A retrospective multi-centre analysis investigating the effects of the rate of change in glucose on intermittently scanned continuous glucose monitoring (isCGM) system accuracy in people with type 1 diabetes

A retrospective multi-centre analysis investigating the effects of the rate of change in glucose on intermittently scanned continuous glucose monitoring (isCGM) system accuracy in people with type 1 diabetes - ROCI 1

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00024682

Enrollment

300

Registered

2021-08-30

Start date

2021-02-08

Completion date

Unknown

Last updated

2025-04-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

E10

Interventions

Group 1: Detection of the MARD due to the rate of change in comparison to the reference method

Eligibility

Sex/Gender

All

Age

18 Years to 65 Years

Inclusion criteria

Inclusion criteria: • Participants being clinically diagnosed with type 1 diabetes • Using an isCGM system against reference blood glucose measurement • Timepoints of measurements noted to assess the rate of change

Exclusion criteria

Exclusion criteria: • Any data that is missing in the inclusion criteria

Design outcomes

Primary

Measure	Time frame
To investigate the impact of the rate of change in sensor glucose on isCGM sensor accuracy assessed by Median/Mean Absolute Relative Difference (MARD)	—

Secondary

Measure	Time frame
• To investigate the impact of the rate of change in senor glucose on isCGM sensor accuracy assessed by Median/Mean Absolute Difference (MAD) • To investigate the impact of the rate of change in senor glucose on isCGM sensor accuracy assessed by Clarke Error Grid (CEG) analysis • To investigate the impact of the rate of change in senor glucose on isCGM sensor accuracy assessed by Bland Altman analysis • To investigate the impact of different glycaemic ranges in senor glucose on isCGM sensor accuracy assessed by MARD • To investigate the impact of different glycaemic ranges in senor glucose on isCGM sensor accuracy assessed by MAD • To investigate the impact of the rate of change in senor glucose on isCGM sensor accuracy stratified for glycaemic ranges assessed by MARD • To investigate the impact of the rate of change in senor glucose on isCGM sensor accuracy stratified for glycaemic ranges assessed by MAD	—

Measure

Time frame

• To investigate the impact of the rate of change in senor glucose on isCGM sensor accuracy assessed by Median/Mean Absolute Difference (MAD) • To investigate the impact of the rate of change in senor glucose on isCGM sensor accuracy assessed by Clarke Error Grid (CEG) analysis • To investigate the impact of the rate of change in senor glucose on isCGM sensor accuracy assessed by Bland Altman analysis • To investigate the impact of different glycaemic ranges in senor glucose on isCGM sensor accuracy assessed by MARD • To investigate the impact of different glycaemic ranges in senor glucose on isCGM sensor accuracy assessed by MAD • To investigate the impact of the rate of change in senor glucose on isCGM sensor accuracy stratified for glycaemic ranges assessed by MARD • To investigate the impact of the rate of change in senor glucose on isCGM sensor accuracy stratified for glycaemic ranges assessed by MAD

—

Countries

Austria, Canada, France, Germany, Italy, Norway, Poland

Contacts

Public ContactOthmar Moser

Universität BayreuthInstitut für SportwissenschaftenDivision of Exercise Physiology and Metabolism

othmar.moser@uni-bayreuth.de+49092155346

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026