<i>In Vitro</i>Antibiotic Susceptibility Pattern of Non-diphtheriae Corynebacterium Isolates in Ontario, Canada, from 2011 to 2016
Bibliographic record
Abstract
ABSTRACT Non- diphtheriae Corynebacterium -associated disease has been increasingly observed and often presents a conundrum to the treating physician. Analysis of antibiotic susceptibility testing data for 1,970 clinical Corynebacterium isolates received between 2011 and 2016 revealed that empirical drug treatment options are limited to vancomycin and linezolid. Corynebacterium striatum was the most frequently observed species during this study period, along with C. amycolatum and C. pseudodiphtheriticum/C. propinquum . Low levels of susceptibility to penicillin (14.5%), erythromycin (15.1%), and clindamycin (8.7%) were observed for non- diphtheriae Corynebacterium species, while 3.0% of isolates were not susceptible to daptomycin. Similarly, 26.9% and 38.1% of Corynebacterium isolates were susceptible to ciprofloxacin and trimethoprim-sulfamethoxazole, respectively. Our data show much lower susceptibility to penicillin than previously reported in the literature and an increasing number of isolates resistant to daptomycin, highlighting the need for continued antibiotic surveillance studies for appropriate patient management and treatment success.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".