MetaboNet: The Largest Publicly Available Consolidated Data Set for Type 1 Diabetes Management

Abstract

Background:

Progress in type 1 diabetes (T1D) algorithm development is limited by the fragmentation and lack of standardization across existing T1D management data sets. Current data sets differ substantially in structure and are time-consuming to access and process, which impedes data integration and reduces the comparability and generalizability of algorithmic developments. This work aims to establish a unified and accessible data resource for T1D algorithm development.

Method:

Multiple publicly available T1D data sets were harmonized into a unified resource, termed the MetaboNet data set. Inclusion required the availability of both continuous glucose monitoring (CGM) data and corresponding insulin pump dosing records. In addition, auxiliary information such as reported carbohydrate intake and physical activity was retained when present.

Results:

The MetaboNet data set comprises 3135 subjects and 1228 patient-years of overlapping CGM and insulin data, making it substantially larger than existing standalone benchmark data sets. The resource is distributed as a fully public subset available for immediate download at https://metabo-net.org/, and with a data use agreement (DUA)-restricted subset accessible through their respective application processes. For the data sets in the latter subset, processing pipelines are provided to automatically convert the data into the standardized MetaboNet format.

Conclusions:

A harmonized public data set for T1D research is presented, and the access pathways for both its unrestricted and DUA-governed components are described. The resulting data set covers a broad range of glycemic profiles and demographics and thus can yield more generalizable algorithmic performance than individual data sets.