3 results
Effectiveness of Bio-K+ for the prevention of Clostridioides difficile infection: Stepped-wedge cluster-randomized controlled trial
- Jenine Leal, Ye Shen, Peter Faris, Bruce Dalton, Deana Sabuda, Wrechelle Ocampo, Lauren Bresee, Blanda Chow, Jared R. Fletcher, Elizabeth Henderson, Jaime Kaufman, Joseph Kim, Maitreyi Raman, Scott Kraft, Nicole C. Lamont, Oscar Larios, Bayan Missaghi, Jayna Holroyd-Leduc, Thomas Louie, John Conly
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 45 / Issue 4 / April 2024
- Published online by Cambridge University Press:
- 11 December 2023, pp. 443-451
- Print publication:
- April 2024
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Objective:
To evaluate the impact of administering probiotics to prevent Clostridioides difficile infection (CDI) among patients receiving therapeutic antibiotics.
Design:Stepped-wedge cluster-randomized trial between September 1, 2016, and August 31, 2019.
Setting:This study was conducted in 4 acute-care hospitals across an integrated health region.
Patients:Hospitalized patients, aged ≥55 years.
Methods:Patients were given 2 probiotic capsules daily (Bio-K+, Laval, Quebec, Canada), containing 50 billion colony-forming units of Lactobacillus acidophilus CL1285, L. casei LBC80R, and L. rhamnosus CLR2. We measured hospital-acquired CDI (HA-CDI) and the number of positive C. difficile tests per 10,000 patient days as well as adherence to administration of Bio-K+ within 48 and 72 hours of antibiotic administration. Mixed-effects generalized linear models, adjusted for influenza admissions and facility characteristics, were used to evaluate the impact of the intervention on outcomes.
Results:Overall adherence of Bio-K+ administration ranged from 76.9% to 84.6% when stratified by facility and periods. Rates of adherence to administration within 48 and 72 hours of antibiotic treatment were 60.2% –71.4% and 66.7%–75.8%, respectively. In the adjusted analysis, there was no change in HA-CDI (incidence rate ratio [IRR], 0.92; 95% confidence interval [CI], 0.68–1.23) or C. difficile positivity rate (IRR, 1.05; 95% CI, 0.89–1.24). Discharged patients may not have received a complete course of Bio-K+. Our hospitals had a low baseline incidence of HA-CDI. Patients who did not receive Bio-K+ may have differential risks of acquiring CDI, introducing selection bias.
Conclusions:Hospitals considering probiotics as a primary prevention strategy should consider the baseline incidence of HA-CDI in their population and timing of probiotics relative to the start of antimicrobial administration.
Impact of Seasonality and Influenza Rates on Interventions to Reduce Hospital-Acquired Clostridioides difficile Rates
- Jenine Leal, Peter Faris, Ye Shen, Lauren Bresee, Kathryn Bush, Blanda Chow, Bruce Dalton, Jared Fletcher, Sara Hartman, Jaime Kaufman, Joseph Kim, Maitreyi Kothandaraman, Scott Kraft, Nicole Lamont, Oscar Larios, Braden Manns, Bayan Missaghi, Wrechelle Ocampo, Paule Poulin, Deana Sabuda, Jayna Holroyd-Leduc, Thomas Louie, John Conly
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 41 / Issue S1 / October 2020
- Published online by Cambridge University Press:
- 02 November 2020, pp. s265-s266
- Print publication:
- October 2020
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Background: Hospital-acquired Clostridioides difficile infection (HA-CDI) rates are highly variable over time, posing problems for research assessing interventions that might improve rates. By understanding seasonality in HA-CDI rates and the impacts that other factors such as influenza admissions might have on these rates, we can account for them when establishing the relationship between interventions and infection rates. We assessed whether there were seasonal trends in HA-CDI and whether they could be accounted for by influenza rates. Methods: We assessed HA-CDI rates per 10,000 patient days, and the rate of hospitalized patients with influenza per 1,000 admissions in 4 acute-care facilities (n = 2,490 beds) in Calgary, Alberta, from January 2016 to December 2018. We used 4 statistical approaches in R (version 3.5.1 software): (1) autoregressive integrated moving average (ARIMA) to assess dependencies and trends in each of the monthly HA-CDI and influenza series; (2) cross correlation to assess dependencies between the HA-CDI and influenza series lagged over time; (3) Poisson harmonic regression models (with sine and cosine components) to assess the seasonality of the rates; and (4) Poisson regression to determine whether influenza rates accounted for seasonality in the HA-CDI rates. Results: Conventional ARIMA approaches did not detect seasonality in the HA-CDI rates, but we found strong seasonality in the influenza rates. A cross-correlation analysis revealed evidence of correlation between the series at a lag of zero (R = 0.41; 95% CI, 0.10–0.65) and provided an indication of a seasonal relationship between the series (Fig. 1). Poisson regression suggested that influenza rates predicted CDI rates (P < .01). Using harmonic regression, there was evidence of seasonality in HA-CDI rates (2 [2 df] = 6.62; P < .05) and influenza rates (2 [2 df] = 1,796.6; P < .001). In a Poisson model of HA-CDI rates with both the harmonic components and influenza admission rates, the harmonic components were no longer predictive of HA-CDI rates. Conclusions: Harmonic regression provided a sensitive means of identifying seasonality in HA-CDI rates, but the seasonality effect was accounted for by influenza admission rates. The relationship between HA-CDI and influenza rates is likely mediated by antibiotic prescriptions, which needs to be assessed. To improve precision and reduce bias, research on interventions to reduce HA-CDI rates should assess historic seasonality in HA-CDI rates and should account for influenza admissions.
Funding: None
Disclosures: None
Implementation Strategies of a Quality Improvement Initiative for Hospital-Acquired Clostridioides difficile Infection Prevention
- Nicole Lamont, Lauren Bresee, Kathryn Bush, Blanda Chow, Bruce Dalton, Cody Doolan, Peter Faris, Jared Fletcher, Sara Hartman, Jaime Kaufman, Maida Khan, Joseph Kim, Maitreyi Kothandaraman, Scott Kraft, Oscar Larios, Jenine Leal, Braden Manns, Bayan Missaghi, Wrechelle Ocampo, Dylan Pillai, Paule Poulin, Deana Sabuda, Ye Shen, Thomas Louie, Jayna Holroyd-Leduc, John Conly
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 41 / Issue S1 / October 2020
- Published online by Cambridge University Press:
- 02 November 2020, pp. s279-s280
- Print publication:
- October 2020
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Background:Clostridioides difficile infection (CDI) is the most common cause of infectious diarrhea in hospitalized patients. Probiotics have been studied as a measure to prevent CDI. Timely probiotic administration to at-risk patients receiving systemic antimicrobials presents significant challenges. We sought to determine optimal implementation methods to administer probiotics to all adult inpatients aged 55 years receiving a course of systemic antimicrobials across an entire health region. Methods: Using a randomized stepped-wedge design across 4 acute-care hospitals (n = 2,490 beds), the probiotic Bio-K+ was prescribed daily to patients receiving systemic antimicrobials and was continued for 5 days after antimicrobial discontinuation. Focus groups and interviews were conducted to identify barriers, and the implementation strategy was adapted to address the key identified barriers. The implementation strategy included clinical decision support involving a linked flag on antibiotic ordering and a 1-click order entry within the electronic medical record (EMR), provider and patient education (written/videos/in-person), and local site champions. Protocol adherence was measured by tracking the number of patients on therapeutic antimicrobials that received BioK+ based on the bedside nursing EMR medication administration records. Adherence rates were sorted by hospital and unit in 48- and 72-hour intervals with recording of percentile distribution of time (days) to receipt of the first antimicrobial. Results: In total, 340 education sessions with >1,800 key stakeholders occurred before and during implementation across the 4 involved hospitals. The overall adherence of probiotic ordering for wards with antimicrobial orders was 78% and 80% at 48 and 72 hours, respectively over 72 patient months. Individual hospital adherence rates varied between 77% and 80% at 48 hours and between 79% and 83% at 72 hours. Of 246,144 scheduled probiotic orders, 94% were administered at the bedside within a median of 0.61 days (75th percentile, 0.88), 0.47 days (75th percentile, 0.86), 0.71 days (75th percentile, 0.92) and 0.67 days (75th percentile, 0.93), respectively, at the 4 sites after receipt of first antimicrobial. The key themes from the focus groups emphasized the usefulness of the linked flag alert for probiotics on antibiotic ordering, the ease of the EMR 1-click order entry, and the importance of the education sessions. Conclusions: Electronic clinical decision support, education, and local champion support achieved a high implementation rate consistent across all sites. Use of a 1-click order entry in the EMR was considered a key component of the success of the implementation and should be considered for any implementation strategy for a stewardship initiative. Achieving high prescribing adherence allows more precision in evaluating the effectiveness of the probiotic strategy.
Funding: Partnerships for Research and Innovation in the Health System, Alberta Innovates/Health Solutions Funding: Award
Disclosures: None