The prevalence of Hemophilia A in males in Africa: evidence from a systematic review and meta-analysis
Bibliographic record
Abstract
Hemophilia A (HA) is an X-linked recessive bleeding disorder characterized by reduced or absent coagulation factor (F) VIII activity. The empirical evidence on the prevalence of HA in Africa has reported inconsistent findings and seems to present such a wide range of prevalence that it is hard to swiftly ascertain its average extent. Hence, this review aimed to pool the results of primary studies reporting the prevalence of HA into a single estimate in the region. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Articles published in EMBASE, PubMed, Web of Science, SCOPUS, Science Direct, and Cochrane Library databases were searched. Observational studies revealing the prevalence of HA in Africa between 2010 and 2023 were incorporated. We assessed the quality of each study using the Newcastle-Ottawa quality assessment tool. The prevalence of HA was estimated as the cases (the sample size) per 100,000 population multiplied by 1000. To produce the pooled estimate, Der Simonian random-effects models were computed with Metaprop on the STATA command. The studies’ heterogeneity was assessed using the I-squared (I 2 ) value test and the Galbraith plot. A funnel plot was conducted to evaluate publication bias. Of the 337 studies accessed, we included 15 that fulfilled the eligibility criteria. The random-effect model meta-analysis demonstrated the overall pooled prevalence of HA was 6.82 cases per 100,000 persons (95% confidence interval: 5.16, 8.48) with heterogeneity (I 2 = 0.00%, p < 0.001). This systematic review and meta-analysis revealed that HA is an alarming problem that may pose a future threat to public health in Africa. Given the detrimental effects of the disease on health and the complications involved, we recommended that African regions increase patient access to factor VIII medication, improve carrier detection rates, and take the initiative toward the development and access to gene therapy.
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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 | 0.017 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.037 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".