Prevention of Nosocomial Infections in Critically Ill Patients With Lactoferrin: A Randomized, Double-Blind, Placebo-Controlled Study
Bibliographic record
Abstract
OBJECTIVE: To obtain preliminary evidence for the efficacy of lactoferrin as a preventative measure for nosocomial infections and inform the conduct of a definitive study. DESIGN: Phase 2, multicenter, randomized, double-blind, placebo-controlled study. SETTING: Medical-surgical ICUs. PATIENTS: Adult, critically ill patients receiving invasive mechanical ventilation. INTERVENTIONS: Randomized, eligible, consenting patients expected to require invasive mechanical ventilation more than 48 hours received lactoferrin both enterally and via an oral swab or a placebo of sterile water for up to 28 days. MEASUREMENTS AND MAIN RESULTS: Of the 214 patients who were randomized, 212 received at least one dose of the intervention and were analyzed (107 lactoferrin and 105 placebo). Protocol adherence was 87.5%. Patients receiving lactoferrin were older (mean [SD], 66.3 [13.5] vs 62.5 [16.2] yr), had a higher Acute Physiology and Chronic Health Evaluation II score (26.8 [7.8] vs 23.5 [7.9]), and need for vasopressors (79% vs 70%). Antibiotic-free days (17.3 [9.0] vs 18.5 [7.1]; p = 0.91) and nosocomial infections (0.3 [0.7] vs 0.4 [0.6] per patient; p = 0.48) did not differ between lactoferrin and placebo groups, respectively. Clinical outcomes for lactoferrin versus placebo were as follows: ICU length of stay (14.5 [18.0] vs 15.0 [37.3] d; p = 0.82), hospital length of stay (25.0 [25.9] vs 28.1 [44.6] d; p = 0.57), hospital mortality (41.1% vs 30.5%; p = 0.11), and 90-day mortality (44.9% vs 32.4%; p = 0.06). Biomarker levels did not differ between the groups. CONCLUSIONS: Lactoferrin did not improve the primary outcome of antibiotic-free days, nor any of the secondary outcomes. Our data do not support the conduct of a larger phase 3 trial.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".