Background: To determine whether the use of a tetracycline-class antibiotic is associated with an increased risk of developing pseudotumor cerebri syndrome (PTCS). Methods: We identified patients in the University of Utah Health system who were prescribed a tetracycline-class antibiotic and determined what percentage of those individuals were subsequently diagnosed with PTCS secondary to tetracycline use. We compared this calculation to the number of patients with PTCS unrelated to tetracycline use. Results: Between 2007 and 2014, a total of 960 patients in the University system between the ages of 12 and 50 were prescribed a tetracycline antibiotic. Among those, 45 were diagnosed with tetracycline-induced PTCS. We estimate the incidence of tetracycline-induced PTCS to be 63.9 per 100,000 person-years. By comparison, the incidence of idiopathic intracranial hypertension (IIH) is estimated to be less than one per 100,000 person-years (Calculated Risk Ratio = 178). Conclusions: Although a causative link between tetracycline use and pseudotumor cerebri has yet to be firmly established, our study suggests that the incidence of pseudotumor cerebri among tetracycline users is significantly higher than the incidence of IIH in the general population.

Introduction: Guidelines regarding rhythm control for atrial arrhythmias (AT/AF) are primarily based on symptom burden. Ambulatory electrocardiogram (AECG) monitoring is often performed to evaluate AT/AF burden and guide clinical decision-making. Yet, to date, little is known about the correlation of symptoms reported during AECG with recorded AT/AF. Methods: University of Utah patient AECGs with at least one AT/AF event over 7 or more days of monitoring were retrospectively reviewed - only events with symptoms or with AT/AF were included (other arrhythmias were rare and excluded). Patient triggered symptoms included reported shortness of breath, tiredness, palpitations, dizziness, or passing out. Tetrachoric correlation analysis was performed to evaluate the correlation between symptoms and AT/AF episodes. Results: We identified 742 patients with a mean age of 64 years, 50% female, 22% with chronic heart failure, overall mean CHA 2 DS 2 -VASc score of 2.5 and 67% with scores ≥2. There were 6,289 symptomatic events and 6,900 AT/AF episodes. Among these were 1,025 (16%) episodes of shortness of breath, 854 (14%) of tiredness, 2,660 (42%) of palpitations, 794 (13%) of dizziness, and 95 (2%) of passing out. Symptomatic events were less likely to predict simultaneous AT/AF compared to sinus rhythm on AECG, with a moderate inverse tetrachoric correlation of -0.66 (range -1 to 1, with 1 representing perfect positive correlation). Conclusion: Patient-triggered symptomatic events were inversely correlated with recorded AT/AF events and represented an unacceptable marker of actual arrhythmia. A more holistic approach to assessment of ATAF symptoms is needed to improve patient selection for rhythm control therapy.

Introduction: Emerging evidence supports more aggressive rhythm control of atrial fibrillation (AF) among heart failure (HF) patients. Yet, the impact of AF on symptom status in HF and the relationship to rate control have not been well studied in the setting of prolonged, ambulatory monitoring. Hypothesis: Patient-triggered symptomatic events (PTSEs) can predict the simultaneous presence of atrial tachycardia/AF (ATAF) on cardiac event monitors(CEM) among HF patients with documented atrial arrhythmia. Methods: All UHealth HF patients with at least 1 ATAF event over ≥7 days on CEMs were retrospectively reviewed. Tetrachoric correlation analysis between PTSEs and ATAF events and t-tests of mean heart rates(HR) were performed. Results: A total of 3,162 events were analyzed among 185 HF patients. The mean age was 68 years and 43% were female; 61% had CAD; the mean ejection fraction was 54% (SD 16%); and 74% were on beta-blockers. There were 2347 ATAF events, 1031 PTSEs, and 216 symptomatic ATAF events. Of PTSEs, 21.0% were ATAF, and of ATAF events, 9.2% were symptomatic. Overall mean HR of PTSEs was 94bpm (SD 29), lower than asymptomatic events, 103bpm (SD 29, p<0.001). Mean HR of symptomatic ATAF events was 117bpm (SD 35), compared with asymptomatic ATAF (110bpm, SD 31, p=0.008). See Figure 1. PTSEs were less likely to predict simultaneous ATAF compared to sinus rhythm, with a moderate inverse tetrachoric correlation of -0.69 (bootstrapped 95% CI -0.65, -0.72). Conclusion: Among patients with AF & HF, symptoms are a poor marker of atrial arrhythmia. PTSEs on ambulatory monitoring are not correlated with ATAF events in a clinically meaningful association and are not adequately explained by the heart rate differences. Classic symptom-based treatment of AF and HF should give way to more comprehensive quality-of-life and substrate guides for therapy.

Introduction: COVID-19 has had a profound effect on everyday life. In one survey, 30.8% of respondents reported “drinking a lot more than normal” during the pandemic. We examined the incidence of alcohol related liver diseases from 2015 to the present to determine whether there was a significant increase of these diseases in the setting of the COVID-19 pandemic. Methods: The number of patients at a large academic center with a first occurrence of alcoholic cirrhosis and alcoholic hepatitis were extracted for each quarter between 2015 and 2021. A quarter was defined as a three-month period with the first quarter (Q1) being the first three months of the year, the second quarter (Q2) the next three months, and so on. Data was further broken down by whether the diagnosis was made inpatient, outpatient, or in the emergency department. This data was compared to the number of outpatient visits for all liver related illnesses in each quarter to standardize the data to a rate per 1000 visits. Diagnoses and inpatients per 1000 visits from Q2 2019 to Q1 2020 of alcoholic cirrhosis and alcoholic hepatitis was compared to that of Q2 2020 to Q1 2021. A Fisher’s exact test was done to determine if there was a significant difference. Results: Diagnoses of alcoholic cirrhosis per quarter fluctuated between 55 and 90 from Q1 2016 to Q1 2020 before increasing to a peak of 267 in Q1 2021. The same trend was found in diagnoses per 1000 visits. (Figure 1) New cases and diagnoses per 1000 visits of alcoholic hepatitis have generally increased from Q1 2016 to Q1 2020 with a more precipitous increase thereafter. In the 12-month period encompassing Q2 2019 to Q1 2020, diagnoses of alcoholic cirrhosis per 1000 visits were 12.3, increasing to 20.5 in the next 12-month period with inpatients per 1000 visits increasing from 5.4 to 8. Both differences have a p-value of < 0.001. When comparing these periods for alcoholic hepatitis, there was an increase in diagnoses per 1000 visits from 5.8 to 7.5 (P = 0.014) and from 4.2 to 5.4 for inpatients per 1000 visits (P = 0.047). Conclusion: There have been more diagnoses and inpatient visits of alcohol related liver diseases since Q2 2020, the first full quarter affected by COVID-19. This could be due to worsening of pre-existing mental health issues or lack of social support during this period. Regardless of the cause, this data is useful for understanding public health needs as we recover from the current pandemic and in future pandemics.Figure 1.: Kaplan-Meier Plot on All-cause Mortality.

POSTER ABSTRACTS from Third Annual Public Meeting: Mobilizing Computable Biomedical Knowledge (MCBK 2020)

BACKGROUND:Hospital-acquired pressure injuries are a serious problem among critical care patients. Although most hospital-acquired pressure injuries are stage 2 (partial-thickness skin loss with exposed dermis), no studies have examined outcomes of stage 2 pressure injuries among critical care patients.OBJECTIVES:To examine outcomes of stage 2 hospital-acquired pressure injuries among critical care patients and identify factors associated with nonhealing stage 2 hospital-acquired pressure injuries.METHODS:Electronic health record data were used to identify surgical critical care patients with stage 2 hospital-acquired pressure injuries at a level I trauma center. Univariate Cox regressions were used to identify factors associated with healed stage 2 hospital-acquired pressure injuries.RESULTS:Of 6376 surgical critical care patients, 298 (4.7%) developed stage 2 hospital-acquired pressure injuries; complete data were available for 253 patients. Of these 253 patients, 160 (63%) had unhealed pressure injuries at hospital discharge. Factors inversely related to the presence of a healed hospital-acquired pressure injury were older age (hazard ratio, 0.98; 95% CI, 0.97-0.99; P = .003), elevated serum lactate (hazard ratio, 0.85; 95% CI, 0.75-0.96; P = .01), elevated serum creatinine (hazard ratio, 0.87; 95% CI, 0.77-0.98; P = .02), and lower oxygenation (hazard ratio, 0.64; 95% CI, 0.41-1.00; P = .05).CONCLUSIONS:Stage 2 hospital-acquired pressure injuries were not healed at discharge in 63% of the patients in our sample. Nurses should be especially vigilant in treating pressure injury patients who are older, have altered oxygenation or perfusion (elevated serum lactate level or decreased oxygenation), or have evidence of renal compromise.

BACKGROUND: The use of venous duplex ultrasonography (VDU) for confirmation of deep venous thrombosis in neurosurgical patients is costly and requires experienced personnel. We evaluated a protocol using D-dimer levels to screen for venous thromboembolism (VTE), defined as deep venous thrombosis and asymptomatic pulmonary embolism. METHODS: We used a retrospective bioinformatics analysis to identify neurosurgical inpatients who had undergone a protocol assessing the serum D-dimer levels and had undergone a VDU study to evaluate for the presence of VTE from March 2008 through July 2017. The clinical risk factors and D-dimer levels were evaluated for the prediction of VTE. RESULTS: In the 1918 patient encounters identified, the overall VTE detection rate was 28.7%. Using a receiver operating characteristic curve, an area under the curve of 0.58 was identified for all D-dimer values (P = 0.0001). A D-dimer level of >= 2.5 mu g/mL on admission conferred a 30% greater relative risk of VTE (sensitivity, 0.43; specificity, 0.67; positive predictive value, 0.27; negative predictive value, 0.8). A D-dimer value of >= 3.5 mu g/mi during hospitalization yielded a 28% greater relative risk of VTE (sensitivity, 0.73; specificity, 0.32; positive predictive value, 0.24; negative predictive value, 0.81). Multivariable logistic regression showed that age, male sex, length of stay, tumor or other neurological disease diagnosis, and D-dimer level >= 3.5 mu g/mL during hospitalization were independent predictors of VTE. CONCLUSIONS: The D-dimer protocol was beneficial in identifying VTE in a heterogeneous group of neurosurgical patients by prompting VDU evaluation for patients with a D-dimer values of >= 3.5 mu g/mL during hospitalization. Refinement of this screening model is necessary to improve the identification of VTE in a practical and costeffective manner.

Exposomic research requires the generation of comprehensive spatio-temporal records of exposures along with capturing associated metadata describing limitations and uncertainties associated with the data. We describe the architecture of a metadata-driven Big Data integration platform for integration of sensor and health data to support diverse translational exposomic research.

BACKGROUND:Hospital-acquired pressure injuries are a serious problem among critical care patients. Some can be prevented by using measures such as specialty beds, which are not feasible for every patient because of costs. However, decisions about which patient would benefit most from a specialty bed are difficult because results of existing tools to determine risk for pressure injury indicate that most critical care patients are at high risk.OBJECTIVE:To develop a model for predicting development of pressure injuries among surgical critical care patients.METHODS:Data from electronic health records were divided into training (67%) and testing (33%) data sets, and a model was developed by using a random forest algorithm via the R package "randomforest."RESULTS:Among a sample of 6376 patients, hospital-acquired pressure injuries of stage 1 or greater (outcome variable 1) developed in 516 patients (8.1%) and injuries of stage 2 or greater (outcome variable 2) developed in 257 (4.0%). Random forest models were developed to predict stage 1 and greater and stage 2 and greater injuries by using the testing set to evaluate classifier performance. The area under the receiver operating characteristic curve for both models was 0.79.CONCLUSION:This machine-learning approach differs from other available models because it does not require clinicians to input information into a tool (eg, the Braden Scale). Rather, it uses information readily available in electronic health records. Next steps include testing in an independent sample and then calibration to optimize specificity.

Exposomic research is an emerging field of study that seeks to address environmental exposures and its effects on life, health, and disease development. Research using exposomic data includes those related to the research and development of sensor devices, chemistry of environmental species and exposure pathways. Concurrently, with the increase in biomedical research interests and advances in exposome data collection, data are increasingly available.1 In order to support such translational exposomic studies, there is a need for an informatics infrastructure along with tools to facilitate access and use by investigators. However, to date, there is no standard or systematic way to model a translational exposomic research study.To support research using personalized and environmental sensor devices, we developed a model for exposomic studies to cover the design, conduct and analytic phases of a study. We reviewed existing study metadata representations and compared them with a sample of publicly available exposome studies from the literature and others elicited from researchers. Gaps were found in how sensor data are represented in the existing study metadata models and in general, a lack of detail into data requirements for exposome studies; all needed for an informatics infrastructure. To address these gaps we consolidated data elements from existing domain specific models. In particular, we incorporated the Sensor Common Metadata Specification (SCMS) into the model. The SCMS is currently being implemented in the Utah PRISMS Informatics Ecosystem (UPIE) and includes metadata of measured data from sensors, the deployment of sensors, and the sensors itself.2 This model is currently being validated within UPIE for reproducible representations of exposomic studies, and computable specification of study data integration, to support the study of effects of the environment on health and advance the science in this area.

OBJECTIVES:Broad-spectrum antibiotics are commonly used for the empiric treatment of acute hematogenous osteomyelitis and often target methicillin-resistant Staphylococcus aureus (MRSA) with medication-associated risk and unknown treatment benefit. We aimed to compare clinical outcomes among patients with osteomyelitis who did and did not receive initial antibiotics used to target MRSA.METHODS:A retrospective cohort study of 974 hospitalized children 2 to 18 years old using the Pediatric Health Information System database, augmented with clinical data. Rates of hospital readmission, repeat MRI and 72-hour improvement in inflammatory markers were compared between treatment groups.RESULTS:Repeat MRI within 7 and 180 days was more frequent among patients who received initial MRSA coverage versus methicillin-sensitive S aureus (MSSA)-only coverage (8.6% vs 4.1% within 7 days [P = .02] and 12% vs 5.8% within 180 days [P < .01], respectively). Ninety- and 180-day hospital readmission rates were similar between coverage groups (9.0% vs 8.7% [P = .87] and 10.9% vs 11.2% [P = .92], respectively). Patients with MRSA- and MSSA-only coverage had similar rates of 72-hour improvement in C-reactive protein values, but patients with MRSA coverage had a lower rate of 72-hour white blood cell count normalization compared with patients with MSSA-only coverage (4.2% vs 16.4%; P = .02).CONCLUSIONS:In this study of children hospitalized with acute hematogenous osteomyelitis, early antibiotic treatment used to target MRSA was associated with a higher rate of repeat MRI compared with early antibiotic treatment used to target MSSA but not MRSA. Hospital readmission rates were similar for both treatment groups.

BACKGROUND:Approximately half of hospital-acquired pressure injuries identified among critical care patients are stage 1. Although stage 1 injuries are common, outcomes associated with them among critical care patients have not been examined.OBJECTIVES:To examine the outcomes of stage 1 pressure injuries among critical care patients and to identify factors associated with worsening of pressure injuries.METHODS:Electronic health records were used to determine which surgical critical care patients at a level I trauma center and academic medical center had stage 1 pressure injuries. Competing risk survival analysis was used to identify factors associated with worsening of pressure injuries.RESULTS:Review of 6377 patient records indicated that 259 patients (4.1%) experienced stage 1 injuries. The injuries persisted until discharge from the hospital in 92 patients (35.5%), worsened into injuries of stage 2 or greater in 84 (32.4%), and healed in 83 (32.0%). Patients whose pressure injuries worsened were more likely to be older (subdistribution hazard ratio [SHR], 1.02; 95% CI, 1.01-1.03; P = .002), or to have higher levels of serum lactate (SHR, 1.06; 95% CI, 1.02-1.10; P = .007), lower levels of hemoglobin (SHR, 0.82; 95% CI, 0.71-0.96; P = .01), or decreased oxygen saturation by pulse oximetry (< 90%; SHR, 1.50; 95% CI, 1.00-2.25; P = .05).CONCLUSIONS:Stage 1 pressure injuries worsen in about one-third of patients (32.4%). Nurses should consider maximal treatment for patients who are older or who experience alterations in oxygen delivery or perfusion.

Exposomic research may utilize multiple sensors to measure individuals' environment and their physiological responses. These sensors measure physical, chemical and biological properties and have wide variations in their capabilities and performance. It is therefore important to provide sensor characterization information in order to make appropriate decisions when selecting and utilizing sensors for research studies and analysis or when performing meta-studies aggregating data from multiple sensors. In this presentation, we discuss the development, organization, and use of a sensor metadata library (SML) developed by the Utah PRISMS Informatics Ecosystem (UPIE) (Grant NIH NIBIB U54EB021973).We performed a needs assessment and utilized the sensor common metadata specifications (SCMS) developed by UPIE in designing the SML. SCMS contains sensor metadata pertaining to the physical device, their deployment and resulting measurement outputs. The SML includes domains describing the physical characteristics of devices, including hardware and software versioning, measurement and/or sample collection characteristics, validation protocols, ownership and additional technical documentation. We implemented the SML using the Ne04j graph database.The SML includes tools for capturing and discovering metadata for new and updated versions of sensors. Sensor owners can submit metadata to the SML using a REDCap survey form, which is then curated and stored. Researchers can visualize stored sensor metadata graphically as interlinked nodes of information.This SML serves as a researcher-facing tool - as a repository of sensor information for researchers to design their exposomic studies and understand their limitations; and an inventory of available sensors for prospective study deployments. It also serves as a source of metadata store for the UPIE for performing semantically consistent metadata driven integration of heterogeneous sensor data streams for exposomic study analysis.

BACKGROUND AND OBJECTIVES:Gastroesophageal reflux (GER), aspiration, and secondary complications lead to morbidity and mortality in children with neurologic impairment (NI), dysphagia, and gastrostomy feeding. Fundoplication and gastrojejunal (GJ) feeding can reduce risk. We compared GJ to fundoplication using first-year postprocedure reflux-related hospitalization (RRH) rates.METHODS:We identified children with NI, dysphagia requiring gastrostomy tube feeding and GER undergoing initial GJ placement or fundoplication from January 1, 2007 to December 31, 2012. Data came from the Pediatric Health Information Systems augmented by laboratory, microbiology, and radiology results. GJ placement was ascertained using radiology results and fundoplication by International Classification of Diseases, Ninth Revision, Clinical Modification codes. Subjects were matched within hospital using propensity scores. The primary outcome was first-year postprocedure RRH rate (hospitalization for GER disease, other esophagitis, aspiration pneumonia, other pneumonia, asthma, or mechanical ventilation). Secondary outcomes included failure to thrive, death, repeated initial intervention, crossover intervention, and procedural complications.RESULTS:We identified 1178 children with fundoplication and 163 with GJ placement, matching 114 per group. Matched sample RRH incident rate per child-year (95% confidence interval) for GJ was 2.07 (1.62–2.64) and for fundoplication 1.67 (1.28–2.18), P = .19. Odds of death were similar between groups. Failure to thrive, repeat of initial intervention, and crossover intervention were more common in the GJ group.CONCLUSIONS:In children with NI, GER, and dysphagia: fundoplication and GJ feeding have similar RRH outcomes. Either intervention can reduce future aspiration risk; the choice can reflect non-RRH-related complication risks, caregiver preference, and clinician recommendation.

PURPOSE:The purpose of the current study was to examine the relationship between pressure injury development and the Braden Scale for Pressure Sore Risk subscale scores in a surgical intensive care unit (ICU) population and to ascertain whether the risk represented by the subscale scores is different between older and younger patients.DESIGN:Retrospective review of electronic medical records.SUBJECTS AND SETTING:The sample comprised patients admitted to the ICU at an academic medical center in the Western United States (Utah) and Level 1 trauma center between January 1, 2008 and May 1, 2013. Analysis is based on data from 6377 patients.METHODS:Retrospective chart review was used to determine Braden Scale total and subscale scores, age, and incidence of pressure injury development. We used survival analysis to determine the hazards of developing a pressure injury associated with each subscale of the Braden Scale, with the lowest-risk category as a reference. In addition, we used time-dependent Cox regression with natural cubic splines to model the interaction between age and Braden Scale scores and subscale scores in pressure injury risk.RESULTS:Of the 6377 ICU patients, 214 (4%) developed a pressure injury (stages 2-4, deep tissue injury, or unstageable) and 516 (8%) developed a hospital-acquired pressure injury of any stage. With the exception of the friction and shear subscales, regardless of age, individuals with scores in the intermediate-risk levels had the highest likelihood of developing pressure injury.CONCLUSION:The relationship between age, Braden Scale subscale scores, and pressure injury development varied among subscales. Maximal preventive efforts should be extended to include individuals with intermediate Braden Scale subscale scores, and age should be considered along with the subscale scores as a factor in care planning.

OBJECTIVES/SPECIFIC AIMS: Issues with recruiting the targeted number of participants in a timely manner often results in underpowered studies, with more than 60% of clinical studies failing to complete or requiring extensions due to enrollment issues. The objective of this study is to develop and implement a scalable, organization wide platform to enhance accrual into clinical research studies. METHODS/STUDY POPULATION: We are developing and evaluating an informatics platform called Utah Utility for Research Recruitment (U2R2). U2R2 consists of 2 components: (i) Semantic Matcher: an automated trial criterion to patient matching component that also reports uncertainty associated with the match, and (ii) Match Delivery: mechanisms to deliver the list of matched patients for different research and clinical settings. As a first step, we limited the Semantic Matcher to utilize only structured data elements from the patient record and trial criteria. We are now including distributional semantic methods to match complete patient records and trial criteria as documents. We evaluated the first phase of U2R2 based on a randomized trial with a target enrollment of 220 participants that compares 2 treatment strategies for managing back pain (physical therapy and usual care) for individuals consulting a nonsurgical provider and symptomatic <90 days. RESULTS/ANTICIPATED RESULTS: U2R2 identified 9370 patients from the University of Utah Hospitals and Clinics as potential matches. Of these 9370, 1145 responded to the Back Pain study research team’s email or phone communications, and were further screened by phone. In total, 250 participants completed a screening visit, resulting in the current study enrollment of 130 participants. Forty-three of 1145 patients refused to participate, and 50 participants no-showed their screening visit. DISCUSSION/SIGNIFICANCE OF IMPACT: A recruitment platform can enhance potential participant identification, but requires attention to multiple issues involved with clinical research studies. Clinical eligibility criteria are usually unstructured and require human mediation and abstraction into discrete data elements for matching against patient records. In addition, key eligibility data are often embedded within text in the patient record. Distributional semantic approaches, by leveraging this content, can identify potential participants for screening with more specificity. The delivery of the list of matched patient results should consider characteristics of the research study, population, and targeted enrollment (eg, back pain being a common disorder and the possibility of the patient visiting different types of clinics), as well as organizational and socio-technical issues surrounding clinical practice and research. Embedding the delivery of match results into the clinical workflow by utilizing user-centered design approaches and involving the clinician, the clinic, and the patient in the recruitment process, could yield higher accrual indices.