<i>In vitro</i> activity of sulopenem against 1880 bacterial pathogens isolated from Canadian patients with urinary tract infections (CANWARD, 2014–21)
Bibliographic record
Abstract
INTRODUCTION: There are limited oral antimicrobial options for the treatment of urinary infections caused by ESBL-producing and MDR Enterobacterales. Sulopenem is an investigational thiopenem antimicrobial that is being developed as both an oral and IV formulation. The purpose of this study was to evaluate the in vitro activity of sulopenem versus bacterial pathogens recovered from the urine of patients admitted to or assessed at hospitals across Canada (CANWARD). MATERIALS AND METHODS: The in vitro activity of sulopenem and clinically relevant comparators was determined for 1880 Gram-negative and Gram-positive urinary isolates obtained as part of the CANWARD study (2014 to 2021) using the CLSI broth microdilution method. RESULTS: Sulopenem demonstrated excellent in vitro activity versus members of the Enterobacterales, with MIC90 values ranging from 0.06 to 0.5 mg/L for all species tested. Over 90% of ESBL-producing, AmpC-producing and MDR (not susceptible to ≥1 antimicrobial from ≥3 classes) Escherichia coli were inhibited by ≤0.25 mg/L of sulopenem. Sulopenem had an identical MIC90 to meropenem for ESBL-producing and MDR E. coli. The MIC90 of sulopenem and meropenem versus MSSA was 0.25 mg/L. Sulopenem was not active in vitro versus Pseudomonas aeruginosa (similar to ertapenem), and it demonstrated poor activity versus Enterococcus faecalis (similar to meropenem). CONCLUSIONS: Sulopenem demonstrated excellent in vitro activity versus bacterial pathogens recovered from the urine of Canadian patients. These data suggest that sulopenem may have a role in the treatment of urinary infections caused by antimicrobial-resistant Enterobacterales, but additional clinical studies are required.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".