Holy water not so holy: Potential source of Elizabethkingia pneumonia and bacteremia in an immunocompromised host
Bibliographic record
Abstract
Elizabethkingia species are Gram-negative, glucose-non-fermenting bacilli predominantly found in soil and water, with Elizabethkingia anophelis increasingly recognized as a human pathogen. E. anophelis has also been reported in hospital outbreaks, suggesting the potential role of contaminated institutional water sources. Conventional microbiological methods often lead to misidentifying this pathogen for other members of the genus Elizabethkingia , suggesting a role for molecular methods for identification. We report a 67-year-old female who developed multiorgan failure requiring intensive care unit admission and mechanical ventilation while being treated with chemotherapy for Burkitt lymphoma. She developed pneumonia with Gram-negative bacilli isolated from her endotracheal aspirate culture, later identified as E. anophelis . She later developed bacteremia due to the same pathogen, which was confirmed by MALDI-TOF and whole genome sequencing. Waterborne transmission via holy water administration was postulated to be potential source of infection. Our case report highlights that E. anophelis may cause significant infection and should not be disregarded as contaminant, especially in immunosuppressed individuals. As a waterborne pathogen that may be brought into hospital environments, emphasis on educating family members, close nursing monitoring, and reporting of suspected, unsupervised manipulation of medical equipment should be undertaken to prevent contamination by this organism from outside sources.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".