Assessing the Theoretical Efficacy of Combination Therapy Against Gram-Negative Infections in Neutropenic Pediatric Cancer Patients: Insights from the Statistical Analysis of Survey Data
Bibliographic record
Abstract
Background: Empirical antibacterial therapy for febrile neutropenia reduces mortality due to Gram-negative blood stream infections (BSIs). Pediatric guidelines recommend monotherapy with an antipseudomonal beta-lactam or a carbapenem and to add a second anti-Gram-negative agent in selected situations. We evaluated the changes in the proportions of resistance of beta-lactam monotherapies vs. their combination with amikacin, and the possible impact on ICU admission or death. Results: 797 BSIs due to Gram-negative bacteria in 685 patients were included. Combination therapies with amikacin had a lower percentage of isolates resistant to one or to both drugs compared with the respective monotherapy. The highest OR for ICU admission was observed when both drugs of the combination of meropenem–amikacin were resistant. Mortality was significantly associated with relapse or the progression of the underlying malignancy, and resistance to both drugs of the combinations of cefepime–amikacin or meropenem–amikacin. Methods: This study was based on data collected for a large multinational study, in which the susceptibility of Gram-negative bloodstream isolates was categorized following either EUCAST or CLSI according to local laboratory standards. An escalation antibiogram was generated for each selected drug. For resistant bacteria, the conditional susceptibility probability on resistance was calculated. Conclusions: In pediatric cancer patients with Gram-negative BSIs, the proportion of the resistant organism correlates with ICU admission or death, which may be reduced by combination therapy. In patients with suspected or confirmed Gram-negative BSIs that are not-improving or deteriorating under monotherapy, escalation to meropenem may represent the best option. Amikacin should be preferred when combination therapy is considered with ciprofloxacin as an alternative in the case of impaired renal function.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".