Hydroxyurea to lower transcranial Doppler velocities and prevent primary stroke: the Uganda NOHARM sickle cell anemia cohort
Bibliographic record
Abstract
Hydroxyurea to lower transcranial Doppler velocities and prevent primary stroke: the Uganda NOHARM sickle cell anemia cohortIn sub-Saharan Africa, sickle cell anemia (SCA) remains a significant public health problem with high mortality: an estimated 50-90% of affected children die before 5 years of age. 1 A high prevalence of stroke is particularly devastating for children and has substantial morbidity.2,3 Hydroxyurea is now recommended across the lifespan as a safe and effective disease-modifying therapy for SCA, 4,5 but is not routinely available in sub-Saharan Africa.6 NOHARM (NCT01976416), a randomized doubleblinded, placebo-controlled trial, was among the first prospective studies to investigate hydroxyurea treatment for children with SCA living in a malaria endemic region within Africa.The NOHARM trial consisted of a blinded phase (Year 1) and an open-label phase (Year 2).7 Initially children 1.00-4.99years of age were randomized either to placebo or fixed-dose hydroxyurea (20 mg/kg/day).The Year 1 results demonstrated that short-term hydroxyurea treatment was both safe and efficacious in this young patient population living in a malarial endemic region.[8] We now analyze Year 2 data from the openlabel phase, in which all NOHARM participants received hydroxyurea at 20 mg/kg/day, to compare the effects of hydroxyurea on SCA-related morbidity and also to provide serial transcranial Doppler (TCD) data, which were not included in the original randomized report.NOHARM was conducted at the Mulago Hospital Sickle Cell Clinic in Kampala, Uganda.A detailed description of the study design, site, study participants, and process for the blinded phase has previously been published.7,8 All study participants were given the opportunity to receive open-label hydroxyurea for 12 months, after the first year of randomized treatment, since there was no evidence from interim analysis of harm for the hydroxyurea arm compared to placebo.Study outcomes included rates of clinical malaria, clinical sickle cell-related adverse events (AE), serious adverse events, hematological toxicities, and laboratory benefits, as well as TCD velocities.Ethical and regulatory approvals were dosing strategies and monitoring regimens, in an effort to determine the overall feasibility and safety of introducing hydroxyurea therapy for SCA widely across sub-Saharan Africa.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".