Bibliographic record
Abstract
PURPOSE OF REVIEW: Infections and antimicrobial use are common in residents of long-term care facilities. This review discusses recent articles that address infection prevention and control and antimicrobial stewardship in these facilities. RECENT FINDINGS: National surveys confirm the continuing high prevalence of infections in residents of long-term care facilities, with the greatest risk for patients with the highest acuity and greatest functional disability. Long-term acute care facilities are a unique environment where residents are characterized by high levels of indwelling device use and antimicrobial-resistant organisms. The major determinant of antimicrobial resistance in long-term care facilities is antimicrobial use. The Centers for Disease Control (CDC) has proposed revised evidence-based definitions for surveillance of infections on the basis of the original McGeer criteria. Consensus national performance standards for infection prevention and antimicrobial stewardship programs in long-term care facilities have been developed in a European initiative. Evidence to support the efficacy of infection control programs is limited. Antimicrobial stewardship programs may, however, be effective in reducing inappropriate antimicrobial use. SUMMARY: The extent to which endemic infections or antimicrobial resistance in long-term care facilities can be prevented remains unclear. Efforts to limit infections in these facilities should focus on outbreak prevention and standard procedures for environmental cleaning, food preparation, and hand hygiene, together with optimal resident medical care. Antimicrobial stewardship programs should be implemented.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".