Urinary Tract Infection Diagnosis and Response to Therapy in Long‐Term Care: A Prospective Observational Study
Bibliographic record
Abstract
BACKGROUND: The prevalence of asymptomatic bacteriuria among residents of long-term care (LTC) facilities is high, and is a source of inappropriate antibiotic prescription. OBJECTIVE: To establish symptoms and signs associated with a positive urine culture, and to determine whether antibiotic therapy is associated with functional improvement. METHODS: A total of 101 LTC patients were prospectively observed after submission of urine for culture. RESULTS: The culture positivity rate was consistent with the expected asymptomatic bacteriuria rate. Change in mental status and male sex were associated with culture positivity. Treatment decisions were not consistent with culture results. Treatment did not lead to improvement in activities of daily living scores at two days or seven days. DISCUSSION: Significant growth cannot be well predicted based on clinical variables; thus, the decision to submit urine is somewhat arbitrary. Because urine culture testing and treatment does not lead to functional improvement, restricting access to the test may be reasonable. CONCLUSION: Urine culture testing in LTC facilities does not lead to functional improvement.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".