Association Between Antibiotic Withdrawal and End-of-Life Comfort in Patients with Advanced Cancer and Suspected Infections: A Multicenter Retrospective Cohort Study
Bibliographic record
Abstract
Purpose: The role of palliative care in addressing end-of-life needs and enhancing the comfort of patients with life-threatening illnesses is crucial. This study aimed to evaluate the relationship between antibiotic withdrawal and end-of-life discomfort in patients with terminal cancer with suspected infections. Materials and Methods: A multicenter retrospective cohort study was conducted on patients aged ≥18 years with advanced cancer and life expectancy under six weeks, as determined by a Palliative Prognostic Index >4. Patients were admitted between January 2018 and December 2021, received antibiotics for suspected infections, and died during hospitalization. Patients were categorized into two cohorts based on whether antibiotic therapy was withdrawn or continued within 72-120 hours prior to death. Data were collected through medical chart review. End-of-life comfort was assessed using the validated Edmonton Comfort Assessment Form scale, with scores ≥4 indicating discomfort. Multivariate logistic regression was used to evaluate the association between antibiotic withdrawal and end-of-life discomfort. Results: A total of 187 patients were included, with a median age of 71 years; 81.8% had solid tumors, predominantly of gastrointestinal origin. Respiratory tract infections were the most common, and sepsis was present in 13% of cases. Symptoms remained mild in both groups, though pain was higher in the antibiotic withdrawal group (median score: 4 vs. 3). Multivariate analysis revealed no significant association between antibiotic withdrawal and end-of-life discomfort (odds ratio = 0.98; 95% confidence interval = 0.52-1.84). Conclusions: Symptom management for pain, nausea, and dyspnea was generally effective, though moderate pain persisted in some patients after antibiotic withdrawal. Antibiotic withdrawal was not associated with increased discomfort at the end of life. These findings support aligning antibiotic decisions with comfort-focused goals in palliative care.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".