Molecular Epidemiology of Candidemia: Evidence of Clusters of Smoldering Nosocomial Infections
Bibliographic record
Abstract
BACKGROUND: Invasive fungal infections pose a serious threat to hospitalized patients worldwide. In particular, the prevalence of clusters of nosocomial infection among patients with candidemia remains unknown. The aim of this study was to investigate the molecular epidemiology of candidemia in a nationwide setting in Iceland during a 16-year period. METHODS: The genotypes of all available fungal bloodstream isolates during 1991-2006 (n = 219) were determined by polymerase chain reaction fingerprinting with use of 4 separate primers. Clusters were defined as isolation of > or =2 strains with genotypes that had > or =90% relatedness in the same hospital within a period of 90 days. RESULTS: Candida albicans represented 61.6% of isolates, followed by Candida glabrata (13.7%), Candida tropicalis (9.1%), and Candida parapsilosis (8.7%). Polymerase chain reaction fingerprinting revealed 35 clones of C. albicans, 10 clones of C. glabrata, 7 clones of C. tropicalis, 4 clones of C. parapsilosis, and 5 clones of Candida dubliniensis. Overall, 18.7%-39.9% of all infections were part of nosocomial clusters, most commonly caused by C. albicans, C. parapsilosis, and C. tropicalis. Most clusters involved 2 cases and disproportionately affected patients in adult and neonatal intensive care units (P = .045). The 7-day (16%) and 30-day (32%) case-fatality rates among cluster-associated cases did not differ statistically significantly from those for sporadic nosocomial infections. None of the clusters were identified by the hospital surveillance team. CONCLUSIONS: In an unselected patient population, as many as one-third of all cases of candidemia may be attributable to nosocomial clusters. The risk is dependent on hospital wards and patient populations; it is highest in intensive care units. Small clusters are not identified by routine hospital surveillance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".