In Vitro Inferiority of Ceftazidime Compared With Other β-lactams for Viridans Group Streptococcus Bacteremia in Pediatric Oncology Patients
Bibliographic record
Abstract
Viridans group Streptococcus (VGS) is a leading cause of bacteremia in pediatric oncology patients, primarily in children with acute myeloid leukemia or after hematopoietic stem cell transplantation. We retrospectively identified all positive blood cultures in oncology patients at the British Columbia Children's Hospital for a period of 54 months. VGS was the second most commonly isolated pathogen, present in 19% of all the positive blood cultures. Susceptibility analysis of 46 VGS isolates from that period was performed using the Etest method for penicillin, cefotaxime, ceftazidime, and piperacillin/tazobactam. The geometric mean minimal inhibitory concentration for ceftazidime was found to be 9 to 12-fold higher than for any other beta-lactam antibiotic. Penicillin resistance was of 13% with an additional 20% of samples with intermediate susceptibility. The study underscores the prevalence of VGS bacteremia in pediatric patients, especially with acute myeloid leukemia or postallogeneic hematopoietic stem cell transplantation, and the in vitro inferiority of ceftazidime compared with other beta-lactams in that context. We conclude that monotherapy with ceftazidime, or its use along with an aminoglycoside, is not an optimal therapy in pediatric oncology patients with febrile neutropenia.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".