Lower Neutrophil Count Without Clinical Consequence Among Children of African Ancestry Living With HIV in Canada
Bibliographic record
Abstract
OBJECTIVE: To investigate the association between African ancestry and neutrophil counts among children living with HIV (CLWH). We also examined whether medications, clinical conditions, hospitalization, or HIV virologic control were associated with low neutrophil counts or African ancestry. DESIGN: We conducted a secondary analysis of the Early Pediatric Initiation Canada Child Cure Cohort (EPIC4) Study, a multicenter prospective cohort study of CLWH across 8 Canadian pediatric HIV care centers. METHODS: We classified CLWH according to African ancestry, defined as "African," "Caribbean," or "Black" maternal race. Longitudinal laboratory data (white blood cells, neutrophils, lymphocytes, viral load, and CD4 count) and clinical data (hospitalizations, AIDS-defining conditions, and treatments) were abstracted from medical records. RESULTS: Among 217 CLWH (median age 14, 55% female), 145 were of African ancestry and 72 were of non-African ancestry. African ancestry was associated with lower neutrophil counts, white blood cell counts, and neutrophil-lymphocyte ratios. Neutrophil count <1.5 × 109/L was detected in 60% of CLWH of African ancestry, compared with 31% of CLWH of non-African ancestry (P < 0.0001), representing a 2.0-fold higher relative frequency (95% CI: 1.4-2.9). Neutrophil count was on average 0.74 × 109/L (95% CI: 0.45 to 1.0) lower in CLWH of African ancestry (P < 0.0001). Neither neutrophil count<1.5 × 109/L nor African ancestry was associated with medications, hospitalizations, AIDS-defining conditions, or markers of virologic control (viral load, sustained viral suppression, and lifetime nadir CD4). CONCLUSIONS: In CLWH, African ancestry is associated with lower neutrophil counts, without clinical consequences. A flexible evaluation of neutrophil counts in CLWH of African ancestry may avoid unnecessary interventions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".