Flu Test Research Articles

Acute caffeine reverses the disruptive effects of chronic fluoxetine on the sexual behavior of female and male rats.

Sexual side effects of chronic treatment with selective serotonin reuptake inhibitors (SSRIs) in humans include anorgasmia and loss of sexual desire and/or arousal which interferes with treatment compliance. There are few options at present to reduce these effects. Because orgasm and desire are mediated in part by activation of sympathetic arousal, we asked whether the sympathomimetic effects of acute caffeine treatment could reverse these effects. The present study examined whether acute treatment with caffeine (CAF; 10 or 20mg/kg, ip) versus vehicle could ameliorate the disruption of appetitive and consummatory measures of copulatory behavior produced by chronic fluoxetine (10mg/kg, sc) in adult, sexually active female or male rats. Sexually experienced female or male rats received daily injections of FLU over a 24-day period and were tested for sexual behaviors five times at 4-day intervals during this period in bilevel pacing chambers. Females had been ovariectomized and given hormone replacement with estradiol benzoate and progesterone prior to each test. Males were left gonadally intact. Four days after the final FLU test, rats were randomly assigned to one of the three doses of CAF and received ip injections of CAF or the saline vehicle 60min before testing. Chronic FLU reduced solicitations and lordosis over time in females and reduced the number of ejaculations in males. Both doses of CAF restored solicitations and lordosis in females and ejaculations in males. On their own, both doses of CAF increased females' pacing behavior and the number of mounts and intromissions in the males. Stimulation of sympathetic outflow by CAF may constitute a readily accessible on-demand treatment for the sexual side-effects of SSRIs.

Combined COVID-19 and flu tests could help overwhelmed hospitals

In greater Kansas City, COVID-19 cases are climbing. Raghu Adiga, the chief medical officer at Liberty Hospital, is worried—and a little bit angry. He has neither the staff nor the testing capacity...

FDA grants EUA to at-home COVID-19 test

The US Food and Drug Administration has given its first emergency use authorization (EUA) for an at-home COVID-19 test to Lucira Health, which originally tried to develop an at-home flu test. The d...

Combined COVID-19 and flu tests could help overwhelmed hospitals

Combined COVID-19 and flu tests could help overwhelmed hospitals

Outcomes of Patients With Hospital-Acquired Influenza

Background: Hospital-acquired influenza (HA flu) lacks a consensus definition. However, it is known to be associated with increased inpatient morbidity and mortality. Objective: To describe the clinical course of HA flu in a cohort population. Methods: A retrospective cohort study was conducted at a tertiary-care adult and pediatric teaching hospital. Patients with HA flu during 3 seasons, 2016 through 2019, were identified from medical record information based on timing of the onset of signs and symptoms and positive virologic testing >72 hours after admission. Influenza infection was confirmed by multiplex respiratory PCR, influenza A/B PCR, or direct fluorescent antibody tests. Chart review was performed to abstract patient demographics and comorbidities, length of stay, testing, and timing to antiviral administration as well as diagnosis of pneumonia, coinfections, and 30-day mortality. Escalation of care during hospitalization was defined as a new requirement of supplemental oxygen, invasive or noninvasive ventilation, and transfer to an intensive care unit. Results: During the 3 flu seasons, 132 patients were identified with HA flu; 76 (58%) were women, 6 (4.6%) were aged <18 years, and 126 (95.4%) were adults. Annually, HA-flu patients accounted for 5%–7.8% of all patients hospitalized with laboratory-proven influenza. The median duration between hospitalization and positive flu test was 15 days, and the median length of stay after influenza diagnosis was 6 days. Antiviral treatment was received by 96% of the patients. In total, 41 patients (31%) showed radiographic evidence for pneumonia. Coinfection with either a viral or bacterial pathogen was identified in 25% of the cases. In addition, 26% of the patients experienced an escalation of care, and 20 patients (15%) were transferred to the intensive care unit after HA flu diagnosis. Furthermore, 4 deaths (3%) were attributed to influenza during their hospitalization. Conclusions: HA flu was a frequent cause for escalation in care and was associated with a mortality rate substantially higher than is typically seen in community-based populations with influenza. Coinfection was mostly related to bacteremia and pneumonia, yet not all pneumonias had an associated microbiological diagnosis other than influenza, and there was no significant association between coinfection and mortality. Future work should explore more precise definitions for HA flu as well as its complications.Funding: NoneDisclosures: None

Impact of Rapid PCR Influenza Testing on the Rate of Inpatient Admissions During Influenza Season at a Tertiary-Care Center

Background: Influenza causes a high burden of disease in the United States, with an estimate of 960,000 hospitalizations in the 2017–2018 flu season. Traditional flu diagnostic polymerase chain reaction (PCR) tests have a longer (24 hours or more) turnaround time that may lead to an increase in unnecessary inpatient admissions during peak influenza season. A new point-of-care rapid PCR assays, Xpert Flu, is an FDA-approved PCR test that has a significant decrease in turnaround time (2 hours). The present study sought to understand the impact of implementing a new Xpert Flu test on the rate of inpatient admissions. Methods: A retrospective study was conducted to compare rates of inpatient admissions in patients tested with traditional flu PCR during the 2017–2018 flu season and the rapid flu PCR during the 2018–2019 flu season in a tertiary-care center in greater Detroit area. The center has 1 pediatric hospital (hospital A) and 3 adult hospitals (hospital B, C, D). Patients with influenza-like illness who presented to all 4 hospitals during 2 consecutive influenza seasons were analyzed. Results: In total, 20,923 patients were tested with either the rapid flu PCR or the traditional flu PCR. Among these, 14,124 patients (67.2%) were discharged from the emergency department and 6,844 (32.7%) were admitted. There was a significant decrease in inpatient admissions in the traditional flu PCR group compared to the rapid flu PCR group across all hospitals (49.56% vs 26.6% respectively; P < .001). As expected, a significant proportion of influenza testing was performed in the pediatric hospital, 10,513 (50.2%). A greater reduction (30% decrease in the rapid flu PCR group compared to the traditional flu PCR group) was observed in inpatient admissions in the pediatric hospital (Table 1) Conclusions: Rapid molecular influenza testing can significantly decrease inpatient admissions in a busy tertiary-care hospital, which can indirectly lead to improved patient quality with easy bed availability and less time spent in a private room with droplet precautions. Last but not the least, this testing method can certainly lead to lower healthcare costs.Funding: NoneDisclosures: None

Rapid PCR Influenza Testing Decreases Inappropriate Empiric Antibiotic Use

Background: The clinical picture of influenza-like illness can mimic bacterial pneumonia, and empiric treatment is often initiated with antibacterial agents. Molecular testing such as polymerase chain reaction (PCR) is often used to diagnose influenza. However, traditional PCR tests have a slow turnaround time and cannot deliver results soon enough to influence the clinical decision making. The Detroit Medical Center (DMC) implemented the Xpert Flu test for all patients presenting with influenza-like illness (ILI). We evaluated antibacterial use after implementation of rapid influenza PCR Xpert Flu. Methods: We conducted a retrospective study comparing all pediatric and adult patients tested using traditional RT PCR during the 2017–2018 flu season to patients tested using the rapid influenza Xpert Flu during the 2018–2019 flu season in a tertiary-care hospital in Detroit, Michigan. These patients were further divided into 3 groups: not admitted (NA), admitted to acute-care floor (ACF), or admitted to intensive care unit (ICU). The groups were then compared with respect to percentage of antibacterial use after traditional RT PCR versus rapid influenza Xpert Flu testing during their hospital visit for ILI. The χ2 test was used for statistical analyses. Results: In total, 20,923 patients presented with influenza-like illness during the study period: 26% (n = 5,569) had the rapid influenza Xpert Flu and 73.4% (n= 15,354) had traditional RT PCR. For a comparison of the number of patients in 3 groups (NA, ACF, and ICU) and type of influenza PCR performed among these patients, please refer to Table 1. When comparing antibacterial use in the NA group, the proportions of patients who received antibacterial agents in the traditional RT PCR group versus the rapid influenza Xpert Flu group were 24.4% (n = 695) versus 3.9% (n = 450), respectively (P < .0001). In the ACF group, the proportions of patients who received antibacterial agents in the traditional RT PCR group versus the rapid influenza Xpert Flu group was 62.3% (n = 1,406) versus 27.7% (n = 994), respectively (P < .001). In the ICU group, the proportions of patients who received antibacterials in the traditional RT PCR group versus the rapid influenza Xpert Flu group were 80.3% (n = 382) versus 38.3% (n = 204), respectively (P < .0001). Conclusions: With rising antimicrobial resistance and increasing influenza morbidity and mortality, rapid diagnostics not only can help diagnose influenza faster but also can reduce inappropriate antimicrobial use.Funding: NoneDisclosures: None

Some reasons to stay energized during uncertain times

Over the last few weeks, there have been some sensational developments for pharmacists and our patients. I hope you’re as excited about them as I am. At the end of July, President Trump signed an executive order resurrecting a rule that could force PBMs to pass on to Medicare Part D beneficiaries any discounts from manufacturer rebates and other price concessions at point of sale. It was a rare L for PBMs, and it’s a positive sign that the executive branch recognizes that PBMs do not make drugs more affordable to patients—yet it’s not quite a W for us. Now, our job is to work with the U.S. Department of Health and Human Services (HHS) and our pharmacy partners to ensure the agencies implementing the rebate rule also end PBMs’ gaming of Medicare regulation loopholes that allows them to inflate patients’ prescription-drug costs and put pharmacies on life support by extracting vampiric direct and indirect remuneration (DIR) fees—not just retroactively, but once and for all. A few weeks later, CMS issued updated guidance granting new flexibility for accredited and recognized diabetes self-management training (DSMT) programs already billing Medicare Part B for DSMT services. These programs, CMS said, may furnish and bill for DSMT services provided via telehealth during the COVID-19 public health emergency. This is a huge triumph for diabetes care and education specialists and the Medicare beneficiaries with diabetes whom they serve. Then HHS announced it would authorize licensed pharmacists to provide all vaccines recommended by CDC’s Advisory Committee on Immunization Practices and approved or licensed by FDA to all children ages 3 to 18 during the COVID-19 pandemic, regardless of state laws and regulations to the contrary. This is great news. APhA has long advocated that pharmacists are uniquely positioned to address this public health emergency, and we worked with HHS to develop this strategy to engage all pharmacists. As Admiral Brett Giroir, the HHS assistant secretary for health, said in the announcement, pharmacists have always been a trusted voice in the community, and they’re readily accessible. We couldn’t agree more. We’ve still got some milestones to reach. Congress must include coverage for pharmacists’ COVID-19 and flu testing and immunizing services under Medicare Part B in the next coronavirus stimulus package. Keep writing and calling Capitol Hill to tell your patients’ stories and how much more pharmacists could be doing to help them stay safe and healthy, during the public health crisis and beyond. We aren’t done, but I’m thrilled with the progress we’re making and more optimistic than ever about pharmacy’s future. Let’s get there together!

320: Physiologic parameters and sepsis bundle failures during the 2017-2018 influenza season

We characterized gravidas with influenza-like illness during the 2017-2018 influenza season in the context of a hospital-wide sepsis bundle. The bundle is triggered for any 2 abnormal vital signs, defined as: temperature < 36°C or ≥38°C, heart rate >90/min, systolic blood pressure < 90mmHg, and respiratory rate >20/min. This was a retrospective cohort study of 2017-2018 encounters for influenza-like illness (ILI), defined as respiratory symptoms for which a rapid flu test was ordered. Multiple encounters during a single pregnancy were possible. We excluded patients with RSV, pyelonephritis, non-influenza indications, or indeterminate flu testing. We compared “abnormal” vital signs recorded within 4h of presentation and hospitalization rates among gravidas with positive versus negative flu tests. Missing values were assumed normal. Between September 1, 2017 and March 31, 2018, 913 encounters for ILI were identified. Of these, 100(11%) were excluded (Figure 1). Of the 165 first, 271 second, and 377 third trimester encounters, 64(39%), 85(31%), and 144(38%) were influenza-positive, respectively (Table 1). Influenza positivity was associated with “abnormal” vital signs in all trimesters. Influenza-positive gravidas had two to three times the risk of having 2 abnormal vital signs, which would trigger sepsis bundle initiation and assessment for end-organ damage (i.e., lactate). Relative to influenza-negative encounters, influenza-positivity was associated with 1.6 to 2.1 times the risk for hospital admission for all trimesters, though absolute frequency of admission was low: 36%, 44%, and 58% for each trimester. ICU admission was rare. Influenza-positivity in pregnancy is associated with vitals signs that trigger a sepsis alert requiring further action, regardless of trimester. Despite higher risk for hospital admission among gravidas with influenza, most women are actually discharged after evaluation. A hospital-wide sepsis bundle fails to identify pregnant women with influenza at highest risk for severe morbidity.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

2614. Demographic and Clinical Characteristics by Antiviral Prescription in Influenza-Positive Children who Presented to Seven US Emergency Departments

BackgroundAntiviral (AV) therapy is recommended for children < 2 years, hospitalized, or with underlying conditions (UC) and suspected influenza (flu). We sought to compare demographic and clinical characteristics by AV prescription in flu-positive children who presented to the emergency department (ED) and determine the percentage of AV prescription in these high-risk children.MethodsChildren < 18 years who presented with respiratory symptoms and/or fever at seven New Vaccine Surveillance Network sites were enrolled. We conducted interviews, obtained mid-turbinate nasal and/or throat swabs for molecular flu testing (results unknown to providers), and reviewed medical charts for AV prescription after presenting to the ED. These are preliminary data.ResultsFrom December 2016 to June 2018, 9,524 subjects were enrolled and tested for flu; 1,260 (13%) were flu-positive by research testing; 54% were male, median age was 41 months, and 23% were prescribed an AV. The frequency of AV prescription differed by study site (Figure 1). Among research-tested flu-positive patients, AV were prescribed to 25% of children < 2 years, 31% of children with UC, and 51% admitted to the hospital from the ED (Table 1). Of the 388 (31%) clinically-tested flu-positive patients, 52%, 66%, and 77% of the same high-risk groups were prescribed an AV, respectively.ConclusionAV prescriptions varied by study site and differences by race, ethnicity, and clinical presentation were noted. Clinical testing was associated with higher use of AV treatment in appropriate target patients. Efforts are needed to understand AV use patterns and improve prescription rates in recommended patients. Disclosures All authors: No reported disclosures.

2758. Identifying Populations at High-Risk for Influenza-Related Hospitalization: A Real-World Analysis of Commercially Insured Population in the United States

BackgroundThe disease burden of seasonal influenza (flu) is high and contributes to morbidity, mortality and healthcare utilization. While only 1–2% of flu cases are hospitalized, these events are costly. The objective of this study was to describe and quantify risk factors for flu hospitalization.MethodsPatients with 1 flu diagnosis (Dx) over 4 seasons (October 1, 2014–May 31, 2018) in IQVIA’s Real-World Data Adjudicated Claims – US database were selected into the study; the earliest flu Dx was the index date. Patients were required to have ≥12 months continuous enrollment in their health plan before index (baseline), ≥30 days after index, and either a record of a flu test ± 14 days of index or a flu Dx in the primary position. Comorbidities during a fixed 12-month baseline period were categorized by AHRQ and CDC definitions. The study outcome of interest, flu-related hospitalization during the 30-day follow-up period, was defined as hospitalization with Dx of flu or a pre-defined flu-related complication in any position. A logistic regression model assessed the odds of flu-related hospitalization, adjusting for age, sex, region, payer, season of index Dx, evidence of flu vaccination, and comorbidities.ResultsMore than 1.6 million medically-attended flu cases were identified, of which 18,509 (1%) had a hospitalization. 40% of patients were < 18 years of age, 47% were male, and 28%, 15%, 24%, and 33% were identified in the 2014–2017 flu seasons, respectively. More hospitalized patients were ages 50+ compared with non-hospitalized patients (57% vs. 20%) and 44% of hospitalized patients had 4 or more AHRQ/CDC comorbidities vs. 8% of non-hospitalized patients. In adjusted analyses, older age (65+ vs. 5–17; OR = 9.4, 95% CI 8.8–10.1) and leukemia/lymphoma/metastatic cancer (OR = 3.2, 95% CI = 2.9–3.5) were key drivers of hospitalization (Figure 1).ConclusionThe risk of flu-related hospitalization is high for elderly populations and those with certain underlying co-morbidities among all age groups. While these findings reflect the burden of medically-attended flu in a younger, commercially insured population, additional research is needed to address the flu burden in high-risk populations. Disclosures All authors: No reported disclosures.

1775. A Community-wide Study to Evaluate the Accuracy of Self-testing for Influenza: Works in Progress

BackgroundSeasonal influenza (flu) occurs annually, causing disease with substantial morbidity and mortality. Currently, flu is suspected from clinical features, but requires a laboratory test to confirm infection. No influenza tests in the United States are approved for use outside of clinical settings. We aimed to determine the accuracy of influenza self-testing using an at-home, app-guided, lateral flow assay compared with a molecular reference standard conducted at a laboratory among adults self-reporting influenza-like illness (ILI).MethodsThis is an observational study of individuals with self-reported ILI throughout the continental 48 United States recruited from the Flu Near You platform, online marketing, and clinics in the Seattle area. Recruitment took place from March 4 to April 26, 2019. Participants were directed to an iPhone App that determined eligibility, consent, and responses to symptom questions and risk factors. Individuals were mailed a commercially available CLIA-waived influenza lateral flow test to conduct at home, guided by the app, and returned the used test along with a second nasal swab collected in viral transport media to the research team. Influenza testing was performed by RT–PCR on the second nasal swab, as well as the residual fluid from the RDT. Accuracy of home test result (read by the participant), as well as image capture of the lateral flow test strip, were compared with the lab-based reference standard.ResultsTo date, 1127 at-home flu tests were mailed to participants and 711 (63.1%) samples returned to the lab. There were 17 flu-positive results from the rapid diagnostic test for a flu positivity rate of 2.4%. Testing using the reference standard is currently in progress. We will share diagnostic accuracy results once testing of the reference standard is completed. Of the kits returned, 353 (49.7%)had an error recorded, which included errors in return packaging, reference standard, rapid test tube sample, or rapid test strip errors.ConclusionOverall, findings from this study will determine the accuracy of an at-home rapid diagnostic test, and inform more widely research design for evaluating smartphone-enhanced home tests for pathogens. Many samples returned to the lab had a recorded error, suggesting at-home testing requires additional feasibility testing and refinement of the current methods used.Disclosures All authors: No reported disclosures.

A sticking point for rapid flu tests?

Adoption of molecular tests for influenza has been slow — partly because of their high cost. Adoption of molecular tests for influenza has been slow — partly because of their high cost.

Leaving a Mobile Footprint: Utilizing Data to Combat the 2017 - 2018 Influenza Season

ObjectiveDuring this session, participants will be able to understand how Harris County Public Health utilized data to make informed decisions on how to combat the influenza season.IntroductionThe 2017 – 2018 influenza season was classified by the Centers for Disease Control and Prevention (CDC) as ‘high severity’ across all age groups. Furthermore, CDC noted that this was the first year to be categorized as such, with the highest peak percentage of influenza-like-illnesses (ILI), since 2009. In Harris County alone, there were 2,665 positive flu tests reported in comparison to the previous season at 1,395 positive tests. In response to the severity of this year’s flu season, Harris County Public Health (HCPH) collaborated across the department to deploy five pop up influenza vaccination events utilizing our Mobile Fleets open to the general public.HCPH epidemiologists are able to collect influenza data from multiple systems and compile it into useful reports/tools. These data include latitudinal and longitudinal data, allowing us to create highly localized maps of where influenza has had impacted communities the hardest. This granular data allowed HCPH to target 5 areas with our Mobile Fleet that had a) high levels of influenza and b) generally limited healthcare/public health infrastructure.Our Mobile Fleet is made up of 8 different Recreational Vehicles that have been retrofitted to offer various public health services including: immunizations, medical visits, dental visits, pet adoptions, mosquito and vector control education, and a fresh food market. The Fleet allows HCPH to offer a full menu of public health services anywhere within the County. While our efforts for this abstract were focused on controlling the influenza outbreak, we leveraged the opportunity to engage with the public on multiple issues such as environmental, veterinary, mosquito control, dental health, and accessible healthy food options.MethodsAs positive flu reports mounted, our epidemiology program provided surveillance data of influenza and ILI in Harris County. Data was obtained through multiple sources including: National Electronic Disease Surveillance System (NEDSS), which includes electronic laboratory reporting; National Respiratory Enteric Virus Surveillance System (NREVSS), which includes all flu tests done in laboratories in Houston; and last, the Flu Portal, which school nurses in Harris County upload school absenteeism rates due to ILI. Once collected and compiled, our Geographic Information System (GIS) team used the data to generate spatial maps of Harris County illustrating the disproportionally high rates. Specifically, our GIS team was able to utilize ArcGIS, and cross layer them with the flu data provided from the epidemiologists. Utilizing these maps, HCPH leadership mobilized the preparedness team to lead a data driven response in five different zip codes throughout the county to hold the influenza vaccination events.ResultsThe Mobile Fleet was operational on five separate dates in five separate zip codes during February and March of 2018. Overall, 477 individuals were provided the influenza vaccine. Of those 477, 304 were 18 years or older, with 173 being under 18 years of age.ConclusionsHaving timely and actionable data is an essential first step to understand and stop an outbreak of any size. However, surveillance data alone won't prevent an outbreak from spreading. That data must be married to effective public health action. Our Mobile Fleet is able to deliver precision public health services by targeting communities most affected and vulnerable to the spread of disease. As surveillance geospatial data becomes more granular so too must our public health service delivery modes become more precise and targeted.

Streamlined Development of Analytic Fusion Capability for Health Surveillance

Streamlined Development of Analytic Fusion Capability for Health Surveillance

2520. Epidemiology, Clinical Manifestations, and Outcomes of the 2017–2018 Influenza Season Among Hospitalized Patients at a Tertiary Care Center

Background2017–2018 Influenza season showed widespread activity and is expected to be of “high severity.”MethodsRetrospective chart review of patients with Influenza admitted from September 1, 2017 to April 1, 2018. Diagnosis was confirmed by Rapid flu test (RIDT) or Target Enriched Multiplex PCR (TEM PCR). Demographic, clinical, lab, treatment, and outcomes data were obtained. Analysis included prevalence and relative risk (RR)Results220 patients were identified (47% males, 73% White). Median age was 70 years (range 18–99). 65% had Flu A and 27% Flu B. 81% came from home, 17% from a facility (nursing home, assisted living). 49% had flu vaccination (Figure 1). Flu strain and vaccination status had no association RR 1.31 (95% CI 0.85–2.01, P = 0.21). Common comorbidities were lung disease 44%, obesity 41%, DM 36%, CAD 34%, CHF 31% (Figure 2). Common presentations were respiratory 79% and constitutional 53%. 68% were hypoxic and 4% hypotensive on arrival. 42% had new CXR/CT finding and 55% had pneumonia. Sensitivity of RIDT was 38%. 91% were treated with oseltamivir (21% within 48 hours of flu detection). Median treatment duration was 5 days. Hospitalizations peaked in January (Figure 3). Median length of hospital stay was 6 days. 23% had severe flu (needed NPPV 13%, intubation 12%, pressor 5%, ICU stay 16%) which showed significant association with arrival from facility RR 2.21 (95% CI 1.36–3.56, P = 0.001), lung disease RR 1.91 (95% CI 1.17–3.14, P = 0.01) and co-detection of respiratory pathogen (TEM PCR/sputum culture/serology) RR 2.65 (CI 1.60–4.38, P = 0.0001), but none with age >65 RR 1.46 (95% 0.83–2.56, P = 0.18), flu type RR 1.59 (95% CI 0.85–2.98, P = 0.14), active smoking RR 1.40 (95% CI 0.79–2.47, P = 0.24) or vaccination RR 1.21 (95% CI 0.70–2.12, P = 0.48). Fatality rate was 6% with significant association with arrival from facility RR 4.56 (95% CI 1.55–13.40, P = 0.006).Conclusion2017–2018 Influenza season among hospitalized patients involved more elderly and peaked in January. Sensitivity of flu swab was 38% calling for better utilization of TEM PCR in hospitalized patients. Severe flu had significant association with arrival from facility, lung disease and co-detection of respiratory pathogen. Fatality had significant association with arrival from facility. Confounders not accounted. Disclosures All authors: No reported disclosures.

Implementation of a Facility Based County Surveillance System Using Epi Info

ObjectiveThe Florida Department of Health in Hillsborough County (DOH-Hillsborough) routinely reviews the ESSENCE-FL system to assess syndromic trends in emergency department (ED) and urgent care data (UCC). Collection of this type of symptom data from long term care facilities (LTCFs) and child care centers is of interest in order to better understand how these illness patterns present in vulnerable populations outside of the EDs.IntroductionSurveillance in nursing homes (Enserink et al., 2011) and day care facilities (Enserink et al., 2012) has been conducted in the Netherlands, but is not commonly practiced in the United States (Buehler et al., 2008). Outbreaks of illnesses within these facilities are required to be reported to the Epidemiology Program, however a small fraction of outbreaks reported come from LTCFs. Without regular communication between LTCFs and the Epidemiology Program, it is likely that many outbreaks are going unreported due to lack of awareness of the reporting requirements by facility staff. To better understand the prevalence of illness in LTCFs and improve communication between LTCFs and DOH-Hillsborough a weekly surveillance survey was created using Epi Info web survey.MethodsThe online facility search tool from the Agency for Healthcare Administration (AHCA) was used to query assisted living facilities and nursing homes in Hillsborough County in July 2017. The information provided included the number of beds a facility is licensed to have. Interest in participation was solicited from larger LTCFs within the county in August 2017 and 23 facilities volunteered to receive weekly surveys, with a total volume of 3,276 beds. A form was created in Epi Info to capture weekly information per facility of the number of residents and staff with new onset of various symptoms. Symptom groups include GI, rash, respiratory, and those with respiratory symptoms who also have a fever (to assess influenza-like illness); number of positive flu tests for the week is also asked. Starting with week 38, an email has been sent once a week to participating facilities with a link to the Epi Info web survey (Figure 1) and instructions to fill out the information for the previous week.ResultsTo date, 12 weeks of information has successfully been captured in Epi Info and transferred to Microsoft Excel for graphical visualization of percentage of residents/staff reported each week in the county with new onset of the above symptoms. Low levels of illness (&lt;6%/week of total reported residents/staff) have been reported for various syndromes each week. Over the 12 week period an average of 3.9 facilities submit data per week, with a total of 10 of 23 facilities participating at least once. In week 42 phone calls were made to faclities that had not submitted any responses in an attempt to elicit more participation and troubleshoot any problems faclities may have encountered. Prior to week 42, an average of 3.2 facilties reported per week. After reminder phone calls were conducted, the average number of responses for weeks 42-48 was 4.4 with the highest in week 42 (6 responses). Starting in week 42 the survey has also been implemented for 15 child care facilities, with four participating over the seven weeks with an average of 2.1 responses per week.ConclusionsSince implementation, the main limitation with the data collection is lack of regular participation from facilities.The current goal of the project is to increase the number of regular responses from both LTCFs and child care facilities. The phone calls made in week 42 increased the response rate for LTCFs, particularly for that week. Preliminary results from the first 12 weeks of data indicate that using Epi Info web survey as a syndromic surveillance tool for local facilities has potential if regular participation can be acheived.ReferencesBuehler, J., Sonricker, A., Paladini, M., Soper, P., Mostashari, F. (2008), Syndromic Surveillance Practice in the United States: Findings from a Survey of State, Territorial, and Selected Local Health Departments. Advances in Disease Surveillance, 6:3.Enserink, R., Meijer, A., Dijkstra, F., van Benthem, B., van der Steen, J. T., Haenen, A., van Delden, H., Cools, H., van der Sande, M., Veldman-Ariesen, M.-J. and on behalf of the Sentinel Surveillance Network on Infectious Diseases in Nursing Homes Study Group (2011), Absence of Influenza A(H1N1) During Seasonal and Pandemic Seasons in a Sentinel Nursing Home Surveillance Network in the Netherlands. J Am Geriatr Soc, 59: 2301–2305. doi:10.1111/j.1532-5415.2011.03715.xEnserink, R., Noel, H., Friesema, I., de Jager, C., Kooistra-Smid, A., Kortbeek, L., Duizer, E., van der Sande, M., Smit, H., van Pelt, W. (2012), The KIzSS network, a sentinel surveillance system for infectious diseases in day care centers: study protocol. BMC Infectious Diseases, 12:259. doi:10.1186/1471-2334-12-259

Comparison of Cepheid® Xpert Flu and Roche RealTime Ready Influenza A/H1N1 Detection Set for detection of influenza A/H1N1

ObjectiveTo compare two influenza polymerase chain reaction (PCR) methods. MethodsA total of 749 suspected MERS-CoV patients presenting at Johns Hopkins Aramco Healthcare, Saudi Arabia, each submitted a clinical sample for influenza A reflex testing using the on-site Cepheid® Xpert Flu assay and at the Ministry of Health laboratory by the Roche PCR assay. ResultsThere was 92.12% overall agreement between the two methods. Specificity of the Cepheid® Xpert Flu was 95.8% for H1N1 and 94.4% for total influenza A. Cepheid® Xpert Flu sensitivity for influenza A was 100% for younger patients (0–19-year age group) but significantly lower both for older patients (68.2% for 60–79-year and 50% for ≥80-year age groups) and overall for males compared to females (72.6% and 94.0%, respectively). ConclusionsSpecificity of the Cepheid® Xpert Flu test was high; however, sensitivity for total influenza A was lower particularly in males and older patients.

Herpes Simplex Hepatitis in a Young, Healthy Female

Herpes simplex hepatitis (HSV) is a rarely encountered infectious hepatitis and is more commonly seen in immunocompromised and pregnant females. Prompt recognition and treatment is needed to prevent morbidity and mortality. Delays in treatment can be fatal. A 25 year old female presented to the ER with fevers and myalgias for the 3 days. A CBC and BMP were unremarkable. A pregnancy, monospot and rapid flu tests were negative. An abdomen CT reported hepatomegaly with steatosis. The patient was discharged from the ER. The patient returned 2 days later with worsening fevers. Repeat labs noted leukopenia with thrombocytopenia, and severe transaminitis (AST 1,810 U/L, ALT 1,224 U/L) with a normal total bilirubin, alkaline phosphatase, and lipase levels. INR was elevated. A toxicology screen, salicylate and acetaminophen levels were negative. Hepatitis A, B, and C tests were negative. Empiric IV acyclovir was started for suspected viral etiology. A RUQ ultrasound found possible cholecystitis, no gallstones, 0.9 cm common bile duct diameter, patency of the portal veins with normal venous waveforms, and a normal appearing liver. An MRCP followed and confirmed the findings on the ultrasound report. EBV testing revealed likely past exposure, but no acute infection. ANA screen was negative. HIV and Varicella PCR tests were negative. HSV I and II IgG antibodies were elevated. A PCR study was positive for HSV I. Gynecology noted ulcerated vaginal lesions consistent with HSV infection. Later, a liver biopsy was performed. The pathology review by Mayo Medical Laboratories reports centrilobular necrosis with areas of extension to portal tracts with every necrotic focus impinging on a central vein. Unlike typical drug-related zone 3 necrosis, the necroinflammatory process does not encircle central veins. The abnormal foci have apparent suppurative necrosis and loose collections of histiocytes suggestive of granuloma with the overall picture suggestive for an infectious process. No viral cytopathic inclusions were readily identified. Unfortunately no viral inclusions were seen on biopsy, but the patient had received 5 days of IV acyclovir prior. Based on the pathology report along with the positive PCR test and active vaginal lesions, the patient contracted HSV hepatitis. This case demonstrates a case of HSV hepatitis in an otherwise young, healthy female and the importance of early recognition and treatment with IV acyclovir.Figure: Centrilobular necrosis with central vein on the right and portal tract on the left.Figure: Centrilobular necrosis with inflammation and plasma cells.

The performance of Luminex ARIES® Flu A/B & RSV and Cepheid Xpert® Flu/RSV XC for the detection of influenza A, influenza B, and respiratory syncytial virus in prospective patient samples

BackgroundThe demand for rapid, accurate viral testing has increased the number of assays available for the detection of viral pathogens. One of the newest FDA cleared platforms is the Luminex ARIES® Flu A/B & RSV, which is a fully automated, real-time PCR-based assay used for detection of influenza A, influenza B, and respiratory syncytial virus (RSV). ObjectivesWe sought to compare the performance of Luminex ARIES® Flu A/B & RSV assay to the Cepheid Xpert® Flu/RSV XC assay for rapid Flu and RSV testing. Study designA series of consecutive nasopharyngeal specimens received in the clinical microbiology laboratory during peak influenza season at a major academic center in Chicago, IL, were prospectively tested, using both the ARIES® Flu A/B & RSV and Xpert® Flu/RSV XC assays, side by side. Discrepant results were tested on the BioFire FilmArray® Respiratory Panel for resolution. ResultsA total of 143 consecutive nasopharyngeal specimens, obtained from patients ranging from six months to ninety-three years in age were received between January 1st, 2017 and March 21st, 2017. There was 96.6% agreement between the two assays for detection influenza A, 100% agreement for detection influenza B and RSV, and 98.9% agreement for negative results. The Xpert® Flu/RSV XC performed with an average turn-around time of approximately 60min, compared to the ARIES® Flu A/B & RSV of approximately 120min. Both assays were equally easy to perform, with a similar amount of hands-on technologist time for each platform. ConclusionsOverall, these results indicate that both tests are comparable in terms of result agreement and technical ease-of-use. The Xpert® Flu/RSV XC assay did produce results with less turn-around-time, approximately 60min quicker than the ARIES® Flu A/B & RSV.