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Record W4323920834 · doi:10.1007/s13300-023-01389-2

Correlation Between Time in Range and HbA1c in People with Type 2 Diabetes on Basal Insulin: Post Hoc Analysis of the SWITCH PRO Study

2023· article· en· W4323920834 on OpenAlexaff
Ronald Goldenberg, Vanita R. Aroda, Liana K. Billings, Anders Meller Donatsky, Marie Frederiksen, David C. Klonoff, Balamurali Kalyanam, Richard M. Bergenstal

Bibliographic record

VenueDiabetes Therapy · 2023
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsLMC Diabetes & Endocrinology (Canada)
FundersNovo Nordisk
KeywordsMedicineBasal (medicine)Post-hoc analysisType 2 diabetesDiabetes mellitusBasal insulinInsulinPost hocInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.019
GPT teacher head0.281
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2023
Admission routes1
Has abstractyes

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