Burden of neurological and neurocognitive impairment in pediatric sickle cell anemia in Uganda (BRAIN SAFE): a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Children with sickle cell anemia (SCA) are highly susceptible to stroke and other manifestations of pediatric cerebral vasculopathy. Detailed evaluations in sub-Saharan Africa are limited. METHODS: We aimed to establish the frequency and types of pediatric brain injury in a cross-sectional study at a large SCA clinic in Kampala, Uganda in a randomly selected sample of 265 patients with HbSS ages 1-12 years. Brain injury was defined as one or more abnormality on standardized testing: neurocognitive impairment using an age-appropriate test battery, prior stroke by examination or transcranial Doppler (TCD) velocities associated with stroke risk in children with SCA (cerebral arterial time averaged mean maximum velocity ≥ 170 cm/second). RESULTS: Mean age was 5.5 ± 2.9 years; 52.3% were male. Mean hemoglobin was 7.3 ± 1.01 g/dl; 76.4% had hemoglobin < 8.0 g/dl. Using established international standards, 14.7% were malnourished, and was more common in children ages 5-12. Overall, 57 (21.5%) subjects had one to three abnormal primary testing. Neurocognitive dysfunction was found in 27, while prior stroke was detected in 15 (5.7%). The most frequent abnormality was elevated TCD velocity 43 (18.1%), of which five (2.1%) were in the highest velocity range of abnormal. Only impaired neurocognitive dysfunction increased with age (OR 1.44, 95%CI 1.23-1.68), p < 0.001). In univariate models, malnutrition defined as wasting (weight-for-height ≤ -2SD), but not sex or hemoglobin, was modestly related to elevated TCD (OR 1.37, 95%CI 1.01-1.86, p = 0.04). In adjusted models, neurocognitive dysfunction was strongly related to prior stroke (OR 6.88, 95%CI 1.95-24.3, p = .003) and to abnormal TCD (OR 4.37, 95%CI 1.30, p = 0.02). In a subset of 81 subjects who were enriched for other abnormal results, magnetic resonance imaging and angiography (MRI/MRA) detected infarcts and/or arterial stenosis in 52%. Thirteen subjects (25%) with abnormal imaging had no other abnormalities detected. CONCLUSIONS: The high frequency of neurocognitive impairment or other abnormal results describes a large burden of pediatric SCA brain disease in Uganda. Evaluation by any single modality would have underestimated the impact of SCA. Testing the impact of hydroxyurea or other available disease-modifying interventions for reducing or preventing SCA brain effects is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".