Effectiveness of Subcutaneous Administration of Antibiotics to Control Infections in Elder Palliative Patients: A Systematic Review
Bibliographic record
Abstract
Background: Infections are common in patients with advanced illnesses for whom the intravenous or oral route is not possible. The subcutaneous administration of antibiotics is a promising alternative, but there is not enough theoretical support for its use. This study aims to explore the effectiveness and safety of subcutaneous antibiotic therapy in the context of palliative care in elderly patients. Methods: A systematic review was conducted using PubMed and Embase, without time or language limits. Seven articles were selected on the effectiveness of subcutaneous antibiotic therapy in adult patients with chronic progressive diseases. The quality of the articles was assessed with the Newcastle Ottawa Scale and relevant data was extracted using a selection capture file. Results: Seven quasi-experimental studies evaluated 865 elderly patients with advanced diseases, comorbidities, and infections (ie, urinary tract, respiratory system, and bone joint) who received subcutaneous antibiotic therapy (ie, Ceftriaxone, Ertapenem, and Teicoplanin). The pooled success rate of subcutaneous antibiotics for the 7 studies was 71%, the therapy failure rate was 22%, its withdrawal mean was 8%, and the mean mortality rate was 7%. The studies were of low quality and were heterogeneous in the types of infections, types of antibiotics, time of follow-up, and outcomes assessed. Conclusions: Pilot studies have found a limited number of antibiotics that can be safely used to treat specific infections. Nevertheless, the data isn´t robust enough to recommend their use.
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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 | 0.008 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".