Impact Of Hydroxyurea Adherence Levels On Hematological And Clinical Outcomes In Children With Sickle Cell Disease: A Systematic Review In Sub-Saharan Africa
Bibliographic record
Abstract
Background: Hydroxyurea (HU) therapy success relies heavily on adherence, which remains suboptimal in Sub-Saharan Africa (SSA), with over 90% of global pediatric Sickle Cell Disease (SCD) cases. Appropriate HU therapy in this population is crucial in extending life expectancy and curbing the high mortality rate. Aim: We aimed to synthesize available literature on HU adherence, methods of measuring adherence levels, and its impact on hematological and clinical outcomes in children with SCD in SSA. Method: All studies indexed in PubMed, Embase, Cochrane Library, ScienceDirect/Elsevier, Ovid, and Google Scholar published in English between 2010 and 2025 were searched. Original studies on the query topics were included and findings were categorized and narratively synthesized. Adherence data, including the quality of data reporting bias, were evaluated using the Newcastle-Ottawa Scale for observational studies. The review followed the PRISMA framework for systematic reviews. The review protocol was registered in the PROSPERO database (ID CRD420251012201). Result: Out of the 226 studies screened, only four met our inclusion criteria, comprising two cross-sectional, and two cohort studies. Three adherence measurement methods were identified: retrospective review of medical records, Morisky Medication-Taking Adherence Scale (MMAS-4), and feasibility assessments (enrollment and retention rates). Studies reported that high adherence (≥75%) was associated with improved hematological and clinical outcomes regardless of the method employed. Persistent barriers to adherence included socioeconomic challenges, limited access to healthcare, and caregiver-related factors, which collectively hindered optimal HU utilization. Meta-analysis was not feasible due to a lack of key statistical metrics and heterogenicity in adherence measurement methods between the studies. Conclusion: Our review highlights a significant gap in research on HU adherence in pediatric populations in SSA, emphasizing the importance of high adherence rates for improving hematological and clinical outcomes. Recommendation: Future research should prioritize robust, multi-center, and longitudinal studies to explore adherence dynamics, while healthcare systems must adopt innovative adherence monitoring tools, enhance caregiver support, and address systemic challenges through targeted interventions, policy reforms, and infrastructure improvements to mitigate the clinical burden of SCD in SSA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".