Bibliographic record
Abstract
Recent upswings in the use of continuous glucose monitoring (CGM) technologies have given people with diabetes and healthcare professionals unprecedented access to a range of new indicators of glucose control. Some of these metrics are useful research tools and others have been welcomed by patient groups for providing insights into the quality of glucose control not captured by conventional laboratory testing. Among the latter, time in range (TIR) is an intuitive metric that denotes the proportion of time that a person’s glucose level is within a desired target range (usually 3.9–10.0 mmol/l [3.5–7.8 mmol/l in pregnancy]). For individuals choosing to use CGM technology, TIR is now often part of the expected conversation between patient and healthcare professional, and consensus recommendations have recently been produced to facilitate the adoption of standardised TIR targets. At a regulatory level, emerging evidence linking TIR to risk of complications may see TIR being more widely accepted as a valid endpoint in future clinical trials. However, given the skewed distribution of possible glucose values outside of the target range, TIR (on its own) is a poor indicator of the frequency or severity of hypoglycaemia. Here, the state-of-the-art linking TIR with complications risk in diabetes and the inverse association between TIR and HbA 1c are reviewed. Moreover, the importance of including the amount and severity of time below range (TBR) in any discussions around TIR and, by inference, time above range (TAR) is discussed. This review also summarises recent guidance in setting ‘time in ranges’ goals for individuals with diabetes who wish to make use of these metrics. For most people with type 1 or type 2 diabetes, a TIR >70%, a TBR <3.9 mmol/l of <4%, and a TBR <3.0 mmol/l of <1% are recommended targets, with less stringent targets for older or high-risk individuals and for those under 25 years of age. As always though, glycaemic targets should be individualised and rarely is that more applicable than in the personal use of CGM and the data it provides.
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.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".