COMPARISON OF ANTIMICROBIAL SENSITIVITY TO OLDER AND NEWER QUINOLONES VERSUS PIPERACILLIN-TAZOBACTAM, CEFEPIME AND MEROPENEM IN FEBRILE PATIENTS WITH CANCER IN TWO REFERRAL PEDIATRIC CENTERS IN TEHRAN, IRAN
Bibliographic record
Abstract
BACKGROUND: Infection in pediatric cancer patients has become a concerning problem due to increasing antimicrobial resistance. The goal of this study was to determine the antimicrobial resistance patterns of blood isolates from pediatric oncology patients in Iran to determine if there was significant resistance to quinolones. METHODS: Children with cancer who were admitted with or developed fever during admission to Aliasghar Children's Hospital or Mahak Hospitals July 2009 through June 2011 were eligible for enrollment. Two blood cultures were obtained. Antimicrobial sensitivity test was performed for ciprofloxacin, moxifloxacin, gatifloxacin, meropenem, cefepime, and piperacillin-tazobactam on isolates from children who were bacteremic. RESULTS: Blood cultures were positive for 38 episodes in 169 enrolled children but 9 episodes were excluded as blood cultures were thought to be contaminated, yielding a bacteremia rate of 29/160 (18%). The mean age of children and the stage of malignancy did not differ between those with and without bacteremia. Meropenem was the most likely antibiotic to cover isolates (97%) with cefepime having the lowest coverage rate (21%). Quinolone coverage ranged from 63% to 76%. CONCLUSION: Quinolones may not be suitable for use as empiric therapy in febrile pediatric oncology patients in Iran.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".