- ICH GCP
- Registro degli studi clinici negli Stati Uniti
- Sperimentazione clinica NCT00884611
Development of Algorithms for a Hypoglycemic Prevention Alarm: Closed Loop Study
Development of Algorithms for a Hypoglycemic Prevention Alarm
This research study, Development of Algorithms for a Hypoglycemic Prevention Alarm, is being conducted at Stanford University Medical Center and the University of Colorado Barbara Davis Center. It is paid for by the Juvenile Diabetes Research Foundation.
The purpose of doing this research study is to understand the best way to stop an insulin infusion pump from delivering insulin to prevent a subject from having hypoglycemia. Nocturnal hypoglycemia is a common problem with type 1 diabetes. This is a pilot study to evaluate the safety of a system consisting of an insulin pump and continuous glucose monitor communicating wirelessly with a bedside computer running an algorithm that temporarily suspends insulin delivery when hypoglycemia is predicted in a home setting.
Panoramica dello studio
Stato
Condizioni
Descrizione dettagliata
After the run-in phase, there is a 21-night trial in which each night is randomly assigned 2:1 to have either the predictive low-glucose suspend (PLGS) system active (intervention night) or inactive (control night).
Three predictive algorithm versions were studied sequentially during the study.
Tipo di studio
Iscrizione (Effettivo)
Fase
- Non applicabile
Contatti e Sedi
Luoghi di studio
-
-
California
-
Stanford, California, Stati Uniti, 94305
- Stanford University School of Medicine
-
-
Colorado
-
Aurora, Colorado, Stati Uniti, 80045
- Barbara Davis Center for Childhood Diabetes, University of Colorado
-
-
Criteri di partecipazione
Criteri di ammissibilità
Età idonea allo studio
Accetta volontari sani
Sessi ammissibili allo studio
Descrizione
Inclusion Criteria:
- Age 18 years or older,
- Type 1 diabetes for at least 1 year
- Current user of the MiniMed Paradigm Real-Time Revel system and Sof-sensor glucose sensor
- Hemoglobin A1c level of < 8.0%,
- Home computer with access to the Internet,
- At least one CGMglucose value < 70 mg/dL during the most recent 15 nights of CGM glucose data.
- Not pregnant or planning to become pregnant
Exclusion Criteria:
The exclusion criteria for this study is the following:
- The presence of a significant medical disorder that in the judgment of the investigator will affect the wearing of the sensors or the completion of any aspect of the protocol
The presence of any of the following diseases:
- Asthma if treated with systemic or inhaled corticosteroids in the last 6 months
- Cystic fibrosis
- Angina (recurrent heart pain)
- Past heart attack or coronary artery (heart vessel) disease
- Past stroke or impairment of blood flow to the brain
- Other major illness that in the judgment of the investigator might interfere with the completion of the protocol Adequately treated thyroid disease and celiac disease do not exclude subjects from enrollment
- Inpatient psychiatric treatment in the past 6 months for either the subject or the subject's primary care giver (i.e., parent or guardian)
- Current use of oral/inhaled glucocorticoids or other medications, which in the judgment of the investigator would be a contraindication to participation in the study
- Severe hypoglycemic event, as described as a seizure, loss of consciousness, severe neurological impairment, or neurological impairment suggestive of hypoglycemia and requiring an emergency department visit or hospitalization within 18 months of enrollment.
Piano di studio
Come è strutturato lo studio?
Dettagli di progettazione
- Scopo principale: Trattamento
- Assegnazione: N / A
- Modello interventistico: Assegnazione di gruppo singolo
- Mascheramento: Nessuno (etichetta aperta)
Armi e interventi
Gruppo di partecipanti / Arm |
Intervento / Trattamento |
|---|---|
|
Sperimentale: Predictive Low Glucose Suspend
The pump suspension system consists of the Revel CGM device communicating with a laptop computer that contains the hypoglycemia prediction algorithm.
During the 21 night study period, the laptop is placed at the bedside and turned on by the participant at bedtime and off on arising in the morning.The laptop contains a randomization schedule (2:1) that indicats whether the hypoglycemia prediction algorithm will be in operation that night (Predictive Low Glucose Suspend Algorithm ON) or will not be activated (Predictive Low Glucose Suspend Algorithm OFF), to which the participant is blinded.
|
The algorithm uses a Kalman filter-based model to predict whether the sensor glucose level will fall below 80 mg/dL within a given time period and suspends the insulin pump if this event is predicted.
Altri nomi:
Altri nomi:
|
Cosa sta misurando lo studio?
Misure di risultato primarie
Misura del risultato |
Misura Descrizione |
Lasso di tempo |
|---|---|---|
|
Percentage of Nights With CGM (Continuous Glucose Monitor) Sensor Values < 60 mg/dL
Lasso di tempo: 21 days
|
Nights with CGM sensor values < 60 mg/dL were considered to be undesirable.
A Kalman filter-based model algorithm predicted whether the sensor glucose level would fall below 80 mg/dL and would suspend insulin delivery as needed.
Participants may have received treatment using one or more of the following algorithms: Algorithm 1 had a hypoglycaemic prediction horizon of 70 minutes; algorithm 2: 50 minutes; algorithm 3: 30 minutes.
|
21 days
|
Misure di risultato secondarie
Misura del risultato |
Misura Descrizione |
Lasso di tempo |
|---|---|---|
|
Percentage of Nights With CGM Values >180 mg/dL
Lasso di tempo: 21 days
|
Nights with CGM sensor values >180 mg/dL were considered to be undesirable.
Participants may have received treatment using one or more of the following algorithms: Algorithm 1 had a hypoglycaemic prediction horizon of 70 minutes; algorithm 2: 50 minutes; algorithm 3: 30 minutes.
|
21 days
|
|
Mean Morning Blood Glucose (BG)
Lasso di tempo: 21 days
|
Desirable glucose level was 70-180 mg/mL.
Average of all morning BG data is presented.
Participants may have received treatment using one or more of the following algorithms: Algorithm 1 had a hypoglycaemic prediction horizon of 70 minutes; algorithm 2: 50 minutes; algorithm 3: 30 minutes.
|
21 days
|
Collaboratori e investigatori
Sponsor
Collaboratori
Pubblicazioni e link utili
Studiare le date dei record
Studia le date principali
Inizio studio
Completamento primario (Effettivo)
Completamento dello studio (Effettivo)
Date di iscrizione allo studio
Primo inviato
Primo inviato che soddisfa i criteri di controllo qualità
Primo Inserito (Stima)
Aggiornamenti dei record di studio
Ultimo aggiornamento pubblicato (Effettivo)
Ultimo aggiornamento inviato che soddisfa i criteri QC
Ultimo verificato
Maggiori informazioni
Termini relativi a questo studio
Termini MeSH pertinenti aggiuntivi
Altri numeri di identificazione dello studio
- SU-10162008-1321
- Stanford eprotocol # 6789 (Altro identificatore: Stanford University)
Queste informazioni sono state recuperate direttamente dal sito web clinicaltrials.gov senza alcuna modifica. In caso di richieste di modifica, rimozione o aggiornamento dei dettagli dello studio, contattare register@clinicaltrials.gov. Non appena verrà implementata una modifica su clinicaltrials.gov, questa verrà aggiornata automaticamente anche sul nostro sito web .