Why are antibiotics prescribed for asymptomatic bacteriuria in institutionalized elderly people? A qualitative study of physicians' and nurses' perceptions.
Bibliographic record
Abstract
BACKGROUND: Antibiotic therapy for asymptomatic bacteriuria in institutionalized elderly people has not been shown to be of benefit and may in fact be harmful; however, antibiotics are still frequently used to treat asymptomatic bacteriuria in this population. The aim of this study was to explore the perceptions, attitudes and opinions of physicians and nurses involved in the process of prescribing antibiotics for asymptomatic bacteriuria in institutionalized elderly people. METHODS: Focus groups were conducted among physicians and nurses who provide care to residents of long-term care facilities in Hamilton, Ont. A total of 22 physicians and 16 nurses participated. The focus group discussions were tape-recorded, and the transcripts of each session were analysed for issues and themes emerging from the text. Content analysis using an open analytic approach was used to explore and understand the experience of the focus group participants. The data from the text were then coded according to the relevant and emergent themes and issues. RESULTS: We observed that the ordering of urine cultures and the prescribing of antibiotics for residents with asymptomatic bacteriuria were influenced by a wide range of nonspecific symptoms or signs in residents. The physicians felt that the presence of these signs justified a decision to order antibiotics. Nurses played a central role in both the ordering of urine cultures and the decision to prescribe antibiotics through their awareness of changes in residents' status and communication of this to physicians. Education about asymptomatic bacteriuria was viewed as an important priority for both physicians and nurses. INTERPRETATION: The presence of non-urinary symptoms and signs is an important factor in the prescription of antibiotics for asymptomatic bacteriuria in institutionalized elderly people. However, no evidence exists to support this reason for antibiotic treatment. Health care providers at long-term care facilities need more education about antibiotic use and asymptomatic bacteriuria.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".