Relationship Between Adenosine Triphosphate and Colony Counts for Monitoring of Surface Cleanliness of Intensive Care Rooms
Bibliographic record
Abstract
Background. Ensuring quality of and compliance with surface cleaning protocols in the intensive care unit (ICU) is important for controlling the transmission of pathogens. However, there is no standard method for measuring surface contamination. A prospective study was conducted in 4 countries to measure cleanliness of high-touch surfaces in ICU patient rooms using adenosine triphosphate (ATP), colony counts, reflective surface markers (RSM) and visual inspection, both before (Phase 1) and after educational intervention (IE) of cleaning protocols (Phase 2). Results focusing on the performance of ATP and colony counts as quality indicators are reported. Methods. Standard cleaning procedures for ICU patient rooms were recorded for each of 4 sites in Brazil, Canada, Netherlands, and the United States. Monitoring of surface cleanliness was performed on 50 ICU rooms at each site using 3M CleanTrace ATP Surface Test (reported as relative light units [RLUs]) and microbial culture (reported as colony-forming units per square centimeter [CFUs/cm2]), and a reflective surface marker. The cleanliness pass threshold for ATP sampling was ≤250 RLUs and for bioburden was 2.5 CFU/cm2. Results. The percentage of tested surfaces passing ATP and bioburden thresholds prior to discharge cleaning in Phase 1, by country, ranged from 45.2% and 64.8%, respectively, to 74.8% and 88.4%, respectively. Post-cleaning pass rates were generally higher based on bioburden measurement (range: 90.8%–98.4%) than for ATP measurement (range: 24.7%–91.6%). After retraining interventions in Phase 2, the pass rates for ATP and bioburden measurements generally increased. Using the cutoffs of <250 RLU and >2.5 CFU/cm2, the discordancy rate between the measurements was 61.5%. Lowering the pass thresholds for both measures improved concordance. Conclusion. Re-training and real-time feedback of ATP results had a positive effect on improving ICU room cleanliness based on measures of ATP and bioburden. The clean cutoff threshold for bioburden (2.5 CFU/cm2) is likely too high as few tested surfaces were above the threshold prior to cleaning. Lowering the cutoffs for CFU and/or RLU are shown to improve concordance between ATP and bioburden pass/fail rates. Disclosures. M. Alfa, 3M: Consultant, Consulting fee; I. Boszczowski, 3M: Consultant, Consulting fee; J. Hopman, 3M: Consultant, Consulting fee
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".