Success Rates in a Diabetes Specialist Nurse-Led Education Programme: Re-setting the Glucostat
Bibliographic record
Abstract
Analysis of National Diabetes Audit data from 2011-2012 of newly diagnosed people with type 1 diabetes mellitus (DM) found low initial success rates in much of the UK at 20% on initial training, while an unusually high success rate of 75% achieving target HbA1C<58 mmol/mol (< 7.5%) was found in Cheshire (England average=40.8%). We present a review of the approach taken by the Cheshire Diabetes team in the 12 months following diagnosis. Between 2012 and 2013, 15 consecutive newly diagnosed people with type 1 DM were followed up for 18 months. All received support and advice by community Diabetes Specialist Nurses (DSNs) and Dieticians covering Central and Eastern Cheshire, UK. Mean±SD age at diagnosis was 23±3 years. The period of contact with the DSN service varied from 7-12 weeks. Baseline HbA1C of 99 mmol/mol [11.2%] (95% CI: 86-111 mmol/mol [10.0-12.3%]) declined by ~50% to 49 mmol/mol [6.6%] (41-57 mmol/mol [5.9-7.4%]; F=16.9, p<0.001) at 6 months and did not change between 6-12 months. Of those newly diagnosed with type 1 DM, 84.6% achieved a target HbA1C<58 mmol/mol (<7.5%) and 61.5% met a target<48 mmol/mol (<6.5%). There was no significant weight change during the study. The key elements of this bio-psycho-social approach by the DSN team included providing psychological support, patient engagement, demonstrating positive regard, gaining trust, identifying health-seeking behaviour, providing key decision-making skills and developing a self-management plan. This resulted in improvements in overall glycaemic control well above the national average without untoward weight gain. The UK National Diabetes Audit (2011-2012) in newly diagnosed type 1 diabetics in Cheshire, UK, showed a success rate at 6 months post-diagnosis of 75% achieving a target HbA1C<58 mmol/mol (<7.5%) compared with the national average of 40.8%. Initially thought to be erroneous, these excellent results were confirmed. The approach taken to achieve them is herein described.
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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 | 0.020 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".