Exploring Patient and Physician Perspectives on the Use of SGLT2 Inhibitors for Adjunct-to-Insulin Treatment in Patients Living with Type 1 Diabetes
Bibliographic record
Abstract
Background: Sodium-glucose co-transporter inhibitors (SGLTi) have proven cardiorenal benefits in type 2 diabetes and are promising as adjunct-to-insulin therapy in patients with type 1 diabetes (T1D). However, their regulatory approvals and clinical use in T1D have been limited owing to the augmented risk of diabetic ketoacidosis (DKA). Patient and physician input is critical in understanding how and when the risk-benefit ratio with these therapies is perceived to be favorable for users. This study aimed to explore how risks and benefits of SGLTi are considered by patients with T1D and physicians who treat the condition, particularly in the context of diabetic kidney disease (DKD). Methods: We used a qualitative descriptive study design, in which we conducted semi-structured interviews with T1D patients (with and without DKD) and physicians who treat this population. Participants were sampled from multiple Canadian sites via online recruitment. Transcripts were analysed inductively using conventional qualitative content analysis to identify themes. Results: We interviewed 22 patients with long-standing T1D including those with DKD, whose duration of living with diabetes ranged from 8-62 years. We also interviewed 7 physicians, including endocrinologists and nephrologists with a range of 4-20+ years in practice. Our analysis revealed four major themes: i) Strong motivation towards innovative treatments that can improve glycemia and yield cardiorenal benefits; ii) The need for a personalized approach when considering SGLTi initiation – as it was considered to be “not for everyone”; iii) Mitigating risk of DKA through proactive patient and prescriber-oriented strategies; and iv) Concern over absence of empirical evidence and regulatory approvals for this indication. Conclusion: While there is great interest and motivation toward the use of SGLTi among patients with T1D (both with and without DKD), and the physicians who treat them, there is also clear understanding by all, of the need for personalization of therapy and support for robust evidence to inform care. Funding: Government Support – Non-U.S.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".