Near Patient Testing for C Difficile Infections Results in Drop in Patient Isolation

Article

The results also show a decrease in antibiotic use, hospital length of stay, and overall cost to the patient.

Near Patient Testing for C Difficile Infections Results in Drop in Patient Isolation

Cody P. Doolan

Implementing a rapid near patient testing program around suspected clostridiodes difficile infections (CDI) cases in hospital settings could result in a number of positive patient outcomes.

A team, led by Cody P. Doolan, Department of Microbiology, Immunology, and Infectious Diseases, University of Calgary, examined whether rapid near patient testing reduced patient isolation time, hospital lengths of stay, antibiotic usage, and cost when there are suspected cases of CDI.

Standard of Care

Generally, when there are suspected cases of CDI in hospital settings, the reaction is patient isolation, laboratory testing, infection control, and presumptive treatment.

In the two-period pragmatic cluster randomized crossover trial, the investigators examined patients at 39 wards and divided them into 2 separate arms.

They sought primary outcomes of the effect of near patient testing on patient isolation time. To do this they used mixed effect generalized linear regression models.

The investigators also sought various secondary outcomes, including hospital length of stay and antibiotic therapy based on a negative binomial regression model.

Finally, they conducted natural experiment, intention-to-treat, and per protocol analyses.

The patient population included 656 patients who received NPT for CDI and 1667 patients in the standard of care cohort.

The Results

The results show a significant decrease in patient isolation time for the NPT group compared to the others (NE 9.4 hours; P <0.01, ITT, 2.3; P <0.05; PP, 6.7; P <0.1), as well as a significant reduction in hospital length of stay for short stays (NE, 47.4%; P <0.01; ITT, 18.4%; P <0.01; ITT, 34.2%; P <0.01).

For every additional hour of delay for a negative result there was an increase in metronidazole use (24 DDD per 1000 patients; P <0.05) and non-CDI treating antibiotics by 70.13 mg (P <0.01).

In the cost analysis, the investigators found NPT testing saved $25.48 per patient including test cost and patient isolation.

“The cluster randomized cross-over trial demonstrated that implementation of CDI NPT can contribute to significant reductions in isolation time, hospital length of stay, antibiotic usage, and health care cost,” the authors wrote.

CDI During COVID-19

Recently, investigators found prevalence of CDI in patients hospitalized with COVID-19 infections was relatively low during the pandemic.

In a study published in January, a team, led by Aalam Sohal, MBBS, Liver Institute Northwest, assessed the prevalence and impact of CDI in a population of hospitalized patients with COVID-19 infections in the US.

However, the study of 1.5 million patients show patients with CDI and COVID-19 were at an increased risk of negative outcomes, including mortality.

Overall, there was a higher incidence of mortality in the CDI group compared to patients without COVID-19 (23.25% vs. 13.33%; <0.001).

Patients with COVID-19 and CDI had a higher incidence of sepsis (7.69% vs. 5%, <0.001), shock (23.59% vs. 8.59%, <0.001), ICU admission (25.54% vs. 12.28%, <0.001), and AKI (47.71% vs. 28.52%, <0.001).

The investigators found patients with CDII had a statistically significant higher risk of mortality (aOR, 1.47; P <0.001) compared to those without CDI after conducting a multivariable analysis.

There was also a statistically significant higher risk of sepsis (aOR, 1.47; P <0.001), shock (aOR, 2.7; <0.001), AKI (aOR, 1.5; <0.001), and ICU admission (aOR, 2.16; <0.001).

References

Doolan CP, Sahragard B, Leal J, et al. clostridioides difficile near patient testing versus centralized testing: A pragmatic cluster randomized cross-over trial. Clinical Infectious Diseases. 2023. doi:10.1093/cid/ciad046

Related Videos
Nanette B. Silverberg, MD: Uncovering Molluscum Epidemiology
Vipul Jairath, MBChB, DPhil | Credit: LinkedIn
Marla Dubinsky, MD | Credit: LinkedIn
Marla Dubinsky, MD | Credit: LinkedIn
Marla Dubinsky, MD | Credit: LinkedIn
Marla Dubinsky, MD | Credit: LinkedIn
Katie Falloon, MD
© 2024 MJH Life Sciences

All rights reserved.