Epidemiology of intensive care unit-acquired urinary tract infections
Bibliographic record
Abstract
PURPOSE OF REVIEW: The development of urinary tract infections in critically ill adult patients is associated with considerable morbidity, prolonged hospitalization, and greater healthcare expenditures. We review the occurrence, microbiology, risk factors for acquisition, and outcomes associated with intensive care unit-acquired urinary tract infections. RECENT FINDINGS: Reports from several countries indicate that nosocomial urinary tract infections frequently complicate the course of patients admitted to intensive care units. Virtually all patients who develop an intensive care unit-acquired urinary tract infection have indwelling urinary catheters; other factors associated with the development of these infections include increased duration of urinary catheterization, female sex, intensive care unit length of stay, and preceding systemic antimicrobial therapy. The most frequent pathogens include Escherichia coli, Pseudomonas aeruginosa, enterococci, and Candida albicans; both the species distribution and rates of resistance vary considerably among institutions and regions. Secondary bloodstream infections are uncommon. Although acquisition of an intensive care unit-acquired urinary tract infection has been associated with a prolongation of intensive care unit length of stay, higher cost, and a higher crude case fatality rate, they do not appear to independently increase the risk for death. SUMMARY: Urinary tract infection is a common complication of critical illness that is associated with increased patient morbidity but not mortality. There is a relative paucity of research on nosocomial urinary tract infection specifically acquired in the intensive care unit and further studies are needed to better define the epidemiology and management of these infections.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".