Hospital-acquired bacterial pneumonia (HABP) and ventilator-associated bacterial pneumonia (VABP) in Canada: treatment update and the role of new IV antimicrobials
Bibliographic record
Abstract
INTRODUCTION: Hospital-acquired bacterial pneumonia (HABP) and ventilator-associated bacterial pneumonia (VABP) continue to be common infections causing significant morbidity and mortality worldwide. The timely initiation of empiric antimicrobial therapy is essential. In this paper, we provide a focused expert opinion on the current and potential empiric antimicrobial treatment options in HABP and VABP in Canada influenced by antimicrobial resistance impacting the use of older agents as well as available new intravenous (IV) antimicrobials. AREAS COVERED: The authors discuss treatment options for HABP and VABP in Canada. In addition, we focus on the potential role of new IV antimicrobials recently introduced to Canada. A literature search of HABP and VABP treatments was performed via PubMed (up to March 2023), using the following key words: monotherapy, combination therapy, aminoglycosides, carbapenems, cephalosporins, fluoroquinolones, penicillins as well as amoxicillin/clavulanate, ceftobiprole, ceftolozane/tazobactam, dalbavancin, and fosfomycin. EXPERT OPINION: Empiric antimicrobial treatment for HABP and VABP in Canada continues to focus on both the severity of illness and the presence/absence of patient risk factors for antimicrobial resistance. The role of new IV antimicrobials in the empiric treatment for HABP and VABP depends on their antimicrobial activity and published data on efficacy and safety and influenced by Health Canada-approved indications.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".