Bibliographic record
Abstract
PURPOSE OF REVIEW: Asymptomatic bacteriuria is a common finding. Inappropriate antimicrobial treatment of asymptomatic bacteriuria has been identified as a major issue for antimicrobial stewardship programs. This review summarizes and evaluates recent studies which extend our knowledge of the occurrence, management, and outcomes of bacteriuria. RECENT FINDINGS: The reported prevalence of bacteriuria is higher in some developing countries than generally reported for developed countries, but reasons for this remain unclear. Clinical studies of young women, renal transplant patients, and patients undergoing minor nontraumatic urologic procedures confirm that treatment of asymptomatic bacteriuria for these populations is not beneficial, and may be harmful. There is also no benefit for treatment of asymptomatic bacteriuria prior to orthopedic surgery to decrease postoperative surgical site infection. Studies continue to report substantial inappropriate antimicrobial use for treatment of asymptomatic bacteriuria. SUMMARY: Recent publications confirm that asymptomatic bacteriuria is benign in most patients. Management strategies for pregnant women with recurrent bacteriuria require further clarification. There is a continuing problem with inappropriate treatment of asymptomatic bacteriuria, and sustainable strategies to optimize antimicrobial use for this problem are needed.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".