The Role of Antibiotics in the Management of Infection-Related Symptoms in Advanced Cancer Patients
Bibliographic record
Abstract
UNLABELLED: We prospectively evaluated the effect of antibiotic treatment on infection-related symptoms in patients with advanced cancer, in addition to assessing infection characteristics. METHODS: A questionnaire was completed for enrolled patients using a personal digital assistant. Pre-antibiotic and post-antibiotic treatment Edmonton Symptom Assessment Scale (ESAS) scores were evaluated. Patient and the patient's physician identified infection-related symptoms experienced by the patient, which were documented under the "other" category on the ESAS. Pre-antibiotic and post-antibiotic scores of the patient and physician for the identified infection-related symptoms were evaluated. RESULTS: Twenty-six patients on a tertiary palliative care unit with 31 episodes of infection were included for analysis. Patients' pre- and post-antibiotic ESAS scores revealed a small improvement in all variables except anxiety. Patient assessment of symptoms related to infection showed a small improvement in all symptoms, with dsyuria being statistically significant. Physician assessment revealed a slight improvement for all the symptoms, although only cough was statistically significant. A general comparative physician assessment of patient outcome following antibiotic treatment suggested symptom improvement in 48.4% of patients. However, 50% of patients died within a week of antibiotic discontinuation. CONCLUSIONS: Antibiotic treatment appears to offer a mild improvement in infection-related symptoms. Patients reported the greatest improvement in dysuria, and physicians, in cough. Despite this symptomatic improvement, one quarter of the patients died within one week of antibiotic administration. Further comparative studies to evaluate symptomatic benefit, patient burden, and cost/benefit of antibiotic therapy in the treatment of infections in advanced cancer patients are required.
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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 | 0.000 |
| 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".