Correlation Between Time in Range and HbA1c in People with Type 2 Diabetes on Basal Insulin: Post Hoc Analysis of the SWITCH PRO Study
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Bibliographic record
Abstract
Use of continuous glucose monitoring (CGM) in people with diabetes may provide a more complete picture of glycemic control than glycated hemoglobin (HbA1c) measurements, which do not capture day-to-day fluctuations in blood glucose levels. The randomized, crossover, phase IV SWITCH PRO study assessed time in range (TIR), derived from CGM, following treatment with insulin degludec or insulin glargine U100 in patients with type 2 diabetes at risk for hypoglycemia. This post hoc analysis evaluated the relationship between TIR and HbA1c, following treatment intensification during the SWITCH PRO study. Correlation between absolute values for TIR (assessed over 2-week intervals) and HbA1c, at baseline and at the end of maintenance period 1 (M1; week 18) or maintenance period 2 (M2; week 36), were assessed by linear regression and using the Spearman correlation coefficient ( r s ). These methods were also used to assess correlation between change in TIR and change in HbA1c from baseline to the end of M1, both in the full cohort and in subgroups stratified by baseline median HbA1c (≥ 7.5% [≥ 58.5 mmol/mol] or < 7.5% [< 58.5 mmol/mol]). A total of 419 participants were included in the analysis. A moderate inverse linear correlation was observed between TIR and HbA1c at baseline ( r s −0.54), becoming stronger following treatment intensification during maintenance periods M1 (weeks 17–18: r s −0.59) and M2 (weeks 35–36: r s −0.60). Changes in TIR and HbA1c from baseline to end of M1 were also linearly inversely correlated in the full cohort ( r s –0.40) and the subgroup with baseline HbA1c ≥ 7.5% ( r s −0.43). This was less apparent in the subgroup with baseline HbA1c < 7.5% ( r s −0.17) ( p -interaction = 0.07). Results from this post hoc analysis of data from SWITCH PRO, one of the first large interventional clinical studies to use TIR as the primary outcome, further support TIR as a valid clinical indicator of glycemic control. Trial registration: ClinicalTrials.gov identifier, NCT03687827.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it