Antimicrobial stewardship in long term care facilities: what is effective?
Bibliographic record
Abstract
Intense antimicrobial use in long term care facilities promotes the emergence and persistence of antimicrobial resistant organisms and leads to adverse effects such as C. difficile colitis. Guidelines recommend development of antimicrobial stewardship programs for these facilities to promote optimal antimicrobial use. However, the effectiveness of these programs or the contribution of any specific program component is not known. For this review, publications describing evaluation of antimicrobial stewardship programs for long term care facilities were identified through a systematic literature search. Interventions included education, guidelines development, feedback to practitioners, and infectious disease consultation. The studies reviewed varied in types of facilities, interventions used, implementation, and evaluation. Comprehensive programs addressing all infections were reported to have improved antimicrobial use for at least some outcomes. Targeted programs for treatment of pneumonia were minimally effective, and only for indicators of uncertain relevance for stewardship. Programs focusing on specific aspects of treatment of urinary infection - limiting treatment of asymptomatic bacteriuria or prophylaxis of urinary infection - were reported to be effective. There were no reports of cost-effectiveness, and the sustainability of most of the programs is unclear. There is a need for further evaluation to characterize effective antimicrobial stewardship for long term care facilities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.024 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".