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Net changes in non-insulin medication class count stratified by cohort <t>and</t> <t>RT-CGM</t> use or CGM non-use. “Addition” and “Reduction” categories indicate a net increase or decrease in medications at follow-up compared to baseline. “No Change” indicates the same medication classes were used at baseline and follow-up. “Net Zero Change” indicates the same number of medication classes were added as removed at follow-up compared to baseline. Cohorts are presented as ( A ) T2D-NIT, ( B ) T2D-BIT, and ( C ) T2D-IIT.
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Net changes in non-insulin medication class count stratified by cohort and RT-CGM use or CGM non-use. “Addition” and “Reduction” categories indicate a net increase or decrease in medications at follow-up compared to baseline. “No Change” indicates the same medication classes were used at baseline and follow-up. “Net Zero Change” indicates the same number of medication classes were added as removed at follow-up compared to baseline. Cohorts are presented as ( A ) T2D-NIT, ( B ) T2D-BIT, and ( C ) T2D-IIT.

Journal: Diabetes, Metabolic Syndrome and Obesity

Article Title: Impact of Real-Time Continuous Glucose Monitoring on Medication Use and Glycemic Control in Type 2 Diabetes Across Therapy Regimens

doi: 10.2147/DMSO.S574769

Figure Lengend Snippet: Net changes in non-insulin medication class count stratified by cohort and RT-CGM use or CGM non-use. “Addition” and “Reduction” categories indicate a net increase or decrease in medications at follow-up compared to baseline. “No Change” indicates the same medication classes were used at baseline and follow-up. “Net Zero Change” indicates the same number of medication classes were added as removed at follow-up compared to baseline. Cohorts are presented as ( A ) T2D-NIT, ( B ) T2D-BIT, and ( C ) T2D-IIT.

Article Snippet: Each cohort contained two groups: Dexcom RT-CGM users or CGM non-users and 1:1 propensity score matching was performed to minimize differences between the groups.

Techniques: Medications

Proportion of each cohort achieving A1c targets stratified by RT-CGM use or CGM non-use. ( A ) Proportion of NIT cohort achieving A1c goals at follow-up, ( B ) Proportion of BIT cohort achieving A1c goals at follow-up, ( C ) Proportion of IIT cohort achieving A1c goals at follow-up, ( D and E ) Proportion of each cohort with a baseline A1c above the indicated target meeting the target at follow-up. **, p<0.001; ***, p<0.0001.

Journal: Diabetes, Metabolic Syndrome and Obesity

Article Title: Impact of Real-Time Continuous Glucose Monitoring on Medication Use and Glycemic Control in Type 2 Diabetes Across Therapy Regimens

doi: 10.2147/DMSO.S574769

Figure Lengend Snippet: Proportion of each cohort achieving A1c targets stratified by RT-CGM use or CGM non-use. ( A ) Proportion of NIT cohort achieving A1c goals at follow-up, ( B ) Proportion of BIT cohort achieving A1c goals at follow-up, ( C ) Proportion of IIT cohort achieving A1c goals at follow-up, ( D and E ) Proportion of each cohort with a baseline A1c above the indicated target meeting the target at follow-up. **, p<0.001; ***, p<0.0001.

Article Snippet: Each cohort contained two groups: Dexcom RT-CGM users or CGM non-users and 1:1 propensity score matching was performed to minimize differences between the groups.

Techniques: