Person-to-person transmission of microbes in a nursing home serving patients in a persistent vegetative state
Bibliographic record
Abstract
Background: A probable outbreak of respiratory disease in a nursing home serving exclusively patients in a persistent vegetative state (PVS) resulted in hospitalization of eight patients. Methods: Microbes from all PVS patients’ respiratory tracks and environments were surveyed by microbiological methods. Major pathogenic microbes were analyzed by pulsed-field gel electrophoresis (PFGE). Results: 24 PVS patients were investigated. Half were colonized with at least four different pathogenic microbes in their respiratory tracts. The most prevalent microbes were Pseudomonas aeruginosa in 15 patients (62.5%), Serratia marcescens in 14 (58.3%), Citrobacter koseri in nine (37.5%), Streptococcus pneumoniae in six (25%), and Proteus mirabilis in five (20.8%). By PFGE analysis, one major pulsotype each was identified for S. marcescens (92.9%, 13/14) and S. pneumoniae (100%, 6/6), whereas diverse pulsotypes were identified for P. aeruginosa, C. koseri, and P. mirabilis. Both major pulsotypes for S. marcescens and S. pneumoniae were also found in strains from patients outside the nursing home. No environmental reservoir was found for prevalent microbes. Conclusions: Clonal transmission of S. marcescens and S. pneumoniae among PVS patients in the nursing home was evident, indicating a need to enforce control measures to reduce threats to this type of facility.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".