Dose escalation study of bovine lactoferrin in preterm infants: getting the dose right
Bibliographic record
Abstract
Lactoferrin as a nutritional enteral supplement has emerged as a novel preventative therapy against serious infections in preterm infants, although neonatal studies have demonstrated variable results, in part due to the lack of pharmacokinetic data and differences in the products tested. We conducted a prospective, dose escalation (100, 200, and 300 mg·kg–1·day–1) safety study of bovine lactoferrin (Glanbia Nutritionals, USA) dissolved in sterile water (100 mg·mL–1) for 30 days in preterm infants with birth weight <1500 g. Safety related to adverse events (AEs), tolerability, and exposure-response of lactoferrin was assessed. We enrolled 31 patients [10, 10, and 11 patients, for the lactoferrin treatment groups (100, 200, and 300 mg·kg–1·day–1, respectively)] over a 10-month period. No AEs related to the study solution occurred, and lactoferrin was tolerated by each group. During lactoferrin supplementation, one bloodstream infection occurred in each group, but there were no incidences of urinary tract infections and no cases of necrotizing enterocolitis. Postnatal cytomegalovirus acquisition was detected in the group treated with 200 mg·kg–1·day–1 (n = 2). There were no adverse effects on hepatic, renal, or hematologic function. All of the patients survived to discharge. Bovine lactoferrin at doses up to 300 mg·kg–1·day–1 is safe in preterm infants. Future studies examining higher doses of lactoferrin, length of treatment, and potency of different products will aid in determining the optimal approach for the use of lactoferrin to prevent infections in preterm infants.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".