Hypoglycemia: a review of definitions used in clinical trials evaluating antihyperglycemic drugs for diabetes
Bibliographic record
Abstract
OBJECTIVE: To understand the severity and potential impact of heterogeneity in definitions of hypoglycemia used in diabetes research, we aimed to review the hypoglycemia definitions adopted in randomized controlled trials (RCTs). METHODS: We reviewed 109 RCTs included in the Canadian Agency for Drugs and Technologies in Health reports for the second- and third-line therapy for the patients with type 2 diabetes (T2D). RESULTS: Nearly 60% (n=66) of the studies reviewed presented the definitions for overall hypoglycemia, and another 20% (n=22) of the studies reported the results for hypoglycemia but did not report a definition. Among these 66 studies, only 9 (14%) followed the American Diabetes Association/European Medicines Agency specified guidelines to define hypoglycemia, with an exact threshold of plasma glucose ≤3.9 mmol/L. Fifty-two of the 66 studies (79%) used a threshold considerably lower than the recommended ≤3.9 mmol/L, and 16 studies used a threshold between 3.8 and 4.0 mmol/L. The proportion of the trials that used a cutoff value of <3.1 mmol/L appeared to be slightly similar among the more commonly used non-insulin treatments, GLP-1s (7 of 18 [39%]), thiazolidinediones (TZDs; 6 of 11 [55%]), DPP-4s (12 of 19 [64%]), and sulfonylureas (11 of 20 [55%]). Among trials with intermediate-long-acting insulins (neutral protamine Hagedorn insulin, detemir, glargine), 7 of 26 trials (27%) used a cutoff of <3.1 mmol/L. The definition of severe hypoglycemia was also subject to substantial heterogeneity, in both the utilized threshold and accompanying soft definitions. CONCLUSION: This review demonstrates that substantial heterogeneity exists in the definition of overall, severe/major, and nocturnal hypoglycemia across RCTs investigating T2D interventions.
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 | 0.055 | 0.170 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.011 |
| Bibliometrics | 0.023 | 0.021 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| 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".