Faculty Bibliography

New York City quickly became an epicentre of the COVID-19 pandemic. An ability to triage patients was needed due to a sudden and massive increase in patients during the COVID-19 pandemic as healthcare providers incurred an exponential increase in workload,which created a strain on the staff and limited resources. Further, methods to better understand and characterise the predictors of morbidity and mortality was needed. METHODS: We developed a prediction model to predict patients at risk for mortality using only laboratory, vital and demographic information readily available in the electronic health record on more than 3395 hospital admissions with COVID-19. Multiple methods were applied, and final model was selected based on performance. A variable importance algorithm was used for interpretability, and understanding of performance and predictors was applied to the best model. We built a model with an area under the receiver operating characteristic curve of 83-97 to identify predictors and patients with high risk of mortality due to COVID-19. Oximetry, respirations, blood urea nitrogen, lymphocyte per cent, calcium, troponin and neutrophil percentage were important features, and key ranges were identified that contributed to a 50% increase in patients' mortality prediction score. With an increasing negative predictive value starting 0.90 after the second day of admission suggests we might be able to more confidently identify likely survivors DISCUSSION: This study serves as a use case of a machine learning methods with visualisations to aide clinicians with a better understanding of the model and predictors of mortality. CONCLUSION: As we continue to understand COVID-19, computer assisted algorithms might be able to improve the care of patients.

INTRODUCTION/BACKGROUND:It is common among microbiology laboratories to blind the Clostridioides difficile (C. difficile) BioFire FilmArray GI Panel result in fear of overdiagnosis. METHODS:We examined the rate of missed community-onset C. difficile infection (CDI) diagnosis and associated outcomes. Adult patients with FilmArray GI Panel positive for C. difficile on hospital admission who lacked dedicated C. difficile testing were included. RESULTS:Among 144 adults with a FilmArray Panel positive for C. difficile, 18 did not have concurrent dedicated C. difficile testing. Eight patients were categorized as possible, 5 as probable and 4 as definite cases of missed CDI diagnosis. We observed associated delays in initiation of appropriate therapy, intensive care unit admissions, hospital readmissions, colorectal surgery and death/discharge to hospice. Five out of 17 lacked risk factors for CDI. CONCLUSION/CONCLUSIONS:The practice of concealing C. difficile FilmArray GI Panel results needs to be reconsidered in patients presenting with community-onset colitis.

BACKGROUND:Standard urine sampling and testing techniques do not mitigate against detection of colonization, resulting in false positive catheter-associated urinary tract infections (CAUTI). We aim to evaluate if a novel protocol for urine sampling and testing reduces rates of CAUTI. METHODS:A pre-intervention and post-intervention study with a contemporaneous control group was conducted at two campuses (test and control) of the same academic medical center. The test campus implemented a protocol requiring urinary catheter removal prior to urine sampling from a new catheter or sterile straight catheterization, along with urine bacteria and pyuria screening prior to culture. Primary outcomes were test campus CAUTI rates compared between each 9-month pre- and post-intervention epoch. Secondary outcomes included the percent reductions in CAUTI rates compared between the test campus and a propensity-score matched cohort at the control campus. RESULTS:  A total of 7,991 patients from the test campus were included in the primary analysis, and 4,264 were included in the propensity-score matched secondary analysis. In primary analysis, CAUTI/1000-patients was reduced by 77% (6.6 to 1.5), CAUTI/1000-catheter days by 63% (5.9 to 2.2) and urinary catheter days/patient by 37% (1.1 to 0.69, all P≤0.001). In propensity score-matched analysis, CAUTI/1000-patients was reduced by 82% at the test campus versus 57% at the control campus, CAUTI/1000 catheter-days declined by 68% versus 57% and catheter-days/patient decreased by 44% versus 1% (all P<0.001). CONCLUSIONS: Protocolized urine sampling and testing aimed at minimizing contamination by colonization was associated with significantly reduced CAUTI infection rates and urinary catheter days.

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.

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.