Early neurodevelopmental markers predictive of mortality in infants infected with HIV‐1
Bibliographic record
Abstract
One-hundred and fifty-seven vertically infected HIV-1 positive infants (85 males, 72 females) underwent longitudinal assessment to determine whether early neurodevelopmental markers are useful predictors of mortality in those infants who survive to at least 4 months of age. Survival analysis methods were used to estimate time to death for quartiles of 4-month scores (baseline) on the Bayley Scales of Infant Development (BSID). Cox proportional hazards progression was used to estimate relative hazard (RH, 95% CI) of death for BSID scores and potential confounders. Thirty infants with BSID scores at 4 months of age died during follow-up. Survival analysis revealed greater mortality rates in infants with BSID (Mental Developmental Index and Psychomotor Developmental Index) scores in the lower quartile (p=0.004, p=0.036). Unadjusted univariate analyses revealed increased mortality associated with baseline CD4+ 29%, gestational age <37 weeks, smaller head circumference, advanced HIV and higher plasma viral load. BSID scores independently predicted mortality after adjusting for treatment, clinical category, gestational age, plasma viral load and CD4+ percentage.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".