Nosocomial Pseudomonas Species Bacteremia in Adult Patients at a Tertiary Care Centre: Risk Factors for Mortality and Multidrug Resistance
Bibliographic record
Abstract
Background. Nosocomial bacteremia due to Pseudomonas spp confers significant morbidity and mortality. Identifying those at increased risk for bacteremia with a multidrug-resistant (MDR) isolate has important treatment implications. The objective of this study was to describe the incidence, mortality, patient and microbiological characteristics of Pseudomonas spp blood stream infections at a large tertiary care hospital and to identify risk factors associated with mortality and with isolation of MDR strains. Methods. Cases of Pseudomonas spp bacteremia that occurred at a tertiary care hospital in Edmonton, Alberta between 2007 and 2014 were prospectively identified through the hospital infection prevention and control surveillance program. Charts were then retrospectively reviewed to collect further epidemiologic information. Results. A total of 102 incident cases of Pseudomonas bacteremia were identified (overall rate of 0.53 per 10 000 patient days). Sixty-six cases (64.7%) occurred in male patients. The most common sources of infection were the respiratory tract (22, 21.6%), urinary tract (20, 19.6%), gastrointestinal tract (19, 18.6%), and skin (15, 14.7%). Twenty-two cases (21.6%) had Pseudomonas aeruginosa isolates classified as MDR. All-cause 30-day mortality was 32.4%. Factors that predicted mortality were isolation of MDR Pseudomonas (OR 2.64, p < 0.05) a pulmonary source of infection (OR 4.33, p < 0.01), and inappropriate empiric antibiotic therapy (OR 10.98, p < 0.01). Inappropriate empiric therapy occurred more often when MDR strains were isolated (OR 5.4, p < 0.01). Factors that predicted isolation of a MDR strain were length of stay >28 days prior to bacteremia (OR 4.45, p < 0.01), any prior intensive care unit (ICU) stay (OR 4.37, p < 0.01), hemodialysis (OR 5.23, p < 0.01), and patient age <50 years (OR 3.16, p < 0.05). Conclusion. Our study suggests that patients bacteremic with a MDR Psuedomonas spp have a higher mortality-risk, which is likely associated with inappropriate empiric antibiotic treatment. Factors that may be helpful in identifying patients at risk of having a MDR Pseudomonas bacteremia are prolonged hospitalization, prior ICU stay, hemodialysis, and younger age. Disclosures. All authors: No reported disclosures.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".