Use of a decision support tool and quick start onboarding tool in individuals with type 1 diabetes using advanced automated insulin delivery: a single-arm multi-phase intervention study.
Background: Multiple clinician adjustable parameters impact upon glycemia in people with type 1 diabetes (T1D) using Medtronic Mini Med 780G (MM780G) AHCL. These include glucose targets, carbohydrate ratios (CR), and active insulin time (AIT). Algorithm-based decision support advising upon potential...
| Publicado en: | BMC Endocrine Disorders Vol. 24; no. 1; pp. 1 - 12 |
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| Autores principales: | , , , , , , , , , , , , , , |
| Formato: | clinical trial research tables/charts Journal Article |
| Publicado: |
BioMed Central
8/30/2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=179358407&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 179358407 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14726823 1CHL jtl: BMC Endocrine Disorders issn: 14726823 maglogo: N pubinfo: dt: 8/30/2024 vid: 24 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 179358407 179358407 179358407 10.1186/s12902-024-01709-y 179358407 ppf: 1 ppct: 11 formats: tig: atl: Use of a decision support tool and quick start onboarding tool in individuals with type 1 diabetes using advanced automated insulin delivery: a single-arm multi-phase intervention study. aug: au: Sehgal, Shekhar De Bock, Martin Grosman, Benyamin Williman, Jonathan Kurtz, Natalie Guzman, Vanessa Benedetti, Andrea Roy, Anirban Turksoy, Kamuran Juarez, Magaly Jones, Shirley Frewen, Carla Watson, Antony Taylor, Barry Wheeler, Benjamin J. affil: https://ror.org/01jmxt844 Department of Women's and Children's Health, Dunedin School of Medicine, University of Otago, 201 Great King St, 9016, Dunedin, Otago, New Zealand sug: subj: Automation Insulin Therapeutic Use Diabetes Mellitus, Type 1 Drug Therapy Drug Efficacy Patient Safety Decision Support Systems, Clinical Insulin Infusion Systems Experimental Studies Human Exploratory Research Diabetic Patients Algorithms Time Factors Carbohydrates Analysis Health Personnel Collaboration Insulin Administration and Dosage Body Weight Adult Glycated Hemoglobin Analysis Descriptive Statistics Decision Making Funding Source Clinical Trials Adult: 19-44 years ab: Background: Multiple clinician adjustable parameters impact upon glycemia in people with type 1 diabetes (T1D) using Medtronic Mini Med 780G (MM780G) AHCL. These include glucose targets, carbohydrate ratios (CR), and active insulin time (AIT). Algorithm-based decision support advising upon potential settings adjustments may enhance clinical decision-making. Methods: Single-arm, two-phase exploratory study developing decision support to commence and sustain AHCL. Participants commenced investigational MM780G, then 8 weeks Phase 1-initial optimization tool evaluation, involving algorithm-based decision support with weekly AIT and CR recommendations. Clinicians approved or rejected CR and AIT recommendations based on perceived safety per protocol. Co-design resulted in a refined algorithm evaluated in a further identically configured Phase 2. Phase 2 participants also transitioned to commercial MM780G following "Quick Start" (algorithm-derived tool determining initial AHCL settings using daily insulin dose and weight). We assessed efficacy, safety, and acceptability of decision support using glycemic metrics, and the proportion of accepted CR and AIT settings per phase. Results: Fifty three participants commenced Phase 1 (mean age 24.4; Hba1c 61.5mmol/7.7%). The proportion of CR and AIT accepted by clinicians increased between Phases 1 and 2 respectively: CR 89.2% vs. 98.6%, p < 0.01; AIT 95.2% vs. 99.3%, p < 0.01. Between Phases, mean glucose percentage time < 3.9mmol (< 70mg/dl) reduced (2.1% vs. 1.4%, p = 0.04); change in mean TIR 3.9-10mmol/L (70-180mg/dl) was not statistically significant: 72.9% ± 7.8 and 73.5% ± 8.6. Quick start resulted in stable TIR, and glycemic metrics compared to international guidelines. Conclusion: The co-designed decision support tools were able to deliver safe and effective therapy. They can potentially reduce the burden of diabetes management related decision making for both health care practitioners and patients. Trial registration: Prospectively registered with Australia/New Zealand Clinical Trials Registry(ANZCTR) on 30th March 2021 as study ACTRN12621000360819. pubtype: Academic Journal doctype: clinical trial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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