Practical steps to improving the management of type 1 diabetes: recommendations from the Global Partnership for Effective Diabetes Management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Diabetes Control and Complications Trial (DCCT) led to considerable improvements in the management of type 1 diabetes, with the wider adoption of intensive insulin therapy to reduce the risk of complications. However, a large gap between evidence and practice remains, as recently shown by the Pittsburgh Epidemiology of Diabetes Complications (EDC) study, in which 30-year rates of microvascular complications in the 'real world' EDC patients were twice that of DCCT patients who received intensive insulin therapy. This gap may be attributed to the many challenges that patients and practitioners face in the day-to-day management of the disease. These barriers include reaching glycaemic goals, overcoming the reality and fear of hypoglycaemia, and appropriate insulin therapy and dose adjustment. As practitioners, the question remains: how do we help patients with type 1 diabetes manage glycaemia while overcoming barriers? In this article, the Global Partnership for Effective Diabetes Management provides practical recommendations to help improve the care of patients with type 1 diabetes.
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.
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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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