Antimicrobial Use for Symptom Management in Patients Receiving Hospice and Palliative Care: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Patients receiving hospice or palliative care often receive antimicrobial therapy; however the effectiveness of antimicrobial therapy for symptom management in these patients is unknown. OBJECTIVE: The study's objective was to systematically review and summarize existing data on the prevalence and effectiveness of antimicrobial therapy to improve symptom burden among hospice or palliative care patients. DESIGN: Systematic review of articles on microbial use in hospice and palliative care patients published from January 1, 2001 through June 30, 2011. MEASUREMENTS: We extracted data on patients' underlying chronic condition and health care setting, study design, prevalence of antimicrobial use, whether symptom response following antimicrobial use was measured, and the method for measuring symptom response. RESULTS: Eleven studies met our inclusion criteria in which prevalence of antimicrobial use ranged from 4% to 84%. Eight studies measured symptom response following antimicrobial therapy. Methods of symptom assessment were highly variable and ranged from clinical assessment from patients' charts to the Edmonton Symptom Assessment Scale. Symptom improvement varied by indication, and patients with urinary tract infections (two studies) appeared to experience the greatest improvement following antimicrobial therapy (range 67% to 92%). CONCLUSION: Limited data are available on the use of antimicrobial therapy for symptom management among patients receiving palliative or hospice care. Future studies should systematically measure symptom response and control for important confounders to provide useful data to guide antimicrobial use in this population.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".