New Zealand’s slow uptake of carbohydrate-reduction in type 2 diabetes management
Bibliographic record
Abstract
Type 2 diabetes (T2DM) is a condition that involves insulin resistance and a reduced ability to control blood glucose.Science and logic indicate that reducing the very nutrient that raises blood sugar, ie carbohydrate, would be worth consideration, yet it's been overlooked for many years.Global dietary guidelines have been updated to align with scientific evidence.The American Diabetes Association (ADA), The British Diabetes and Dietetic Associations, Diabetes Canada and Diabetes Australia have included carbohydrate reduction (CR) in their official T2DM dietary guidelines. 1,2An ADA 2019 consensus report concluded: 'reducing overall carbohydrate intake for individuals with diabetes has demonstrated the most evidence for improving glycemia and may be applied in a variety of eating patterns that meet individual needs and preferences'.This report was included in the 2020 ADA Standards of Medical Care in Diabetes update. 3Diabetes Australia states: 'For people with type 2 diabetes, there is reliable evidence that lower carb eating can be safe and useful in lowering average blood glucose levels in the short term (up to 6 months).It can also help reduce body weight and help manage heart disease risk factors such as raised cholesterol and raised blood pressure.' 4 New Zealand (NZ) does not endorse CR as a viable option for individuals, but rather cautions against it.The NZ Society for the Study of Diabetes states in their guidelines 'meta-analyses show that the benefits of ketogenic diets are unlikely to be sustained'. 5,6 and the Ministry of Health states 'Very low carbohydrate diets: Not recommended'. 5 This is surprising, as clinical trials and primary care practice data report beneficial and sustained results from CR. 7,8 Virta Health, a US-based research entity has shown CR to be safe in prediabetes/T2DM.Their 5-year data concluded their model of care showed excellent retention, sustained clinically significant weight loss, stable glycaemic control and less dependency on diabetes medication. 9British general practitioner, Dr David Unwin used CR to reverse/remit T2DM; of 199 patients with T2DM, 46% achieved drug-free remission, with enormous cost savings from reduced diabetes medication. 10 In view of the rapid growth of evidence around CR and T2DM, and the global guideline adoption, we simply ask why NZ is not at least including a CR approach in its guidelines, alongside other dietary approaches, to manage T2DM.We now call upon NZ to catch up and follow suit.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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; a candidate call from one teacher head, 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".