Prevention of nosocomial pneumonia recurrence using a bacteriophage cocktail in intensive care unit
Bibliographic record
Abstract
Chronically critically ill patients are a rapidly growing population requiring long-term intensive care. Lower respiratory tract infections are the main infectious complications in these patients. Adaptive phage prophylaxis may be one of the perspective and insufficiently studied approaches for prevention of respiratory infectious complications in intensive care units. Objective. To study the effectiveness of complex cocktail complex drag of bacteriophages in prevention of infectious respiratory complications in chronically critically ill patients. Material and methods. The study included ICU patients at the Federal Research Clinical Center of Intensive Care and Rehabilitology. Overall sample consisted of 79 patients with severe brain damage. Group 1 (n=41) received complex drag of bacteriophages for prevention of pneumonia, group No. 2 (n=38) — standard therapy. All patients were followed-up for 28 days. Results. Both groups were comparable in gender, age and clinical severity. Microbiological examination revealed multidrug-resistant gram-negative bacteria (Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa) in majority of patients. In the 1st group, resistance genes were less common compared to the control group. Incidence of recurrent pneumonia was lower in the same group. Conclusion. Prophylactic phage therapy can reduce the number of antimicrobial drugs. Incidence of nosocomial pneumonia recurrences after 14 and 21 days was lower in the main group.
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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 | 0.001 |
| 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".