Infection Control & Hospital Epidemiology


919


Table 1. Estimated Environmental Sample Clostridium difficile Positivity and Quantity Based on qPCR (16S target and Toxin B target) and Enrichment Culture From Environmental Samples Collected at a Tertiary Hospital


Positivity (N, %)


16S


Sample Area Total


Surface area Small Large


Type


Bedrail Floor


Surface area and type Small bedrail Large bedrail Small floor Large floor


24 24


12 12 12 12


Room Risk of Contaminationa Low


Medium High


20 8


20


10 (41.7) 21 (87.5)


5 (41.7) 5 (41.7) 9 (75.0) 12 (100)


10 (50.0) 4 (50.0) 17 (85.0)


5 (20.8) 14 (58.3)


2 (16.7) 3 (25.0) 5 (41.7) 9 (75.0)


5 (25.0) 3 (37.5) 11 (55.0)


6 (25) 15 (62.5)


3 (25.0) 3 (25.0) 6 (50.0) 9 (75.0)


7 (35.0) 1 (12.5) 13 (65.0)


2.7 69.4


2.1 3.5


23.3 206.5


4.3 5.0


65.6


0.9 4.3


0.7 1.1 2.3 8.2


1.3 1.7 3.0


NOTE. qPCR, quantitative polymerase chain reaction. aLow, occupant had no receipt of antibiotics in prior 14 days; medium, occupant had receipt of antibiotics in prior 14 days; high, occupant had confirmed C. difficile infection.


16S qPCR and toxin B qPCR.22 All multivariable models included the same fixed effects and random intercepts. We used fixed effects for patient risk stratum, sample type, and sample surface area, and we used random intercepts corresponding to the ward, the patient room, and the sample pair. The random intercepts for patient room and sample pair accounted for the clustering inherent to the split-plot sampling design.14,15 All multilevel models were fit using Bayesian random-effects regression models in the R statistical programming language (rstanarm library) and default settings (4 chains of 1,000 warmup and 1,000 sampling draws, and default weak priors23). Furthermore, 95% confidence intervals (95% CIs) were based on the sampling draws. We conducted 2 secondary analyses. First, to assess whether


the association between sample surface area and yield was con- sistent across the surface type (bedrail vs floor), we ran an additional negative binomial multivariable model that added the interaction term between surface area and type. Second, to assess the relatedness of the 3 different laboratory techniques for mea- suring C. difficile, we measured the association between 16S qPCR spore counts and toxin B qPCR spore counts using linear regression, and between 16S qPCR spore count and enrichment culture positivity using logistic regression.


Ethics


This study was approved by the Public Health Ontario and Sunnybrook Health Sciences Center research ethics boards.


Results


Of the 48 samples collected, 31 (64.6%) were positive for C. difficile by 16S qPCR, with a geometric mean of 13.8 spores per sample; 19 (39.6%) were positive by toxin B qPCR, with a geometric mean of 1.9 spores per sample; and 21 (43.8%) were positive by enrichment culture.


Descriptive analyses


Large surface-area samples were more likely to be positive and had higher estimated spore counts compared to small surface- area samples (Table 1, Appendix 2). By 16S qPCR, 17 of 24 large surface-area samples (70.8%) were positive, while 14 of 24 small surface-area samples (58.3%) were positive. The geometric mean estimated spore count was 27.0 for large surface-area samples and 7.0 for small surface-area samples. However, large surface-area bedrail samples (0.23m2) were less likely to be positive (5 of 12, 41.7%) than small surface-area floor samples (0.10m2; 9 of 12, 75%) (Fig. 1). Overall, 21 of 24 floor samples (87.5%) were positive compared to 10 of 24 bedrail samples (41.7%), and the geometric mean estimated spore count was 69.4 for floor samples compared to 2.7 for bedrail samples.


Multivariable analyses


After multivariable adjustment, each 10-fold increase in surface area was associated with a 4.5-fold (adjusted odds ratio [aOR],


No. 48


24 24


qPCR 31 (64.6)


14 (58.3) 17 (70.8)


Toxin B qPCR


19 (39.6)


7 (29.2) 12 (50.0)


16S


Enrichment culture 21 (43.8)


9 (37.5) 12 (50)


qPCR 13.8


7.0 27.0


Toxin B qPCR 1.9


1.2 3.0


Estimated Spore Count (Geometric Mean)


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