Antibiotics needed to treat multidrug-resistant infections in neonates
Bibliographic record
Abstract
Infections remain a leading cause of death in neonates. The sparse antibiotic development pipeline and challenges in conducting neonatal research have resulted in few effective antibiotics being adequately studied to treat multidrug-resistant (MDR) infections in neonates, despite the increasing global mortality burden caused by antimicrobial resistance. Of 40 antibiotics approved for use in adults since 2000, only four have included dosing information for neonates in their labelling. Currently, 43 adult antibiotic clinical trials are recruiting patients, compared with only six trials recruiting neonates. We review the World Health Organization (WHO) priority pathogens list relevant to neonatal sepsis and propose a WHO multiexpert stakeholder meeting to promote the development of a neonatal priority antibiotic development list. The goal is to develop international, interdisciplinary consensus for an accelerated neonatal antibiotic development programme. This programme would enable focused research on identified priority antibiotics for neonates to reduce the excess morbidity and mortality caused by MDR infections in this vulnerable population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".