Antimicrobial Resistance in<i>Haemophilus influenzae:</i>How Can We Prevent the Inevitable? Commentary on Antimicrobial Resistance in<i>H. influenzae</i>Based on Data from the TARGETed Surveillance Program
Bibliographic record
Abstract
Haemophilus influenzae is an important cause of respiratory tract infections, particularly in elderly persons. It is the major bacterial pathogen in acute exacerbations of chronic bronchitis (AECB) and also causes otitis media and sinusitis. In many cases, treatment is empiric, and there is a lack of understanding of resistance issues with this bacterium. There is little understanding of the epidemiology of H. influenzae respiratory infections, although some strains may be replaced by new strains that cause more severe infections. There is almost no information on how these bacteria may spread in the community. Ampicillin resistance is significant (it may be >30%), and there are few oral agents capable of reducing organism burden. There is little understanding of the epidemiology of H. influenzae respiratory infections, and almost no information on how these bacteria may spread in the community. Recent evidence suggests that these bacteria may behave in a similar way to Streptococcus pneumoniae. If that proves correct, then it will be important to follow these organisms in the community to determine if resistance determinants may spread more widely than we have thus far believed. The implications for treatment, infection prevention and control, and public health should not be underestimated as it has been with other organisms such as S. pneumoniae and Staphylococcus aureus.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".