- ICH GCP
- Yhdysvaltain kliinisten tutkimusten rekisteri
- Kliininen tutkimus NCT07507708
[Laitteen koe, jota Yhdysvaltain elintarvike- ja lääkevirasto (FDA) ei ole hyväksynyt tai hyväksynyt] (INSIGHT)
[Laitteen koe, jota Yhdysvaltain FDA ei ole hyväksynyt tai vahvistanut]
Tutkimuksen yleiskatsaus
Tila
Ehdot
Yksityiskohtainen kuvaus
The UVA AIDANET algorithm is intended for use by patients with T1D to control the subcutaneous infusion of insulin and aid in their T1D self-management. AIDANET automatically adjusts insulin delivery every 5 minutes in response to CGM values. AIDANET can be used with meal announcement (hybrid closed loop, HCL), without meal announcement (full closed loop, FCL), and with meal anticipation (anticipatory closed loop, ACL).
The purpose of this study is to demonstrate superior glycemic control when using anticipation within our latest Automated Insulin Delivery as Adaptive NETwork (AIDANET) in FCL with Anticipation (AIDANET+ACL) vs. AIDANET in FCL without Anticipation.
Opintotyyppi
Ilmoittautuminen (Arvioitu)
Vaihe
- Ei sovellettavissa
Yhteystiedot ja paikat
Opiskeluyhteys
- Nimi: Andrea Riana, MD
- Puhelinnumero: (434) 249-6251
- Sähköposti: rys6hm@uvahealth.org
Tutki yhteystietojen varmuuskopiointi
- Nimi: Laura Kollar, RN
- Puhelinnumero: (434) 982-6479
- Sähköposti: llk7m@uvahealth.org
Opiskelupaikat
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Virginia
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Charlottesville, Virginia, Yhdysvallat, 22903
- Rekrytointi
- University of Virginia Center for Diabetes Technology
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Alatutkija:
- Mark DeBoer, MD
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Alatutkija:
- Samina Afreen, MD
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Alatutkija:
- Marcela Moscoso-Vasquez, PhD
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Ottaa yhteyttä:
- Sue Brown, MD
- Puhelinnumero: 4349820602
- Sähköposti: sab2f@uvahealth.org
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Alatutkija:
- Driscoll Kimberly, PhD
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Osallistumiskriteerit
Kelpoisuusvaatimukset
Opintokelpoiset iät
- Aikuinen
- Vanhempi Aikuinen
Hyväksyy terveitä vapaaehtoisia
Kuvaus
Participant Inclusion Criteria
- Age ≥18.0 years old at time of consent
- Clinical diagnosis, based on investigator assessment, of T1D for > 1 year.
- Having used an FDA approved AID system within the last 6 months (can be intermittent use).
- Currently using insulin for >6 months.
- Willingness to switch to use an FDA-approved personal insulin for the study pump (e.g., lispro or aspart, or biosimilar FDA-approved products) as directed by the study team.
- Has one or more supportive companions knowledgeable about emergency procedures for severe hypoglycemia and able to contact emergency services and study staff who either lives with participant or located within approximately 30 minutes of participant and able to locate participant in the event of an emergency.
- Participant not currently known to be pregnant or breastfeeding.
- If participant can become pregnant, they must agree to use a form of contraception to prevent pregnancy while a participant in the study. A negative serum or urine pregnancy test will be required for all participants of childbearing potential. Participants who become pregnant will be discontinued from the study. Also, participants who during the study develop and express the intention to become pregnant within the timespan of the study will be discontinued.
- Willingness to wear a Dexcom CGM during each of the study phases.
- Willingness to use the study AIDANET system (CGM, pump, and phone) during the relevant study periods.
- Willingness not to start any new non-insulin glucose-lowering agent during the trial.
- Willingness to participate in all study procedures including in person training.
- Access to internet at home and willingness to upload data during the study as needed.
- Investigator has confidence that the participant can successfully operate all study devices and can adhere to the protocol.
- Participant is proficient in reading and verbal communication in English.
Participant Exclusion Criteria The participant must not have any exclusion criteria to be eligible to participate in the study.
- Plans to start a new non-insulin glucose-lowering agent (e.g., GLP-1 receptor agonists, Symlin, DPP-4 inhibitors,). Participants may be on a stable dose of such an agent for at least the past month.
- Current use of sulfonylurea medications.
- Uncontrolled microvascular complications such as active proliferative retinopathy not being treated or not responsive to current treatment.
- Current use of an SGLT-2 or SGLT-1/2 inhibitor due to risk of euglycemic DKA.
- Hemophilia or any other bleeding disorder.
- History of severe hypoglycemic events with seizure or loss of consciousness in the last 12 months.
- History of DKA event in the last 12 months.
- Currently on peritoneal or hemodialysis.
- Currently being treated for adrenal insufficiency.
- Currently being treated for a seizure disorder.
- Hypothyroidism or hyperthyroidism that is not adequately treated.
- Use of oral or injectable steroids at the time of enrollment.
- Known ongoing adhesive intolerance that is not well managed.
- A condition, which in the opinion of the investigator or designee, would put the participant or study at risk.
- Participation in another interventional trial at the time of enrollment.
- Participant with a direct supervisor at work/school who is involved in the conduct of the trial.
Opintosuunnitelma
Miten tutkimus on suunniteltu?
Suunnittelun yksityiskohdat
- Ensisijainen käyttötarkoitus: Hoito
- Jako: Satunnaistettu
- Inventiomalli: Crossover-tehtävä
- Naamiointi: Ei mitään (avoin tarra)
Aseet ja interventiot
Osallistujaryhmä / Arm |
Interventio / Hoito |
|---|---|
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Active Comparator: Group A: AID first followed by AIDANET+ACL then AIDANET+FCL
Participants will first complete 4 weeks of AID data collection which will be used to establish baseline and initialize the control algorithm.
Participants will then complete 4 weeks of AIDANET + Anticipatory Closed Loop (ACL) and 4 weeks of AIDANET + Fully Closed-Loop (FCL)
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Usual Care
All participants will use AIDANET in FCL mode with instructions to avoid announcing meal boluses whenever possible during the four weeks.
All insulin will be delivered automatically.
The algorithm will review past behaviors to determine the amount of insulin that will be needed for a meal.
|
|
Active Comparator: Group B: AID first followed by AIDANET+FCL then AIDANET+ACL
Participants will first complete 4 weeks of AID data collection which will be used to establish baseline and initialize the control algorithm.
Participants will then complete 4 weeks of AIDANET + Fully Closed Loop (FCL) and 4 weeks of AIDANET+ Anticipatory Closed Loop (ACL).
|
Usual Care
All participants will use AIDANET in FCL mode with instructions to avoid announcing meal boluses whenever possible during the four weeks.
All insulin will be delivered automatically.
The algorithm will review past behaviors to determine the amount of insulin that will be needed for a meal.
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Mitä tutkimuksessa mitataan?
Ensisijaiset tulostoimenpiteet
Tulosmittaus |
Toimenpiteen kuvaus |
Aikaikkuna |
|---|---|---|
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Time in range 70-140 mg/dL as computed by the study CGM
Aikaikkuna: 8 weeks
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Computed as the number of estimated glucose values ≥70mg/dL and <140mg/dL divided by the number of valid values (defined as a number between 39 and 401)
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8 weeks
|
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Time in range 70-140 mg/dL as computed by the study CGM
Aikaikkuna: 8 weeks
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Outcome is computed if:
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8 weeks
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Yhteistyökumppanit ja tutkijat
Sponsori
Yhteistyökumppanit
Tutkijat
- Päätutkija: Sue A Brown, MD, University of Virginia Center for Diabetes Technology
Opintojen ennätyspäivät
Opi tärkeimmät päivämäärät
Opiskelun aloitus (Todellinen)
Ensisijainen valmistuminen (Arvioitu)
Opintojen valmistuminen (Arvioitu)
Opintoihin ilmoittautumispäivät
Ensimmäinen lähetetty
Ensimmäinen toimitettu, joka täytti QC-kriteerit
Ensimmäinen Lähetetty (Todellinen)
Tutkimustietojen päivitykset
Viimeisin päivitys julkaistu (Todellinen)
Viimeisin lähetetty päivitys, joka täytti QC-kriteerit
Viimeksi vahvistettu
Lisää tietoa
Tähän tutkimukseen liittyvät termit
Avainsanat
Muita asiaankuuluvia MeSH-ehtoja
Muut tutkimustunnusnumerot
- 302996
- 5R01DK129553 (Yhdysvaltain NIH-apuraha/sopimus)
Lääke- ja laitetiedot, tutkimusasiakirjat
Tutkii yhdysvaltalaista FDA sääntelemää lääkevalmistetta
Tutkii yhdysvaltalaista FDA sääntelemää laitetuotetta
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