Implementing Acute Stroke Services in Sub-Saharan Africa: Steps, Progress, and Perspectives from the Tanzania Stroke Project
Bibliographic record
Abstract
INTRODUCTION: Stroke is a leading cause of morbidity and mortality globally, with Africa bearing a disproportionately high burden of poor outcomes. In sub-Saharan Africa, acute stroke care remains inconsistent, with organized stroke units being either absent or rarely available, contributing to the high stroke mortality rates in the region. To address this issue, the Tanzania Stroke Project (TSP) was launched, aimed at establishing acute stroke services at two of the largest tertiary care centers in collaboration with the Tanzanian Ministry of Health, the World Stroke Organization, and Hospital Directorates. METHODS: TSP utilized a three-tier implementation approach to establish a more organized stroke care system in two large academic hospitals. Here, we detail the process of this initiative, which took place between August 2023 and August 2024. The three-tier approach included (1) the establishment of stroke registries; (2) the training of healthcare workers (HCWs); and (3) the development of acute stroke protocols and establishment of stroke units at Muhimbili National Hospital-Mloganzila and Bugando Medical Center in Tanzania. RESULTS: In tier one (stroke registry), two comprehensive stroke registries were established, including 460 adults (mean age 60 ± 15 years). Hemorrhagic stroke was the most common subtype, accounting for 59% of cases (n = 269). Premorbid hypertension was the most prevalent risk factor, affecting 81% (n = 373) of the patients. More than half of patients (58%, n = 171) arrived at the hospital after 24 h from stroke symptoms. Only 11% (n = 50/452) had documented swallowing screenings, and among patients with intracerebral hemorrhage, 11% (n = 28/251) achieved the target for blood pressure control, while 47% (n = 99/213) met blood glucose control targets. The in-hospital mortality rate was 27% (n = 93/340). In tier two (training of HCWs), extensive evidence-based mentorship training was provided with higher participation rates among HCWs at Bugando Medical Center compared to Muhimbili National Hospital-Mloganzila (57% [29/51] vs. 23% [7/31], p = 0.002). In tier three (stroke unit protocols), stroke protocols were developed based on the training and current evidence, leading to the establishment of dedicated stroke units at each facility, with a minimum of 8 beds per unit. The full impact of these implementations has yet to be fully assessed. CONCLUSION: This was the first initiative to implement stroke services at two large tertiary healthcare centers in Tanzania. Our findings highlight the importance of multilevel stakeholder engagement through a 3-tier approach in countries starting to establish stroke services and the need for ongoing quality-of-care monitoring and continuous efforts to sensitize both HCWs and the broader community.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".