Effect of short‐term intensive insulin therapy on quality of life in type 2 diabetes
Bibliographic record
Abstract
RATIONALE, AIMS AND OBJECTIVES: Short-term intensive insulin therapy (IIT) early in the course of type 2 diabetes can improve pancreatic beta-cell function and even induce normoglycemia that persists post-therapy. In spite of this benefit, insulin is often delayed until late in the course of disease partly because of its perceived negative impact on quality of life (QOL). Therefore, we sought to examine the effect of early implementation of short-term IIT on patient-reported QOL and treatment satisfaction. METHODS: A total of 34 patients with type 2 diabetes (5.9 ± 6.6 years duration, on zero to two oral antihyperglycaemic agents) underwent 4-8 weeks of IIT consisting of basal detemir and pre-meal insulin aspart. Patient-reported QOL, treatment satisfaction and symptom distress were assessed at baseline and post-IIT using the Medical Outcomes Study 36-item Short-Form Health Survey (SF-36), Diabetes Quality of Life Measure (DQOL), and Diabetes Symptoms Checklist-Revised (DSC-R). RESULTS: There was a significant improvement in glycated haemoglobin post-IIT (mean 6.5% vs. 7%; P < 0.001). All 34 patients tolerated IIT well with no severe hypoglycaemia. Following IIT, the SF-36 showed a significant improvement compared to baseline in reported physical functioning (mean 88.2 vs. 83.3, P = 0.009), general health (69.4 vs. 65.6, P = 0.03), and general mental health (85.2 vs. 82.2, P = 0.04). The DQOL demonstrated a significant improvement in global health perception (P = 0.02), diabetes worry (P = 0.006) and treatment satisfaction (P = 0.007). The DSC-R revealed a significant improvement in the diabetes-related total symptom score (P = 0.01). CONCLUSIONS: Contrary to popular perception, a short course of IIT resulted in significant improvements in QOL and treatment satisfaction, demonstrating the patient acceptability of early insulin therapy.
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How this classification was reachedexpand
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 | 0.035 | 0.192 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".