Intensive care unit-acquired urinary tract infections in a regional critical care system
Bibliographic record
Abstract
INTRODUCTION: Few studies have evaluated urinary tract infections (UTIs) specifically acquired within intensive care units (ICUs), and the effect of such infections on patient outcome is unclear. The objectives of this study were to describe the occurrence, microbiology, and risk factors for acquiring UTIs in the ICU and to determine whether these infections independently increase mortality. METHODS: A surveillance cohort study was conducted among all adults admitted to multi-system and cardiovascular surgery ICUs in the Calgary Health Region (CHR, population about 1 million) between 1 January 2000 and 31 December 2002. RESULTS: During the 3 years, 4465 patients were admitted 4915 times to a CHR ICU for 48 hours or more. A total of 356 ICU-acquired UTIs (defined as at least 105 colony-forming units/ml of one or two organisms 48 hours or more after ICU admission) occurred among 290 (6.5%) patients, yielding an overall incidence density of ICU-acquired UTIs of 9.6 per 1000 ICU days. Four bacteremic/fungemic ICU-acquired UTIs occurred (0.1 per 1000 ICU days). Development of an ICU-acquired UTI was more common in women (relative risk [RR] 1.58; 95% confidence interval [CI] 1.43-1.75; P < 0.0001) and in medical (9%) compared with non-cardiac surgical (6%), and cardiac surgical patients (2%). The most common organisms isolated were Escherichia coli (23%), Candida albicans (20%), and Enterococcus species (15%). Antibiotic-resistant organisms were identified among 14% isolates. Although development of an ICU-acquired UTI was associated with significantly higher crude in-hospital mortality (86/290 [30%] vs. 862/4167 [21%]; RR = 1.43; 95% CI 1.19-1.73; P < 0.001); an ICU-acquired UTI was not an independent predictor for death. CONCLUSIONS: Development of an ICU-acquired UTI is common in critically ill patients. Although a marker of increased morbidity associated with critical illness, it is not a significant attributable cause of mortality.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".