Individualisation of glycaemic management in older people with type 2 diabetes: a systematic review of clinical practice guidelines recommendations
Bibliographic record
Abstract
BACKGROUND: Recommendations for individualised glycaemic management in older people with type 2 diabetes (T2D) have recently been provided in clinical practice guidelines (CPGs) issued by major scientific societies. The aim of this systematic review is to compare the content of these recommendations concerning health assessment, targets for glycaemic control, lifestyle management and glucose-lowering therapy across CPGs. METHODS: The CPGs on T2D management in people aged ≥65 years published in English after 2015 by major scientific societies were systematically reviewed in accordance with the PRISMA statement. The quality of the CPGs included was assessed using the AGREE-II tool. The recommendations for individualised glycaemic management were extracted, and their level of evidence (LOE) and strength of recommendation recorded. RESULTS: Three CPGs of high methodological quality were included, namely those from the American Diabetes Association 2020, the Endocrine Society 2019 and the Diabetes Canada Expert Committee 2018. They made 27 recommendations addressing individualised glycaemic management, a minority of which (40%) had a high LOE. Comparison of the 27 recommendations identified some discrepancies between CPGs, e.g. the individualised values of HbA1c targets. The 13 strong recommendations addressed 10 clinical messages, five of which are recommended in all three CPGs, i.e. assess health status, screen for cognitive impairment, avoid hypoglycaemia, prioritise drugs with low hypoglycaemic effects and simplify complex drug regimens. CONCLUSIONS: Although there is a consensus on avoiding hypoglycaemia in older patients with T2D, significant discrepancies regarding individualised HbA1c targets exist between CPGs.
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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 | 0.055 | 0.220 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.015 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".