Trends in Time in Range–Related Publications and Clinical Trials: A Bibliometric Review
Bibliographic record
Abstract
Objective: The goal of this article was to describe trends in publications (including conference abstracts) and clinical trials that report on glycemic time in range (TIR). Data sources: Reviewed databases included but were not limited to MEDLINE and Embase. Clinical trial registries were also sourced. Study selection: All studies reporting TIR published between 2010 and 2021 were included. Clinical trials reporting TIR that started in or after 2010 were also included. Non-English publications, abstracts, and clinical trials were excluded. Book chapters, nonhuman studies, and studies not reporting TIR were excluded. Data extraction: Manuscript/abstract category, publication year, study region, interventional versus observational role of continuous glucose monitoring (CGM), and clinical trial start and completion dates were captured. Glycemic outcomes reported in publications or trials, including TIR as a primary outcome, A1C, time below range (TBR), and time above range (TAR), were also captured. Results: A total of 373 clinical trials, 531 publications, and 620 abstracts were included in the review. The number of trials, publications, and abstracts reporting TIR significantly increased, particularly between 2018 and 2021, during which time the number of clinical trials, publications, and conference abstracts reporting TIR increased by 6-fold, 12-fold, and 4.5-fold, respectively. About 35-44% of studies reported TIR as a primary outcome. Approximately 54% of clinical trials, 47% of publications, and 47% of conference abstracts reported the role of CGM to be observational. TBR was reported more often than TAR. Conclusion: The marked increase in the number of trials, publications, and abstracts reporting TIR highlights the increasing significance and acceptance of TIR as an outcome measure in diabetes management.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.063 | 0.259 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.201 | 0.266 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".