Stephen Furmanek

Adults Hospitalized With Pneumonia in the United States: Incidence, Epidemiology, and Mortality

Background Understanding the burden of community-acquired pneumonia (CAP) is critical to allocate resources for prevention, management, and research. The objectives of this study were to define incidence, epidemiology, and mortality of adult patients hospitalized with CAP in the city of Louisville, and to estimate burden of CAP in the US adult population. Methods This was a prospective population-based cohort study of adult residents in Louisville, Kentucky, from 1 June 2014 to 31 May 2016. Consecutive hospitalized patients with CAP were enrolled at all adult hospitals in Louisville. The annual population-based CAP incidence was calculated. Geospatial epidemiology was used to define ecological associations among CAP and income level, race, and age. Mortality was evaluated during hospitalization and at 30 days, 6 months, and 1 year after hospitalization. Results During the 2-year study, from a Louisville population of 587499 adults, 186384 hospitalizations occurred. A total of 7449 unique patients hospitalized with CAP were documented. The annual age-adjusted incidence was 649 patients hospitalized with CAP per 100000 adults (95% confidence interval, 628.2-669.8), corresponding to 1591825 annual adult CAP hospitalizations in the United States. Clusters of CAP cases were found in areas with low-income and black/African American populations. Mortality during hospitalization was 6.5%, corresponding to 102821 annual deaths in the United States. Mortality at 30 days, 6 months, and 1 year was 13.0%, 23.4%, and 30.6%, respectively. Conclusions The estimated US burden of CAP is substantial, with >1.5 million unique adults being hospitalized annually, 100000 deaths occurring during hospitalization, and approximately 1 of 3 patients hospitalized with CAP dying within 1 year.

Enteral nutrition as stress ulcer prophylaxis in critically ill patients: A randomized controlled exploratory study

Purpose: We investigated whether early enteral nutrition alone may be sufficient prophylaxis against stress‐related gastrointestinal (GI) bleeding in mechanically ventilated patients. Materials and methods: Prospective, double blind, randomized, placebo‐controlled, exploratory study that included mechanically ventilated patients in medical ICUs of two academic hospitals. Intravenous pantoprazole and early enteral nutrition were compared to placebo and early enteral nutrition as stress‐ulcer prophylaxis. The incidences of clinically significant and overt GI bleeding were compared in the two groups. Results: 124 patients were enrolled in the study. After exclusion of 22 patients, 102 patients were included in analysis: 55 patients in the treatment group and 47 patients in the placebo group. Two patients (one from each group) showed signs of overt GI bleeding (overall incidence 1.96%), and both patients experienced a drop of >3 points in hematocrit in a 24‐hour period indicating a clinically significant GI bleed. There was no statistical significant difference in the incidence of overt or significant GI bleeding between groups (p = 0.99). Conclusion: We found no benefit when pantoprazole is added to early enteral nutrition in mechanically ventilated critically ill patients. The routine prescription of acid‐suppressive therapy in critically ill patients who tolerate early enteral nutrition warrants further evaluation. Highlights:GI bleeding has low incidence in the critically ill mechanically ventilated patients.Adding PPI to enteral nutrition may not offer an added prophylaxis against stress‐related GI bleeding.Our study supports the protective role of enteral nutrition in ICU.

Theory-Based Cartographic Risk Model Development and Application for Home Fire Safety.

There is a gap in the use of predictive risk models to identify areas at risk for home fires and burn injury. The purpose of this study was to describe the creation, validation, and application of such a model using a sample from an intervention study with parents of newborns in Jefferson County, KY, as an example. Performed was a literature search to identify risk factors for home fires and burn injury in the target population. Obtained from the American Community Survey at the census tract level and synthesized to create a predictive cartographic risk model was risk factor data. Model validation was performed through correlation, regression, and Moran’s I with fire incidence data from open records. Independent samples t-tests were used to examine the model in relation to geocoded participant addresses. Participant risk level for fire rate was determined and proximity to fire station service areas and hospitals. The model showed high and severe risk clustering in the northwest section of the county. Strongly correlated with fire rate was modeled risk; the best predictive model for fire risk contained home value (low), race (black), and non high school graduates. Applying the model to the intervention sample, the majority of participants were at lower risk and mostly within service areas closest to a fire department and hospital. Cartographic risk models were useful in identifying areas at risk and analyzing participant risk level. The methods outlined in this study are generalizable to other public health issues.

Geographic modeling for children at risk for home fires and burns

This study developed a predictive model for fires and burns among parents and children in Jefferson County, Kentucky. Eight risk factors for pediatric burns with census tract level data available were identified. Risk factors were synthesized to develop a cartographic model with risk levels low, medium, high, and severe. Validation was performed with fire dispatch data. At-risk areas were concentrated in the countys northwest. Risk was correlated with fire incidence rate (ρ=0.67, p<0.001). Significant risk factors were race (β=0.54, p<0.001), education (β=0.38, p<0.001), and year home built (β=-0.17, p=0.005). Cartographic modeling is a underutilized tool to identify at-risk areas.

Home fire safety intervention pilot with urban older adults living in Wales

The purpose of this pilot study was to evaluate the effects of a home fire safety (HFS) education program developed in the US, on improved HFS knowledge and practice in a purposive sample of 12 urban older adults living in Swansea, Wales. Knowledge was tested at baseline (T1), immediately after watching a Video on HFS (T2), and at 2-week follow-up (T3). A majority of the participants were Caucasian (n=9, 81.8%), and female (n=11, 91.7%); their mean age was 78years old (SD=12.7years). They had two chronic illnesses (n=1.8, SD=1.3), walked without help (n=7, 58.3%), and lived in a flat (n=10, 90.9%). Knowledge scores (percent correct) changed over time and were significantly different from T1 (46.7%) to T2 (59.2%, p=0.04) and from T1 (46.7%) to T3 (58.9%, p=0.04), but T2 and T3 (p=0.94) scores showed no difference. There is a need for educational HFS intervention programs aimed at this age group. This pilot successfully targeted active older adults living independently in sheltered housing complexes. Further fire safety research is needed with community dwelling older adults living in other types of housing.

Methods for computational disease surveillance in infection prevention and control: Statistical process control versus Twitter's anomaly and breakout detection algorithms

HighlightsWe compared traditional Statistical Process Control (SPC) charts with novel Anomaly/Breakout Detection (ABD) charts using Twitters Anomaly and Breakout detection algorithms for detecting out of control or anomalous HAI data.ABD charts appeared to work better than SPC charts in the context of seasonality and autocorrelation, two well‐known statistical issues with HAI data.These new charts may be useful for trending of HAI data and for other quality improvement data monitoring.An open‐access web application is provided for users to apply their own datasets to generate ABD and SPC charts. Background: Although not all health care‐associated infections (HAIs) are preventable, reducing HAIs through targeted intervention is key to a successful infection prevention program. To identify areas in need of targeted intervention, robust statistical methods must be used when analyzing surveillance data. The objective of this study was to compare and contrast statistical process control (SPC) charts with Twitters anomaly and breakout detection algorithms. Methods: SPC and anomaly/breakout detection (ABD) charts were created for vancomycin‐resistant Enterococcus, Acinetobacter baumannii, catheter‐associated urinary tract infection, and central line‐associated bloodstream infection data. Results: Both SPC and ABD charts detected similar data points as anomalous/out of control on most charts. The vancomycin‐resistant Enterococcus ABD chart detected an extra anomalous point that appeared to be higher than the same time period in prior years. Using a small subset of the central line‐associated bloodstream infection data, the ABD chart was able to detect anomalies where the SPC chart was not. Discussion: SPC charts and ABD charts both performed well, although ABD charts appeared to work better in the context of seasonal variation and autocorrelation. Conclusions: Because they account for common statistical issues in HAI data, ABD charts may be useful for practitioners for analysis of HAI surveillance data.

A Software Tool for Automated Upload of Large Clinical Datasets Using REDCap and the CAPO Database

Introduction: Obtaining clinical data from healthcare sources is necessary for conducting clinical research. New technologies now allow for connecting a research database to Electronic Medical Records remotely, allowing the automatic import of clinical research data. In this paper we design and evaluate a REDCap extension to import clinical records from an external health database. Methods: Many hospital EHRs are designed to use secure file transfer protocol (SFTP) repositories for data communication. We develop a REDCap plugin to connect to an external SFTP file repository for the import of clinical record data. We use the CAPO instance of REDCap and a sample set of clinical pneumonia variables for the connection. Results: The plugin allows the input of record data in a much shorter time than traditional data entry in addition to being less error prone. However, the formatting of the data in the SFTP file repository must be exact in order for the import to be successful. This can require setup time on the part of EHR IT staff. Conclusion: Developing a direct connection from EHR to research database can be an effective way to lower the overhead for conducting clinical research. We demonstrate a means to do this using REDCap and SFTP. DOI: 10.18297/jri/vol2/iss1/7 Received Date: February 12, 2018 Accepted Date: February 27, 2018 Website: https://ir.library.louisville.edu/jri Affiliations: 1University of Louisville Division of Infectious Diseases, Louisville, KY 40202 ©2018, The Author(s). *Correspondence To: William A Mattingly, PhD 501 E Broadway, Suite 120B Louisville, KY 40202 bill.mattingly@louisville.edu 31 ULJRI Vol 2, (1) 2018 ORIGINAL RESEARCH of SFTP-2-REDCap, a REDCap plugin to support the fast upload of data into a REDCap clinical research project.

Antibiotic Timing and Outcomes in Sepsis 1 1Disclosures: No financial or other conflicts of interest to disclose.

Background: We evaluated the effect of time spent in the emergency department (ED) and process of care on mortality and length of hospital stay in patients with sepsis or septic shock. Methods: An observational cohort study was conducted on 117 patients who came through the University of Louisville Hospital ED and subsequently were directly admitted to the intensive care unit (ICU). Variables of interest were time in the ED from triage to physical transport to the ICU, from triage to antibiotic(s) ordered, and from triage to antibiotic(s) administered. Expected mortality was calculated according to the University Health System Consortium Database. Primary and secondary outcomes were in‐hospital death and hospital length of stay in days, respectively. Results: We found no significant association between time in the ED and mortality between survivors and nonsurvivors (5.5 versus 5.7 hours, P = 0.804). After adjusting for expected mortality, a 22% increase in mortality risk was found for each hour delay from triage to antibiotic(s) ordered; a 15% increase in mortality risk was observed for each hour from triage to antibiotic(s) given. Both time from triage to antibiotic(s) ordered (hazard ratio [HR] = 0.8, P = 0.044) and time from triage to antibiotic(s) delivery (HR = 0.79, P = 0.0092) were independently associated with an increased hospital stay (HR = 0.79, P = 0.0092). Conclusion: Though no significant association between mortality and ED time was demonstrated, we observed a significant increase in mortality in septic patients with both delays in antibiotic(s) order and administration. Delay in care also resulted in increased hospital stays both overall and in the ICU.

Families with newborns: Using a cartographic model to identify those who are at risk for fires

We assessed whether a home fire safety intervention targeting families with newborn children in Jefferson County, Kentucky, reached those at severe risk using a cartographic model. Demographic and economic factors of 61 families were compared by census tract. Using geographic information systems (GIS), families were assigned a risk level (low, medium, high, or severe) based on the risk model. Families who participated differed from census tracts in that of being minority race (p=0.01). The median risk category of the families was medium risk. Sixty-five tracts were identified as high or severe risk and in need of future intervention. The model yielded a way to prioritize at-risk families. GIS is a useful tool for examining whether prevention interventions reached those in the severe risk category.

Elevated Blood Lead Levels by Length of Time From Resettlement to Health Screening in Kentucky Refugee Children

Objectives To examine elevated blood lead levels (EBLLs) in refugee children by postrelocation duration with control for several covariates. Methods We assessed EBLLs (≥ 5µg/dL) between 2012 and 2016 of children younger than 15 years (n = 1950) by the duration of resettlement to health screening by using logistic regression, with control for potential confounders (gender, region of birth, age of housing, and intestinal infestation) in a cross-sectional study. Results Prevalence of EBLLs was 11.2%. Length of time from resettlement to health screening was inversely associated with EBLLs (tertile 2 unadjusted odds ratio [OR] = 0.79; 95% confidence interval [CI] = 0.56, 1.12; tertile 3 OR = 0.62; 95% CI = 0.42, 0.90; tertile 2 adjusted odds ratio [AOR] = 0.62; 95% CI = 0.39, 0.97; tertile 3 AOR = 0.57; 95% CI = 0.34, 0.93). There was a significant interaction between intestinal infestation and age of housing (P < .003), indicating significant risk in the joint exposure of intestinal infestation (a pica proxy) and age of house. Conclusions Elevated blood lead levels were reduced with increasing length of time of resettlement in unadjusted and adjusted models. Improved housing, early education, and effective safe-house inspections may be necessary to address EBLLs in refugees.