Transfusions, disease-modifying treatments, and curative therapies for sickle cell anemia in Africa: where are we now?
Bibliographic record
Abstract
The mortality burden of sickle cell anemia (SCA) is centered in sub-Saharan Africa. In addition to a lack of systematic programs for early diagnosis, access to disease-modifying treatments is limited to only a few urban centers. Providing a safe and adequate blood supply is a major challenge, heightening mortality from SCA-associated complications that require urgent blood transfusion and making the delivery of regular transfusion therapy for stroke prevention nonfeasible. Hydroxyurea therapy with proven clinical benefits for pain episodes, acute chest syndrome, malaria, transfusions, hospitalizations, and stroke prevention is the most feasible treatment for SCA in Africa. Access barriers to hydroxyurea treatment include poor availability, unaffordable costs, health professionals' reluctance to prescribe, a lack of national guidelines, and exaggerated fears about drug toxicities. Strategies for the local manufacture of hydroxyurea combined with the systematic education and training of health professionals using guidelines supported by the World Health Organization can help surmount the access barriers. Hematopoietic stem cell transplantation as a curative therapy is available in only 7 countries in Africa. The few patients who have suitable sibling donors and can afford a transplant must usually travel out of the country for treatment, returning to their home countries where expertise and resources for posttransplant follow-up are lacking. The recently developed ex-vivo gene therapies are heavily dependent on technical infrastructure to deliver, a daunting challenge for Africa. Future in-vivo gene therapies that bypass myeloablation and ex-vivo processing would be more suitable. However, enthusiasm for pursuing these gene therapies should not overlook strategies to make hydroxyurea universally accessible in Africa.
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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) | 0.002 | 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 | 0.000 |
| Research integrity | 0.001 | 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".