Prospective 3-Year Surveillance for Nosocomial and Environmental<i>Legionella pneumophila</i>: Implications for Infection Control
Bibliographic record
Abstract
OBJECTIVES: To perform a 3-year, prospective surveillance program for legionnaires disease (LD) in a large university hospital in Rome, and to assess the usefulness of the hospital water monitoring program in predicting the risk of nosocomial LD. METHODS: Samples from patients with new cases of nosocomial pneumonia were sent for legionella laboratory investigations. Meanwhile, water samples for bacteriological analysis were collected every 6 months from high- and medium-risk hospital wards (10 in total). Legionella pneumophila isolates collected were serotyped and analyzed by pulsed-field gel electrophoresis. RESULTS: From June 2001 through May 2004, the pneumonia surveillance identified one case of nosocomial LD among 43 cases of nosocomial pneumonia (2.3%). Environmental investigations detected L. pneumophila in 12 (18.7%) of the 64 water samples, of which 50% belonged to serogroup 1. The L. pneumophila count and the percentage of positive locations never exceeded 10(2) colony-forming units/L and 20%, respectively, except when the LD nosocomial case occurred (positive water samples, 40%; L. pneumophila count, <10(2) colony-forming units/L). Genotyping showed 3 prevalent clones of L. pneumophila in the water distribution network, of which one persisted over the 3 years. One clone contained 3 different L. pneumophila serogroups (2, 4, and 6). CONCLUSIONS: The low incidence of nosocomial cases of LD appears to be associated with a low percentage (<20%) of positive water samples per semester and with a low contamination level (<10(2) colony-forming units/L). An infection control system for nosocomial LD should, therefore, be based on both environmental and clinical surveillance, together with the appropriate maintenance of the hospital water distribution system.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".