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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT04245800
Other study ID # STUDY00008861
Secondary ID
Status Completed
Phase
First received
Last updated
Start date December 13, 2019
Est. completion date July 6, 2020

Study information

Verified date July 2020
Source Evidation Health
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

The main goal of this research study is to use data from activity trackers (such as Fitbits), lab tests, and surveys to see if activity, sleep, and heart rate data can tell the difference between when someone has a respiratory illness (e.g., flu) and when they are feeling healthy. The research will also study an investigational flu@home test and app. If successful, results from the study could be used in the future to better identify people with respiratory illness. In addition, this study will test the accuracy of an at-home flu test kit compared to laboratory test results.


Description:

Background and Rationale

Acute respiratory infections (ARI) cause considerable disease burden globally and can affect both the upper and lower respiratory tract. A majority of ARI are caused by viruses, like the influenza virus, while bacteria are only implicated in approximately 10% of cases . The symptomology across various viral ARI are broadly similar, but two viruses, namely influenza and respiratory syncytial virus (RSV) are associated with considerable morbidity and mortality among adults and children. More immediate virus identification would improve patient health management by triaging appropriate and timely treatment and infection-control measures to mitigate health costs, additional health complications, and total days of symptom expression.

Despite viral infections causing the majority of ARIs, 61% of those with acute respiratory symptoms receive an antibiotic treatment. Due to the rise of antibiotic resistance, the inappropriate and over-prescription of antibiotics has become a severe health risk and is contributing to greater health complications and increased mortality rates. As a result, the correct diagnosis of the various infections associated with ARIs has become even more imperative to not cause undue harm. The abundance, accessibility, and rapidly advancing technology in wearable devices contributes to the progress some studies have demonstrated in using the devices as a potential mechanism to more rapidly identify various diseases. Though limited research has explored this new perspective specifically in illnesses associated with ARI, recent findings were able to demonstrate influenza signals at a population level using step, sleep, and heart rate data collected from consumer wearable devices.

Influenza virus is important to diagnose correctly because, despite annual vaccinations, it has been associated with higher morbidity and mortality than most other ARI viruses and has been associated with greater individual symptom severity. During the 2017-2018 flu season in the United States, it was estimated that 48.8 million people became sick with influenza, 959,000 were hospitalized, and there were 79,400 deaths recorded due to influenza. Additionally, more vulnerable populations, like young children, those experiencing chronic illness, and older adults, disproportionately represent the hospitalization and death totals reported. Older adults represented 70% of influenza related hospitalizations in the 2017-2018 flu season and 90% of influenza related deaths.

The rapid diagnosis of influenza is also of particular importance due to the effectiveness of influenza antiviral medication that is largely limited to initiation within 48 hours of symptom onset. Additionally, rapid diagnosis also has the potential to enact infection control measures to attenuate viral spread, particularly among vulnerable populations, using behavioral interventions or other non-pharmaceutical approaches. Diagnosis of influenza infection in centralized laboratories has largely progressed from traditional viral culture to the use of reverse transcription-polymerase chain reaction (RT-PCR) methods . Alternatively, influenza infection can be detected within a medical office or pharmacy using commercially-available rapid diagnostic tests (RDTs) of varying complexity, cost and accuracy.

There is now interest to expand RDTs to self-conducted tests that individuals can complete at home to further reduce the period between the onset of illness and effective treatment. Audere, a digital health non-profit, developed a mobile device app, the flu@home app, to guide individuals to perform an influenza RDT themselves without being in a clinical setting. The flu@home test uses a mixture of images and written directions prompted through the flu@home app to walk individuals through an influenza RDT process. The flu@home test also includes modified influenza RDT test material from an FDA 510(k) cleared RDT and includes an optional in-app automated influenza RDT test result interpretation system to eventually help inform health decisions and behaviors. Though no research has been published on the efficacy of the flu@home system, it has been implemented, and is being investigated, in two large prospective observational clinical studies during the 2019-2020 flu season, with collaborators at the University of Washington, Seattle and University of Adelaide, Australia.

Expanding on the previous research and development that has been done, the aim of this study is to develop a methodology to better classify and detect RVI cases, including influenza, through the use of behavioral data and patient-reported outcomes, using RVI confirmation through laboratory testing as a reference. This study also aims to assess the accuracy of the flu@home RDT self-test, the in-app automated RDT test result interpretation, and a data enhanced RDT test interpretation, compared to the interpretation provided by a trained professional RDT reader, the PCR test result, and a reference influenza test interpretations/analysis.

Device Description

The flu@home test kit is an at-home self-administered modified influenza RDT that is completed with the assistance of a mobile device app. The flu@home app feature was developed by Audere, a digital health non-profit based in Seattle. The flu@home test consists of the instructional app experience that guides participants through the influenza RDT procedure and the physical material of the RDT influenza test kit modified from the Quidel QuickVue Influenza A+B test. The flu@home app will solely be utilized as an instructional guide and research data collection tool for this study.

The flu@home test kit's instructional app features are available on iOS and Android platforms. The instructional app features include multiple pages of text and imagery content guiding participants through the entirety of the influenza RDT process, from completing a nasal swab to adding solution into a test tube to run a lateral flow immunoassay. The instructional app also includes an in-app questionnaire for participants to complete during a 10-minute participant wait period while their immunoassay processes. The flu@home test kit also guides participants through the viral collection and appropriate transport procedure of study samples for additional RVI analysis to be completed at an accredited laboratory.

The physical material of the flu@home test kit consists of components from an existing commercial influenza RDT, with additional material to collect and return a reference sample for laboratory testing. The complete flu@home test kit includes two foam-tipped nasal swabs, a small tube with dried reagent, a saline vial, a lateral-flow immunoassay test strip, and a tube with liquid reagent for the PCR test. RDT testing material is utilized from the CLIA-waived Quidel QuickVue Influenza A+B Test. All physical testing material will be assembled and mailed to participants through a 3rd party vendor, Molecular Testing Lab (MTL). The flu@home test kit also includes mailing material for participants to return the RDT test remnant and strip to be discarded by MTL and the reference nasal swab for laboratory testing through PCR procedures at MTL's accredited facility.

The flu@home test kit's interpretation features will not be shared with participants within the parameters of this study.

Regulatory Status

The flu@home test kit is considered a non-significant investigational device that is being used for data collection purposes and will be labeled as an investigational device. The test kit contains foam-tipped nasal swabs, a small tube with dried reagent, a saline vial and test strip from the CLIA-waived Quidel QuickVue Influenza A+B Test, and a tube with liquid reagent for the PCR test.

Explanation of choice comparator

PCR (RT-PCR for RNA viruses including influenza) is a reliable reference test for influenza and other respiratory viruses. RT-PCR was identified as the comparator for the modified at-home self-administered influenza RDT. Though RDTs can produce results in a much shorter period of time than RT-PCRs, RT-PCRs have been found to have more sensitivity to the influenza viruses than do RDTs. PCR or RT-PCR is often used as the reference test in research studies and studies designed for FDA submission (e.g., influenza RT-PCR was used as a reference test in the FDA 510(k) submission for the Quidel QuickVue Influenza A+B Test; Quidel, 2018).


Recruitment information / eligibility

Status Completed
Enrollment 5233
Est. completion date July 6, 2020
Est. primary completion date July 5, 2020
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria:

- Age 18 years or older

- Lives in the United States

- Speaks, reads, and understands English

- Owns a wearable Fitbit that collects heart rate data

- Willing to connect their Fitbit to the Achievement study platform and wear their Fitbit daily during the day and during sleep for the duration of the study

- Willing to respond to short daily questionnaires for a 4-month period

- Has an iOS or Android smartphone or tablet that is capable of supporting the Audere flu@home app

- Google Play Store compatible Android devices on Android 5.1 or later

- iOS devices on iOS 11 or later

- Willing to download the flu@home app

- Willing to complete an at-home flu test kit (via two nasal swabs) and return the nasal swab samples within 24 hours of being asked to complete a flu test kit

Exclusion Criteria:

- Diagnosed with flu by a healthcare professional in the past 3 months

- Currently enrolled in another flu study being conducted by Evidation Health/Achievement Studies

Study Design


Locations

Country Name City State
United States Evidation Health San Mateo California

Sponsors (4)

Lead Sponsor Collaborator
Evidation Health Audere, Biomedical Advanced Research and Development Authority, University of Washington

Country where clinical trial is conducted

United States, 

References & Publications (19)

Abu-Diab A, Azzeh M, Ghneim R, Ghneim R, Zoughbi M, Turkuman S, Rishmawi N, Issa AE, Siriani I, Dauodi R, Kattan R, Hindiyeh MY. Comparison between pernasal flocked swabs and nasopharyngeal aspirates for detection of common respiratory viruses in samples from children. J Clin Microbiol. 2008 Jul;46(7):2414-7. doi: 10.1128/JCM.00369-08. Epub 2008 May 14. — View Citation

Bradshaw B, Konty KJ, Ramirez E, et al. 2019. Influenza surveillance using wearable mobile health devices, Online J Public Health Inform, 11:e249

Burnham JP, Olsen MA, Kollef MH. Re-estimating annual deaths due to multidrug-resistant organism infections. Infect Control Hosp Epidemiol. 2019 Jan;40(1):112-113. doi: 10.1017/ice.2018.304. Epub 2018 Nov 22. — View Citation

Donnelly JP, Baddley JW, Wang HE. Antibiotic utilization for acute respiratory tract infections in U.S. emergency departments. Antimicrob Agents Chemother. 2014;58(3):1451-7. doi: 10.1128/AAC.02039-13. Epub 2013 Dec 16. — View Citation

Durkin MJ, Jafarzadeh SR, Hsueh K, Sallah YH, Munshi KD, Henderson RR, Fraser VJ. Outpatient Antibiotic Prescription Trends in the United States: A National Cohort Study. Infect Control Hosp Epidemiol. 2018 May;39(5):584-589. doi: 10.1017/ice.2018.26. Epub 2018 Feb 27. — View Citation

Dziabowska K, Czaczyk E, Nidzworski D. Detection Methods of Human and Animal Influenza Virus-Current Trends. Biosensors (Basel). 2018 Oct 18;8(4). pii: E94. doi: 10.3390/bios8040094. Review. — View Citation

Ebell MH, Afonso A. A systematic review of clinical decision rules for the diagnosis of influenza. Ann Fam Med. 2011 Jan-Feb;9(1):69-77. doi: 10.1370/afm.1192. Review. — View Citation

Ebell MH, Afonso AM, Gonzales R, Stein J, Genton B, Senn N. Development and validation of a clinical decision rule for the diagnosis of influenza. J Am Board Fam Med. 2012 Jan-Feb;25(1):55-62. doi: 10.3122/jabfm.2012.01.110161. — View Citation

Fendrick AM, Monto AS, Nightengale B, Sarnes M. The economic burden of non-influenza-related viral respiratory tract infection in the United States. Arch Intern Med. 2003 Feb 24;163(4):487-94. — View Citation

Kwon YS, Park SH, Kim MA, Kim HJ, Park JS, Lee MY, Lee CW, Dauti S, Choi WI. Risk of mortality associated with respiratory syncytial virus and influenza infection in adults. BMC Infect Dis. 2017 Dec 20;17(1):785. doi: 10.1186/s12879-017-2897-4. — View Citation

Larios OE, Coleman BL, Drews SJ, Mazzulli T, Borgundvaag B, Green K; STOP-Flu Study Group, McGeer AJ. Self-collected mid-turbinate swabs for the detection of respiratory viruses in adults with acute respiratory illnesses. PLoS One. 2011;6(6):e21335. doi: 10.1371/journal.pone.0021335. Epub 2011 Jun 23. — View Citation

Pope LE, Hobbs CG. Epistaxis: an update on current management. Postgrad Med J. 2005 May;81(955):309-14. Review. — View Citation

Ross MH, Zick BL, Tsalik EL. Host-Based Diagnostics for Acute Respiratory Infections. Clin Ther. 2019 Oct;41(10):1923-1938. doi: 10.1016/j.clinthera.2019.06.007. Epub 2019 Jul 26. Review. — View Citation

Shehab N, Lovegrove MC, Geller AI, Rose KO, Weidle NJ, Budnitz DS. US Emergency Department Visits for Outpatient Adverse Drug Events, 2013-2014. JAMA. 2016 Nov 22;316(20):2115-2125. doi: 10.1001/jama.2016.16201. — View Citation

Smith SM, Sonego S, Wallen GR, Waterer G, Cheng AC, Thompson P. Use of non-pharmaceutical interventions to reduce the transmission of influenza in adults: A systematic review. Respirology. 2015 Aug;20(6):896-903. doi: 10.1111/resp.12541. Epub 2015 Apr 14. Review. — View Citation

Uyeki TM, Bernstein HH, Bradley JS, Englund JA, File TM, Fry AM, Gravenstein S, Hayden FG, Harper SA, Hirshon JM, Ison MG, Johnston BL, Knight SL, McGeer A, Riley LE, Wolfe CR, Alexander PE, Pavia AT. Clinical Practice Guidelines by the Infectious Diseases Society of America: 2018 Update on Diagnosis, Treatment, Chemoprophylaxis, and Institutional Outbreak Management of Seasonal Influenzaa. Clin Infect Dis. 2019 Mar 5;68(6):895-902. doi: 10.1093/cid/ciy874. — View Citation

VanWormer JJ, Sundaram ME, Meece JK, Belongia EA. A cross-sectional analysis of symptom severity in adults with influenza and other acute respiratory illness in the outpatient setting. BMC Infect Dis. 2014 May 1;14:231. doi: 10.1186/1471-2334-14-231. — View Citation

Vos LM, Bruning AHL, Reitsma JB, Schuurman R, Riezebos-Brilman A, Hoepelman AIM, Oosterheert JJ. Rapid Molecular Tests for Influenza, Respiratory Syncytial Virus, and Other Respiratory Viruses: A Systematic Review of Diagnostic Accuracy and Clinical Impact Studies. Clin Infect Dis. 2019 Sep 13;69(7):1243-1253. doi: 10.1093/cid/ciz056. — View Citation

Walker TA, Khurana S, Tilden SJ. Viral respiratory infections. Pediatr Clin North Am. 1994 Dec;41(6):1365-81. Review. Erratum in: Pediatr Clin North Am 1995 Apr;42(4):xi. — View Citation

* Note: There are 19 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary Detection of RVI cases through the use of behavioral data and patient-reported outcomes Behavioral data from Fitbit wearables, patient self-reported data (includes but is not limited to demographics, symptoms, medical history, lifestyle, comorbidities, and Medical care utilization), and diagnostics during flu or RVI episode End of month 4 (when data collection concludes)
Primary Database development of Influenza and/or other RVI confirmations collected during the 2019-2020 flu season. Behavioral data from Fitbit wearables, patient self-reported data (includes but is not limited to demographics, symptoms, medical history, lifestyle, comorbidities, and Medical care utilization), and diagnostics during flu or RVI episode End of month 4 (when data collection concludes)
Primary Built, trained and tested analytical model for future real-time RVI surveillance systems Database comprised of behavioral data from Fitbit wearables, patient self-reported data (includes but is not limited to demographics, symptoms, medical history, lifestyle, comorbidities, and Medical care utilization), and diagnostics during flu or RVI episode End of month 4 (when data collection concludes)
Secondary Comparative accuracy of flu@home RDT Comparative accuracy of the flu@home RDT self-test, the in-app automated RDT test result interpretation, and a data enhanced RDT test interpretation, compared to the interpretation provided by a trained professional RDT reader, the PCR test result, and reference influenza test interpretations/analysis. End of month 4 (when data collection concludes)
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