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 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".