Influenza -Like IllnessNCT04245800
Home Testing of Respiratory Illness
An observational study of Influenza -Like Illness and Influenza A, run by Evidation Health at 1 site in United States.
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. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Influenza -Like Illness, Influenza A, Influenza Type B
- Type of treatment
- Vaccines
- How many people
- 5,233 participants
- Where
- 1 siteUnited States
- Study dates
- 13 Dec 2019to 6 Jul 2020
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Adults living in the US
Who may be able to join
- 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
Show all 11Show fewer
- 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
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Behavioral Patterns and Patient Self-completed Diagnostic Testing Study of Respiratory Viral Infection "Home Testing of Respiratory Illness"
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.
Read the detailed 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).
- Conditions
- Influenza -Like Illness, Influenza A, Influenza Type B, Respiratory Viral Infection, Respiratory Tract Infections
- Keywords
- Influenza, self-testing, diagnostic accuracy
- Medical subject headings
- Respiratory Tract Infections, Influenza, Human
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Observational | All participants will be part of the prospective observational cohort. If participants develop flu-like symptoms, they will be prompted to complete the flu@home self-test kit. Analysis will be conducted for various subgroups (e.g. age, vaccination status) |
What is being measured
The primary outcome is the main question the study is designed to answer.
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
Measured: End of month 4 (when data collection concludes)
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
Measured: End of month 4 (when data collection concludes)
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
Measured: End of month 4 (when data collection concludes)
Secondary outcomes (1)
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.
Measured: End of month 4 (when data collection concludes)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Jan 2020
- Study start13 Dec 2019
- Primary completion5 Jul 2020
- Study completion6 Jul 2020
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (20)Papers the sponsor has linked to this study.
- Other trials for Influenza -Like IllnessStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 5,233 participants (actual)
Sponsor and investigators
- Lead sponsor
- Evidation Health
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Audere, University of Washington, Biomedical Advanced Research and Development Authority
- Responsible party
- Principal investigator, Jessie Juusola, Evidation Health
- Investigators
- Matthew J Thompson, DPhil, Study director, University of WashingtonJessie L Juusola, PhD, Principal investigator, Evidation HealthErnesto Ramirez, PhD, Study director, Evidation HealthBarry Lutz, PhD, Study director, University of Washinton
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04245800
- Sponsor's protocol ID
- STUDY00008861
- Status last verified
- Jul 2020
- First submitted
- 27 Jan 2020
- Last updated
- 22 Jul 2020
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Coded Study Data may also be transferred to external research partners in accordance with IRB approved uses. Coded Study Data consists of all data collected within the parameters of this study, excluding any identifying information. After completion of the study, any potentially identifiable information will be removed and Coded Study Data will be made available to qualified researchers using the Synapse Platform run by Sage Bionetworks, a US-based non-profit focused on furthering scientific knowledge.
Publications
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.
PubMed 18480225Bradshaw 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. No abstract available.
PubMed 30463634Donnelly 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.
PubMed 24342652Durkin 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.
PubMed 29485018Dziabowska K, Czaczyk E, Nidzworski D. Detection Methods of Human and Animal Influenza Virus-Current Trends. Biosensors (Basel). 2018 Oct 18;8(4):94. doi: 10.3390/bios8040094.
PubMed 30340339Ebell 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.
PubMed 21242564Ebell 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.
PubMed 22218625Fendrick 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. doi: 10.1001/archinte.163.4.487.
PubMed 12588210Kwon 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.
PubMed 29262784Larios 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.
PubMed 21731708Pope LE, Hobbs CG. Epistaxis: an update on current management. Postgrad Med J. 2005 May;81(955):309-14. doi: 10.1136/pgmj.2004.025007.
PubMed 15879044Ross 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.
PubMed 31353133Shehab 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.
PubMed 27893129Smith 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.
PubMed 25873071
Study at a glance
From the registry record, last updated by the sponsor on 22 Jul 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Behavioral Patterns and Patient Self-completed Diagnostic Testing Study of Respiratory Viral Infection "Home Testing of Respiratory Illness"
- ClinicalTrials.gov ID
- NCT04245800
- Acronym / sponsor ID
- STUDY00008861
- Conditions
- Influenza -Like Illness, Influenza A, Influenza Type B, Respiratory Viral Infection, Respiratory Tract Infections
- Keywords
- Influenza, self-testing, diagnostic accuracy
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 5,233 participants (actual)
- Lead sponsor
- Evidation HealthIndustry (pharma, biotech, devices)
- Collaborators
- Audere, University of Washington, Biomedical Advanced Research and Development Authority
- Study start
- 13 Dec 2019 (actual)
- Primary completion
- 5 Jul 2020 (actual)
- Study completion
- 6 Jul 2020 (actual)
- First posted
- 29 Jan 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed 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).
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Observational | – | –All participants will be part of the prospective observational cohort. If participants develop flu-like symptoms, they will be prompted to complete the flu@home self-test kit. Analysis will be conducted for various subgroups (e.g. age, vaccination status) |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Adults living in the US
Key inclusion criteria (11 listed)
- 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
Key exclusion criteria (2 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Detection of RVI cases through the use of behavioral data and patient-reported outcomes
Time frame: End of month 4 (when data collection concludes)
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
Database development of Influenza and/or other RVI confirmations collected during the 2019-2020 flu season.
Time frame: End of month 4 (when data collection concludes)
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
Built, trained and tested analytical model for future real-time RVI surveillance systems
Time frame: End of month 4 (when data collection concludes)
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
1 secondary outcome
Comparative accuracy of flu@home RDT
Time frame: End of month 4 (when data collection concludes)
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 22 Jul 2020.
- Background: PubMed 18480225Abu-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.
- BackgroundBradshaw B, Konty KJ, Ramirez E, et al. 2019. Influenza surveillance using wearable mobile health devices, Online J Public Health Inform, 11:e249
- Background: PubMed 30463634Burnham 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. No abstract available.
- Background: PubMed 24342652Donnelly 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.
- Background: PubMed 29485018Durkin 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.
- Background: PubMed 30340339Dziabowska K, Czaczyk E, Nidzworski D. Detection Methods of Human and Animal Influenza Virus-Current Trends. Biosensors (Basel). 2018 Oct 18;8(4):94. doi: 10.3390/bios8040094.
- Background: PubMed 21242564Ebell 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.
- Background: PubMed 22218625Ebell 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.
- Background: PubMed 12588210Fendrick 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. doi: 10.1001/archinte.163.4.487.
- Background: PubMed 29262784Kwon 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.
- Background: PubMed 21731708Larios 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.
- Background: PubMed 15879044Pope LE, Hobbs CG. Epistaxis: an update on current management. Postgrad Med J. 2005 May;81(955):309-14. doi: 10.1136/pgmj.2004.025007.
- CLIA Waiver for Quidel QuickVue Influenza A + B Test. (Part of flu@home kit)Link provided by the sponsor.
- Individual participant dataSharing planned: Yes. Coded Study Data may also be transferred to external research partners in accordance with IRB approved uses. Coded Study Data consists of all data collected within the parameters of this study, excluding any identifying information. After completion of the study, any potentially identifiable information will be removed and Coded Study Data will be made available to qualified researchers using the Synapse Platform run by Sage Bionetworks, a US-based non-profit focused on furthering scientific knowledge.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Matthew J Thompson, DPhil study director
University of Washington
Jessie L Juusola, PhD principal investigator
Evidation Health
Ernesto Ramirez, PhD study director
Evidation Health
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Influenza -Like Illness and Influenza A, run by Evidation Health at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 11 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 22 Jul 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Detection of RVI cases through the use of behavioral data and patient-reported outcomes (time frame: End of month 4 (when data collection concludes)). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04245800, which also lists 20 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 22 Jul 2020.