Are Sink Drainage Systems a Reservoir for Hospital-Acquired Gammaproteobacteria Colonization and Infection? A Systematic Review
Bibliographic record
Abstract
Increasing rates of antimicrobial-resistant organisms have focused attention on sink drainage systems as reservoirs for hospital-acquired Gammaproteobacteria colonization and infection. We aimed to assess the quality of evidence for transmission from this reservoir. We searched 8 databases and identified 52 studies implicating sink drainage systems in acute care hospitals as a reservoir for Gammaproteobacterial colonization/infection. We used a causality tool to summarize the quality of evidence. Included studies provided evidence of co-occurrence of contaminated sink drainage systems and colonization/infection, temporal sequencing compatible with sink drainage reservoirs, some steps in potential causal pathways, and relatedness between bacteria from sink drainage systems and patients. Some studies provided convincing evidence of reduced risk of organism acquisition following interventions. No single study provided convincing evidence across all causality domains, and the attributable fraction of infections related to sink drainage systems remains unknown. These results may help to guide conduct and reporting in future studies.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".