Missed opportunities for early infant diagnosis of HIV in rural North-Central Nigeria: A cascade analysis from the INSPIRE MoMent study
Bibliographic record
Abstract
BACKGROUND: Early identification of HIV-infected infants for treatment is critical for survival. Efficient uptake of early infant diagnosis (EID) requires timely presentation of HIV-exposed infants, same-day sample collection, and prompt release of results. The MoMent (Mother Mentor) Nigeria study investigated the impact of structured peer support on EID presentation and maternal retention. This cascade analysis highlights missed opportunities for EID and infant treatment initiation during the study. METHODS: HIV-infected pregnant women and their infants were recruited at 20 rural Primary Healthcare Centers. Routine infant HIV DNA PCR testing was performed at centralized laboratories using dried blood spot (DBS) samples ideally collected by age two months. EID outcomes data were abstracted from study case report forms and facility registers. Descriptive statistics summarized gaps and missed opportunities in the EID cascade. RESULTS: Out of 497 women enrolled, delivery data was available for 445 (90.8%), to whom 415 of 455 (91.2%) infants were live-born. Out of 408 live-born infants with available data, 341 (83.6%) presented for DBS sampling at least once. Only 75.4% (257/341) were sampled, with 81.7% (210/257) sampled at first presentation. Only 199/257 (77.4%) sampled infants had results available up to 28 months post-collection. Two (1.0%) of the 199 infants tested HIV-positive; one infant died before treatment initiation and the other was lost to follow-up. CONCLUSIONS: While nearly 85% of infants presented for sampling, there were multiple missed opportunities, largely due to health system and not necessarily patient-level failures. These included infants presenting without being sampled, presenting multiple times before samples were collected, and getting sampled but results not forthcoming. Finally, neither of the two HIV-positive infants were linked to treatment within the follow-up period, which may have led to the death of one. To facilitate patient compliance and HIV-free infant survival, quality improvement approaches should be optimized for EID commodity availability, consistent DBS sample collection, efficient processing/result release, and prompt infant treatment initiation.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".