriminative ability was determined through the area under the curve (AUC) calculations.

Results

112 TBI patients were admitted during the study period, and 74 patients were included. Independent statistical analysis showed that 14-day mortality risk, age, Glasgow Coma Scale score, TBI severity, pupillary response, and major extracranial trauma had a significant individual correlation with patients' actual mortality outcome (p < 0.05). The AUC analysis revealed an excellent mortality prediction (AUC 0.838; CI 95%).

Conclusion

The CRASH prognostic model performs well in predicting the 14-day mortality of TBI patients who underwent surgery in low-middle income countries.

Psychometric properties and factor structure of the traditional Chinese version of the Community Integration Questionnaire-Revised in traumatic brain injury survivors

This study aimed to translate and validate the traditional Chinese version of the Community Integration Questionnaire-Revised (TC-CIQ-R) in patients with traumatic brain injury (TBI). We included participants aged ≥20 years and diagnosed as having TBI for ≥6 months from neurosurgical clinics. The 18-item TC-CIQ-R, Participation Measure - 3 Domains, 4 Dimensions (PM-3D4D), Extended Glasgow Outcome Scale (GOSE), and Taiwanese Quality of Life After Brain Injury (TQOLIBRI) were completed. The sample included 180 TBI survivors (54% male, mean age 47 years) of whom 87% sustained a mild TBI. Exploratory factor analysis extracted four factors - home integration, social integration, productivity, and electronic social networking - which explained 63.03% of the variation, after discarding the tenth item with a factor loading of 0.25. For criterion-related validity, the TC-CIQ-R was significantly correlated with the PM-3D4D; convergent validity was exhibited by demonstrating the associations between the TC-CIQ-R and TQOLIBRI. Known-group validity testing revealed significant differences in the subdomain and total scores of the TC-CIQ-R between participants with a mean GOSE score of ≤6 and >7 (all P  < 0.001). The TC-CIQ-R exhibited acceptable Cronbach's α values (0.68-0.88). We suggest the 17-item TC-CIQ-R as a valid tool for rehabilitation professionals, useful for both clinical practice and research in assessing community integration levels following TBI.

Factors Delaying the Continuum of Care for the Management of Traumatic Brain Injury in Low- and Middle-Income Countries: A Systematic Review

BACKGROUND

Considering the disproportionate burden of delayed traumatic brain injury (TBI) management in low- and middle-income countries (LMICs), there is pressing demand for investigations. Therefore, our study aims to evaluate factors delaying the continuum of care for the management of TBIs in LMICs.

METHODS

A systematic review was conducted with PubMed, Scopus, Google Scholar and Cumulative Index to Nursing and Allied Health Literature (CINAHL). Observational studies with TBI patients in LMIC were included. The factors affecting management of TBI were extracted and analyzed descriptively.

RESULTS

A total of 55 articles were included consisting of 60,603 TBI cases from 18 LMICs. Road traffic accidents (58.7%) were the most common cause of injury. Among included studies, factors contributing to prehospital delays included a poor referral system and lack of an organized system of referral (14%), long travel distances (11%), inadequacy of emergency medical services (16.6%), and self-treatment practices (2.38%). For in-hospital delays, factors such as lack of trained physicians (10%), improper triage systems (20%), and absence of imaging protocols (10%), lack of in-house computed tomography scanners (35%), malfunctioning computed tomography scanners (10%), and a lack of invasive monitoring of intracranial pressure (5%), limited theater space (28%), lack of in-house neurosurgical facilities (28%), absence of in-house neurosurgeons (28%), and financial constraints (14%) were identified.

CONCLUSIONS

Several factors, both before and during hospitalization contribute to delays in the management of TBIs in LMICs. Strategically addressing these factors can help overcome delays and improve TBI management in LMICs.

Traumatic Brain Injury Mortality and Correlates in Low- and Middle-Income Countries: A Meta-Epidemiological Study

BACKGROUND

It is estimated that up to 69 million people per year experience traumatic brain injury (TBI) with the highest prevalence found in low- and middle-income countries (LMICs). A paucity of data suggests that the mortality rate after severe TBI is twice as high in LMICs than in high-income countries.

OBJECTIVE

To analyze TBI mortality in LMICs and to evaluate what country-based socioeconomic and demographic parameters influence TBI outcomes.

METHODS

Four databases were searched for the period January 1, 2002, to January 1, 2022, for studies describing TBI outcomes in LMICs. Multivariable analysis was performed using multivariable linear regression, with the outcome as the pooled mortality by country and the covariates as the adjusted parameters.

RESULTS

Our search yielded 14 376 records of which 101 were included in the final analysis, totaling 59 197 patients and representing 31 LMICs. The pooled TBI-related mortality was 16.7% (95% CI: 13.7%-20.3%) without significant differences comparing pediatrics vs adults. Pooled severe TBI-related mortality was significantly higher than mild. Multivariable analysis showed a significant association between TBI-related mortality and median income ( P = .04), population percentage below poverty line ( P = .02), primary school enrollment ( P = .01), and poverty head ratio ( P = .04).

CONCLUSION

TBI-related mortality in LMICs is 3-fold to 4-fold higher than that reported in high-income countries. Within LMICs, parameters associated with poorer outcomes after TBI include factors recognized as social determinants of health. Addressing social determinants of health in LMICs might expedite the quest to close the care delivery gap after TBI.

Outcome of 1939 traumatic brain injury patients from road traffic accidents: Findings from specialist medical reports in a low to middle income country (LMIC)

OBJECTIVE

Road traffic accident (RTA) is the major cause of traumatic brain injury (TBI) in developing countries and affects mostly young adult population. This research aimed to describe the factors predicting functional outcome after TBI caused by RTA in a Malaysian setting.

METHODS

This was a retrospective cross-sectional study conducted on specialist medical reports written from 2009 to 2019, involving patients who survived after TBI from RTA. The functional outcome was assessed using the Glasgow Outcome Scale-Extended (GOSE). Factors associated with good outcome were analysed via logistic regression analysis. Multivariate logistic regression analysis was used to derive the best fitting Prediction Model and split-sample cross-validation was performed to develop a prediction model.

RESULTS

A total of 1939 reports were evaluated. The mean age of the study participants was 32.4 ± 13.7 years. Most patients were male, less than 40, and with average post RTA of two years. Good outcome (GOSE score 7 & 8) was reported in 30.3% of the patients. Factors significantly affecting functional outcome include age, gender, ethnicity, marital status, education level, severity of brain injury, neurosurgical intervention, ICU admission, presence of inpatient complications, cognitive impairment, post-traumatic headache, post traumatic seizures, presence of significant behavioural issue; and residence post discharge (p<0.05). After adjusting for confounding factors, prediction model identified age less than 40, mild TBI, absence of post traumatic seizure, absence of behaviour issue, absence of cognitive impairment and independent living post TBI as significant predictors of good functional outcome post trauma. Discrimination of the model was acceptable (C-statistic, 0.67; p<0.001, 95% CI: 0.62-0.73).

CONCLUSION

Good functional outcome following TBI due to RTA in this study population is comparable to other low to middle income countries but lower than high income countries. Factors influencing outcome such as seizure, cognitive and behavioural issues, and independent living post injury should be addressed early to achieve favourable long-term outcomes.

Affordability impacts therapeutic intensity of acute management of severe traumatic brain injury patients: An exploratory study in Tanzania

Introduction

Quality health care in low and middle-income countries (LMICs) is constrained by financing of care.

Research question

What is the effect of ability to pay on critical care management of patients with severe traumatic brain injury (sTBI)?

Material and Methods

Data on sTBI patients admitted to a tertiary referral hospital in Dar-es-Salaam, Tanzania, were collected between 2016 and 2018, and included payor mechanisms for hospitalization costs. Patients were grouped as those who could afford care and those who were unable to pay.

Results

Sixty-seven patients with sTBI were included. Of those enrolled, 44 (65.7%) were able to pay and 15 (22.3%) were unable to pay costs of care upfront. Eight (11.9%) patients did not have a documented source of payment (unknown identity or excluded from further analysis). Overall mechanical ventilation rates were 81% (n=36) in the affordable group and 100% (n=15) in the unaffordable group (p=0.08). Computed tomography (CT) rates were 71.6% (n=48) overall, 100% (n=44) and 0% respectively (p<0.01); Surgical rates were 16.4% (n=11) overall, 18.2% (n=8) vs. 13.3% (n=2) (p=0.67) respectively. Two-week mortality was 59.7% overall (n=40), 47.7% (n=21) in the affordable group and 73.3% (n=11) in the unaffordable group (p=0.09) (adjusted OR 0.4; 95% CI: 0.07-2.41, p=0.32).

Discussion and Conclusion

Ability to pay appears to have a strong association with the use of head CT and a weak association with mechanical ventilation in the management of sTBI. Inability to pay increases redundant or sub-optimal care, and imposes a financial burden on patients and their relatives.

Neurotrauma clinicians’ perspectives on the contextual challenges associated with traumatic brain injury follow up in low-income and middle-income countries: A reflexive thematic analysis

Background

Traumatic brain injury (TBI) is a major global health issue, but low- and middle-income countries (LMICs) face the greatest burden. Significant differences in neurotrauma outcomes are recognised between LMICs and high-income countries. However, outcome data is not consistently nor reliably recorded in either setting, thus the true burden of TBI cannot be accurately quantified.

Objective

To explore the specific contextual challenges of, and possible solutions to improve, long-term follow-up following TBI in low-resource settings.

Methods

A cross-sectional, pragmatic qualitative study, that considered knowledge subjective and reality multiple (i.e. situated within the naturalistic paradigm). Data collection utilised semi-structured interviews, by videoconference and asynchronous e-mail. Data were analysed using Braun and Clarke’s six-stage Reflexive Thematic Analysis.

Results

18 neurosurgeons from 13 countries participated in this study, and data analysis gave rise to five themes: Clinical Context: What must we understand?; Perspectives and Definitions: What are we talking about?; Ownership and Beneficiaries: Why do we do it?; Lost to Follow-up: Who misses out and why?; Processes and Procedures: What do we do, or what might we do?

Conclusion

The collection of long-term outcome data plays an imperative role in reducing the global burden of neurotrauma. Therefore, this was an exploratory study that examined the contextual challenges associated with long-term follow-up in LMICs. Where technology can contribute to improved neurotrauma surveillance and remote assessment, these must be implemented in a manner that improves patient outcomes, reduces clinical burden on physicians, and does not surpass the comprehension, capabilities, or financial means of the end user. Future research is recommended to investigate patient and family perspectives, the impact on clinical care teams, and the full economic implications of new technologies for follow-up.

Predictors of ICU admission and patient outcome for traumatic brain injury in a Tanzanian referral hospital: Implications for improving treatment guidelines

Traumatic brain injuries (TBI) are a critical global health challenge, with disproportionate negative impact in low- and middle-income countries (LMICs). People who suffer severe TBI in LMICs are twice as likely to die than those in high-income countries, and survivors experience substantially poorer outcomes. In the hospital, patients with severe TBI are typically seen in intensive care units (ICU) to receive advanced monitoring and lifesaving treatment. However, the quality and outcomes of ICU care in LMICs are often unclear. We analyzed secondary data from a cohort of 605 adult patients who presented to the Emergency Department (ED) of a Tanzanian hospital with a moderate or severe TBI. We examined patient characteristics and performed two binary logistic regression models to assess predictors of ICU admission and patient outcome. Patients were often young (median age = 32, SD = 15), overwhelmingly male (88.9%), and experienced long delays from time of injury to presentation in the ED (median=12 h, SD = 168). A majority of patients (87.8%) underwent surgery and 55.6% ultimately had a "good recovery" with minimal disability, while 34.0% died. Patients were more likely to be seen in the ICU if they had worse baseline symptoms and were over age 60. TBI surgery conveyed a 37% risk reduction for poor TBI outcome. However, ICU patients had a 3.91 times higher risk of poor TBI outcome as compared to those not seen in the ICU, despite controlling for baseline symptoms. The findings point to the need for targeted interventions among young men, improvements in pre-hospital transportation and care, and continued efforts to increase the quality of surgical and ICU care in this setting. It is unlikely that poorer outcome among ICU patients was indicative of poorer care in the ICU; this finding was more likely due to lack of data on several factors that inform care decisions (e.g., comorbid conditions or injuries). Nevertheless, future efforts should seek to increase the capacity of ICUs in low-resource settings to monitor and treat TBI according to international guidelines, and should improve predictive modeling to identify risk for poor outcome.

Machine Learning for Predicting In-Hospital Mortality After Traumatic Brain Injury in Both High-Income and Low- and Middle-Income Countries

BACKGROUND

Machine learning (ML) holds promise as a tool to guide clinical decision making by predicting in-hospital mortality for patients with traumatic brain injury (TBI). Previous models such as the international mission for prognosis and clinical trials in TBI (IMPACT) and the corticosteroid randomization after significant head injury (CRASH) prognosis calculators can potentially be improved with expanded clinical features and newer ML approaches.

OBJECTIVE

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.

METHODS

We used the Duke University Medical Center National Trauma Data Bank and Mulago National Referral Hospital (MNRH) registry to predict in-hospital mortality for the HIC and LMIC settings, respectively. Six ML models were built on each data set, and the best model was chosen through nested cross-validation. The CRASH and IMPACT models were externally validated on the MNRH database.

RESULTS

ML models built on National Trauma Data Bank (n = 5393, 84 predictors) demonstrated an area under the receiver operating curve (AUROC) of 0.91 (95% CI: 0.85-0.97) while models constructed on MNRH (n = 877, 31 predictors) demonstrated an AUROC of 0.89 (95% CI: 0.81-0.97). Direct comparison with CRASH and IMPACT models showed significant improvement of the proposed LMIC models regarding AUROC (P = .038).

CONCLUSION

We developed high-performing well-calibrated ML models for predicting in-hospital mortality for both the HIC and LMIC settings that have the potential to influence clinical management and traumatic brain injury patient trajectories.

Mobile telephone follow-up assessment of postdischarge death and disability due to trauma in Cameroon: a prospective cohort study

OBJECTIVES

In Cameroon, long-term outcomes after discharge from trauma are largely unknown, limiting our ability to identify opportunities to reduce the burden of injury. In this study, we evaluated injury-related death and disability in Cameroonian trauma patients over a 6-month period after hospital discharge.

DESIGN

Prospective cohort study.

SETTING

Four hospitals in the Littoral and Southwest regions of Cameroon.

PARTICIPANTS

A total of 1914 patients entered the study, 1304 were successfully contacted. Inclusion criteria were patients discharged after being treated for traumatic injury at each of four participating hospitals during a 20-month period. Those who did not possess a cellular phone or were unable to provide a phone number were excluded.

PRIMARY AND SECONDARY OUTCOME MEASURES

The Glasgow Outcome Scale-Extended (GOSE) was administered to trauma patients at 2 weeks, 1 month, 3 months and 6 months post discharge. Median GOSE scores for each timepoint were compared and regression analyses were performed to determine associations with death and disability.

RESULTS

Of 71 deaths recorded, 90% occurred by 2 weeks post discharge. At 6 months, 22% of patients still experienced severe disability. Median (IQR) GOSE scores at the four timepoints were 4 (3-7), 5 (4-8), 7 (4-8) and 7 (5-8), respectively, (p<0.01). Older age was associated with greater odds of postdischarge disability (OR: 1.23, 95% CI: 1.07 to 1.41) and mortality (OR: 2.15, 95% CI: 1.52 to 3.04), while higher education was associated with decreased odds of disability (OR: 0.65, 95% CI: 0.58 to 0.73) and mortality (OR: 0.38, 95% CI: 0.31 to 0.47). Open fractures (OR: 1.73, 95% CI: 1.38 to 2.18) and closed fractures (OR: 1.83, 95% CI: 1.42 to 2.36) were associated with greater postdischarge disability, while higher Injury Severity Score (OR: 2.44, 95% CI: 2.13 to 2.79) and neurological injuries (OR: 4.40, 95% CI: 3.25 to 5.96) were associated with greater odds of postdischarge mortality.

CONCLUSION

Mobile follow-up data show significant morbidity and mortality, particularly for orthopaedic and neurologic injuries, up to 6 months following trauma discharge. These results highlight the need for reliable follow-up systems in Cameroon.

What intensive care registries can teach us about outcomes

PURPOSE OF REVIEW

Critical care registries are synonymous with measurement of outcomes following critical illness. Their ability to provide longitudinal data to enable benchmarking of outcomes for comparison within units over time, and between units, both regionally and nationally is a key part of the evaluation of quality of care and ICU performance as well as a better understanding of case-mix. This review aims to summarize literature on outcome measures currently being reported in registries internationally, describe the current strengths and challenges with interpreting existing outcomes and highlight areas where registries may help improve implementation and interpretation of both existing and new outcome measures.

RECENT FINDINGS

Outcomes being widely reported through ICU registries include measures of survival, events of interest, patient-reported outcomes and measures of resource utilization (including cost). Despite its increasing adoption, challenges with quality of reporting of outcomes measures remain. Measures of short-term survival are feasible but those requiring longer follow-ups are increasingly difficult to interpret given the evolving nature of critical care in the context of acute and chronic disease management. Furthermore, heterogeneity in patient populations and in healthcare organisations in different settings makes use of outcome measures for international benchmarking at best complex, requiring substantial advances in their definitions and implementation to support those seeking to improve patient care.

SUMMARY

Digital registries could help overcome some of the current challenges with implementing and interpreting ICU outcome data through standardization of reporting and harmonization of data. In addition, ICU registries could be instrumental in enabling data for feedback as part of improvement in both patient-centred outcomes and in service outcomes; notably resource utilization and efficiency.

Emerging Applications for Quantitative Susceptibility Mapping in the Detection of Traumatic Brain Injury Pathology

Traumatic brain injury (TBI) is a common but heterogeneous injury underpinned by numerous complex and interrelated pathophysiological mechanisms. An essential trace element, iron is abundant within the brain and involved in many fundamental neurobiological processes, including oxygen transportation, oxidative phosphorylation, myelin production and maintenance, as well as neurotransmitter synthesis and metabolism. Excessive levels of iron are neurotoxic and thus iron homeostasis is tightly regulated in the brain, however, many details about the mechanisms by which this is achieved are yet to be elucidated. A key mediator of oxidative stress, mitochondrial dysfunction and neuroinflammatory response, iron dysregulation is an important contributor to secondary injury in TBI. Advances in neuroimaging that leverage magnetic susceptibility properties have enabled increasingly comprehensive investigations into the distribution and behaviour of iron in the brain amongst healthy individuals as well as disease states such as TBI. Quantitative Susceptibility Mapping (QSM) is an advanced neuroimaging technique that promises quantitative estimation of local magnetic susceptibility at the voxel level. In this review, we provide an overview of brain iron and its homeostasis, describe recent advances enabling applications of QSM within the context of TBI and summarise the current state of the literature. Although limited, the emergent research suggests that QSM is a promising neuroimaging technique that can be used to investigate a host of pathophysiological changes that are associated with TBI.

Face-to-Face Versus Telephonic Extended Glasgow Outcome Score Testing After Traumatic Brain Injury

OBJECTIVE

The Extended Glasgow Outcome Scale (GOS-E) is used for objective assessment of functional outcome in traumatic brain injury (TBI). In situations where face-to-face contact is not feasible, telephonic assessment of the GOS-E might be desirable. The aim of this study is to assess the level of agreement between face-to-face and telephonic assessment of the GOS-E.

SETTING

Multicenter study in 2 Dutch University Medical Centers. Inclusion was performed in the outpatient clinic (face-to-face assessment, by experienced neurologist), followed by assessment via telephone of the GOS-E after ±2 weeks (by trained researcher).

PARTICIPANTS

Patients ±6 months after TBI.

DESIGN

Prospective validation study.

MAIN MEASURES

Interrater agreement of the GOS-E was assessed with Cohen's weighted κ.

RESULTS

From May 2014 until March 2018, 50 patients were enrolled; 54% were male (mean age 49.1 years). Median time between trauma and in-person GOS-E examination was 158 days and median time between face-to-face and telephonic GOS-E was 15 days. The quadratic weighted κ was 0.79. Sensitivity analysis revealed a quadratic weighted κ of 0.77, 0.78, and 0.70 for moderate-severe, complicated mild, and uncomplicated mild TBI, respectively.

CONCLUSION

No disagreements of more than 1 point on the GOS-E were observed, with the κ value representing good or substantial agreement. Assessment of the GOS-E via telephone is a valid alternative to the face-to-face interview when in-person contact is not feasible.

The pattern of hospital-community-home (HCH) nursing in tracheostomy patients with severe traumatic brain injury: Is it feasible?

BACKGROUND

Tracheostomy is very common in patients with severe traumatic brain injury (TBI), long-term nursing care are needed for those patients. We aimed to evaluate the effects of hospital-community-home (HCH) nursing in those patients.

METHODS

This study was a before-after study design. Patients were divided into control groups (traditional nursing care) and HCH group(HCH nursing care). Tracheostomy patients with severe TBI needing long-term care were included. All patients underwent a two-month long follow-up. Glasgow coma score (GCS), Karnofsky, Self-Anxiety Scale (SAS) from caregiver and Barthel assessment at the discharge and two months after discharge were evaluated. The tracheostomy-related complications were recorded and compared.

RESULTS

A total of 60 patients were included. There were no significant differences between the two groups in the GCS, Karnofsky, SAS from caregiver and Barthel index at discharge((all P > .05); the GCS, Karnofsky and Barthel index were all significantly increased after two-month follow-up for the two groups (all P < .05), and the GCS, Karnofsky and Barthel index at two-month follow-up in HCH group were significantly higher than that of the control group(all P < .05), but the SAS from caregiver at two-month follow-up in HCH group was significantly less than that of the control group(P = .009). The incidence of block of artificial tracheal cannula and readmission in HCH group were significant less than that of control group (all P < .05).

CONCLUSION

HCH nursing care is feasible in tracheostomy patients with severe TBI, future studies are needed to further evaluate the role of HCH nursing care.

Delirium as a predictor of mortality and disability among hospitalized patients in Zambia

OBJECTIVE

To study the epidemiology and outcomes of delirium among hospitalized patients in Zambia.

METHODS

We conducted a prospective cohort study at the University Teaching Hospital in Lusaka, Zambia, from October 2017 to April 2018. The primary exposure was delirium duration over the initial 3 days of hospitalization, assessed daily using the Brief Confusion Assessment Method. The primary outcome was 6-month mortality. Secondary outcomes included 6-month disability, evaluated using the World Health Organization Disability Assessment Schedule 2.0.

FINDINGS

711 adults were included (median age, 39 years; 461 men; 459 medical, 252 surgical; 323 with HIV). Delirium prevalence was 48.5% (95% CI, 44.8%-52.3%). 6-month mortality was higher for delirious participants (44.6% [39.3%-50.1%]) versus non-delirious participants (20.0% [15.4%-25.2%]; P < .001). After adjusting for covariates, delirium duration independently predicted 6-month mortality and disability with a significant dose-response association between number of days with delirium and odds of worse clinical outcome. Compared to no delirium, presence of 1, 2 or 3 days of delirium resulted in odds ratios for 6-month mortality of 1.43 (95% CI, 0.73-2.80), 2.20 (1.07-4.51), and 3.92 (2.24-6.87), respectively (P < .001). Odds of 6-month disability were 1.20 (0.70-2.05), 1.73 (0.95-3.17), and 2.80 (1.78-4.43), respectively (P < .001).

CONCLUSION

Among hospitalized medical and surgical patients in Zambia, delirium prevalence was high and delirium duration independently predicted mortality and disability at 6 months. This work lays the foundation for prevention, detection, and management of delirium in low-income countries. Long-term follow up of outcomes of critical illness in resource-limited settings appears feasible using the WHO Disability Assessment Schedule.

Neurosurgical Randomized Trials in Low- and Middle-Income Countries

BACKGROUND

The setting of a randomized trial can determine whether its findings are generalizable and can therefore apply to different settings. The contribution of low- and middle-income countries (LMICs) to neurosurgical randomized trials has not been systematically described before.

OBJECTIVE

To perform a systematic analysis of design characteristics and methodology, funding source, and interventions studied between trials led by and/or conducted in high-income countries (HICs) vs LMICs.

METHODS

From January 2003 to July 2016, English-language trials with >5 patients assessing any one neurosurgical procedure against another procedure, nonsurgical treatment, or no treatment were retrieved from MEDLINE, Scopus, and Cochrane Library. Income classification for each country was assessed using the World Bank Atlas method.

RESULTS

A total of 73.3% of the 397 studies that met inclusion criteria were led by HICs, whereas 26.7% were led by LMICs. Of the 106 LMIC-led studies, 71 were led by China. If China is excluded, only 8.8% were led by LMICs. HIC-led trials enrolled a median of 92 patients vs a median of 65 patients in LMIC-led trials. HIC-led trials enrolled from 7.6 sites vs 1.8 sites in LMIC-led studies. Over half of LMIC-led trials were institutionally funded (54.7%). The majority of both HIC- and LMIC-led trials evaluated spinal neurosurgery, 68% and 71.7%, respectively.

CONCLUSION

We have established that there is a substantial disparity between HICs and LMICs in the number of published neurosurgical trials. A concerted effort to invest in research capacity building in LMICs is an essential step towards ensuring context- and resource-specific high-quality evidence is generated.

Critical care outcomes in resource-limited settings

PURPOSE OF REVIEW

The burden of critical illness in low-income and middle-income countries (LMICs) is substantial. A better understanding of critical care outcomes is essential for improving critical care delivery in resource-limited settings. In this review, we provide an overview of recent literature reporting on critical care outcomes in LMICs. We discuss several barriers and potential solutions for a better understanding of critical care outcomes in LMICs.

RECENT FINDINGS

Epidemiologic studies show higher in-hospital mortality rates for critically ill patients in LMICs as compared with patients in high-income countries (HICs). Recent findings suggest that critical care interventions that are effective in HICs may not be effective and may even be harmful in LMICs. Little data on long-term and morbidity outcomes exist. Better outcomes measurement is beginning to emerge in LMICs through decision support tools that report process outcome measures, studies employing mobile health technologies with community health workers and the development of context-specific severity of illness scores.

SUMMARY

Outcomes from HICs cannot be reliably extrapolated to LMICs, so it is important to study outcomes for critically ill patients in LMICs. Specific challenges to achieving meaningful outcomes studies in LMICs include defining the critically ill population when few ICU beds exist, the resource-intensiveness of long-term follow-up, and the need for reliable severity of illness scores to interpret outcomes. Although much work remains to be done, examples of studies overcoming these challenges are beginning to emerge.