Faculty Bibliography

OBJECTIVE:The data regarding the effectiveness of chemical prophylaxis against recurrent C. difficile infection (CDI) remain conflicting. DESIGN/METHODS:Retrospective cohort study on the effectiveness of oral vancomycin for prevention of recurrent CDI. SETTING/METHODS:Two academic centers in New York. METHODS:Two participating hospitals implemented an automated alert recommending oral vancomycin 125 mg twice daily in patients with CDI history scheduled to receive systemic antimicrobials. Measured outcomes included breakthrough and recurrent CDI rates, defined as CDI during and 1 month after initiation of prophylaxis, respectively. A self-controlled, before-and-after study design was employed to examine the effect of vancomycin prophylaxis on the prevalence of vancomycin-resistant Enterococcus spp (VRE) colonization and infection. RESULTS:We included 264 patients in the analysis. Breakthrough CDI was identified in 17 patients (6.4%; 95% confidence interval [CI], 3.8%-10.1%) and recurrent in 22 patients (8.3%; 95% CI, 5.3%-12.3%). Among the 102 patients with a history of CDI within the 3 months preceding prophylaxis, 4 patients (3.9%; 95% CIs, 1.1%-9.7%) had breakthrough CDI and 9 had recurrent disease (8.8%; 95% CIs, 4.1%-16.1%). In the 3-month period following vancomycin prophylaxis, we detected a statistically significant increase in both the absolute number of VRE (χ2, 0.003) and the ratio of VRE to VSE isolates (χ2, 0.003) compared to the combined period of 1.5 months preceding and the 3-4.5 months following prophylaxis. This effect persisted 6 months following prophylaxis. CONCLUSIONS:Prophylactic vancomycin is an effective strategy to prevent CDI recurrence, but it increases the risk of VRE colonization. Thus, a careful selection of patients with high benefit-to-risk ratio is needed for the implementation of this preventive policy.

Widespread use of antibiotics has resulted in an increase in antimicrobial-resistant microorganisms. Although not all bacterial contact results in infection, patients can become asymptomatically colonized, increasing the risk of infection and pathogen transmission. Consequently, many institutions have begun active surveillance, but in non-research settings, the resulting data are often incomplete and may include non-random testing, making conventional epidemiological analysis problematic. We describe a mathematical model and inference method for in-hospital bacterial colonization and transmission of carbapenem-resistant Enterobacteriaceae that is tailored for analysis of active surveillance data with incomplete observations. The model and inference method make use of the full detailed state of the hospital unit, which takes into account the colonization status of each individual in the unit and not only the number of colonized patients at any given time. The inference method computes the exact likelihood of all possible histories consistent with partial observations (despite the exponential increase in possible states that can make likelihood calculation intractable for large hospital units), includes techniques to improve computational efficiency, is tested by computer simulation, and is applied to active surveillance data from a 13-bed rehabilitation unit in New York City. The inference method for exact likelihood calculation is applicable to other Markov models incorporating incomplete observations. The parameters that we identify are the patient-patient transmission rate, pre-existing colonization probability, and prior-to-new-patient transmission probability. Besides identifying the parameters, we predict the effects on the total prevalence (0.07 of the total colonized patient-days) of changing the parameters and estimate the increase in total prevalence attributable to patient-patient transmission (0.02) above the baseline pre-existing colonization (0.05). Simulations with a colonized versus uncolonized long-stay patient had 44% higher total prevalence, suggesting that the long-stay patient may have been a reservoir of transmission. High-priority interventions may include isolation of incoming colonized patients and repeated screening of long-stay patients.

To determine whether deep surgical site infection (dSSI) rate exhibits temporal variability, dSSI rates following 98,068 cases were analyzed. The overall dSSI rate decreased significantly between 2009 and 2018. Summer had a significantly greater rate of dSSI than winter. There was no difference in dSSI rate in July versus other months.

Background. Staphylococcus aureus infection confers high mortality. S. aureus-colonized hospitalized patients are more likely to develop invasive infection and can transmit S. aureus to other patients in the absence of symptoms. Our health system has a baseline S. aureus colonization rate of 21% (MSSA and MRSA combined). To reduce risk of invasive S. aureus infection in our patients, we implemented an inpatient S. aureus screening and decolonization program. Methods. Interventions include universal S. aureus screening and targeted decolonization for all patients on the Medicine and Pediatrics inpatient services. Adult patients are screened at admission and change in the level of care; pediatric patients are screened weekly. S. aureus screening began incrementally by unit between 2016 and 2017, and extended to transplant units in 2018. All cultures are processed in the hospital microbiology lab for identification of MRSA and MSSA. S. aureus decolonization (mupirocin ointment in nares twice daily, chlorhexidine 2% wipes below the chin daily for 5 days) began in 2017 for patients with a central venous catheter, in intensive care unit or multibedded room. Decolonization was extended to all S. aureus-colonized patients beginning in June 2018, with involvement of a dedicated clinical nurse specialist. We compared compliance with screening and decolonization and the secondary outcome of MRSA bacteremia in the 6 month period before and after the addition of the clinical nurse specialist. Results. 21.5% of screened patients were colonized with S. aureus (82.4% MSSA, 17.6% MRSA). Screening compliance improved from 39.4% of eligible patients (N = 1805) to 52.1% (N = 2024) and decolonization increased from 18.6% of colonized patients to 41.2% comparing January-June 2018 with July-December 2018. The MRSA bacteremia rate fell from 0.2/1,000 patient-days in the first half of 2018 to 0.1/1,000 patient-days in the second half of 2018. Conclusion. A system-wide program that includes S. aureus screening and decolonization of hospitalized patients found that 21% of patients had S. aureus colonization. Screening and decolonization compliance increased with the introduction of a dedicated clinical nurse specialist, and the MRSA bloodstream infection rate fell

Background. Methicillin-resistant staphylococcus aureus (MRSA) colonization of hospitalized patients is associated with higher readmission rates and increased morbidity. Depending on the mechanisms of transmission, numerous potential control interventions exist to reduce the burden of disease. However, given the preponderance of asymptomatic colonization, it is challenging to quantify the relative importance of different transmission mechanisms and assess control efficacy. By identifying clusters of transmission, whole-genome sequencing (WGS) provides an opportunity to overcome these challenges. Methods. We sought to apply cluster analysis techniques to WGS data for MRSA, in order to assess MRSA prevalence, transmissibility, the degree of transmission heterogeneity and the potential effectiveness of control. Our model builds upon previous work that showed a direct relationship between the size distribution of infection clusters, the effective reproduction number (R) and the dispersion parameter (k). To demonstrate its functionality, our model was applied to existing WGS data for MRSA isolates collected during a 12 month period in the East of England (DOI: 10.1126/scitranslmed.aak9745) Results. The effective reproduction number for the East of England data is 0.29 (95% CI: 0.24-0.36). The dispersion parameter is 0.09 (0.03-0.33) reflecting a high degree of transmission heterogeneity. This implies all transmission is caused by just 12% of the cases. Targeted control of these cases could have decreased overall burden of MRSA colonization by 29% during the time period of the study. Conclusion. The high degree of transmission heterogeneity seen in MRSA transmission suggests that the risk for infection is variable.This observation motivates the need for more detailed mechanistic modeling of hospital-based MRSA transmission that integrates patients-specific factors, movement data and genome sequencing. Such models could be used to forecast which patients are at greatest risk for either acquiring or transmitting MRSA, thereby improving targeted control