Validation Study of a Peri-intervention Diabetes Management Algorithm (DIAPI) for Endoscopy Procedures

Centre hospitalier de l'Université de Montréal (CHUM)

Status: Completed

Conditions: Diabetes Mellitus

Treatments: Other: Peri-intervention Diabetes Management Algorithm (DIAPI); Other: Usual Care

Study type: Interventional

Funder types: Other

Identifiers

NCT05849714

2023-11359

Details and patient eligibility

About

The peri-endoscopy management of diabetes mellitus creates significant challenges for both patients and healthcare professionals. These procedures require fasting and in certain situations, such as prior to a colonoscopy, the diet must be modified the day before the intervention and patients need to take a laxative. These factors put patients at high risk for hyperglycemia and hypoglycemia. Inadequate diabetes control or the continuation of certain medications during this period can be dangerous for the patient and lead to the cancellation of the procedure.

DIAPI is a web application designed to generate orders for optimal and personalized treatment based on each patient's antidiabetic treatment, their glycemic control, their risk of hypoglycemia, and the intervention-related variables. DIAPI's algorithm is established on current evidence-based data when available, and experts' opinions.

Information generated by DIAPI:

• For the patient: Clear instructions regarding their diabetes medication management for the days preceding and the day of the endoscopy.

• For the health care team:

  • Clear instructions regarding patient's diabetes medication management for the days preceding and the day of the endoscopy;
  • Individualized hyperglycemia protocol;
  • Hypoglycemia protocol;
  • Guidelines if SGLT2 inhibitors have not been discontinued pre-intervention;
  • Suggestion on whether an Endocrinology consultation is needed.

DIAPI aims to simplify the complex task of peri-intervention diabetes management while ensuring patient safety. It is a cost-effective solution that can lead to a reduction of unnecessary Endocrinology consultations, a decrease in nurses' workload, a lessening of the risk of errors and a diminution of endoscopy cancellation.

The validation study is divided into two main phases.

• Phase 1 - Concordance. The investigators will assess the reproducibility of DIAPI orders when two different healthcare workers (an endocrinologist and a nurse) collect data for the same patient. The investigators hypothesize that DIAPI orders are concordant in 80%. Patients in this phase will be subjected to the mainstay management, which is using the treating-physician's recommendations instead of DIAPI's. This group will be the control arm for the non-inferiority study (Phase 2).
• Phase 2 - Non-inferiority study. The investigators hypothesize that DIAPI's orders are not inferior to the recommendations issued by the treating-physician in terms of efficacy and security. Patients in this phase will be subjected DIAPI's orders. This group will be the intervention arm for the non-inferiority study.

Enrollment: 173 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Living with diabetes mellitus for at least 6 months
• Receiving pharmacological treatment for diabetes mellitus
• Awaiting an endoscopy intervention scheduled in 2 weeks or more in order to have time to prepare for the study participation

Exclusion criteria

• Undergoing an urgent endoscopy intervention
• Being pregnant
• Currently treated with an insulin pump or the insulin Entuzity

Trial design

Primary purpose: Treatment

Allocation: Non-Randomized

Interventional model: Sequential Assignment

Masking: None (Open label)

---

173 participants in 2 patient groups

Usual Care

Active Comparator group

Description:

Patients will receive usual care for their diabetes during their peri-procedural period.

Treatment:

Other: Usual Care

DIAPI

Experimental group

Description:

Patients will receive the care for their diabetes recommended by the DIAPI algorithm during their peri-procedural period.

Treatment:

Other: Peri-intervention Diabetes Management Algorithm (DIAPI)