Consensus Report: The Current Role of Self-Monitoring of Blood Glucose in Non-Insulin-Treated Type 2 Diabetes
Bibliographic record
Abstract
The Coalition for Clinical Research--Self-Monitoring of Blood Glucose Scientific Board convened a meeting in San Francisco, CA, July 20-21, 2011, to discuss the current practice of self-monitoring of blood glucose (SMBG) in non-insulin-treated (NIT) type 2 diabetes mellitus (T2DM). Twelve physician panel members from academia, practice, and government attended this meeting. These experts came from the United States, Brazil, Canada, France, Germany, Italy, and the United Kingdom. In addition, three consultants from Australia, Germany, and the United States contributed to the group's final report. This coalition was organized by Diabetes Technology Society. Self-monitoring of blood glucose was studied from eight perspectives related to patients with NIT T2DM: (1) epidemiological studies; (2) randomized controlled trials (RCT)s and meta-analyses; (3) targets, timing, and frequency of SMBG use; (4) incidence and role of SMBG in preventing hypoglycemia with single-drug regimens and combination regimens consisting of antihyperglycemic agents other than secretagogues and insulin; (5) comparison of SMBG with continuous glucose monitoring; (6) technological capabilities and limitations of SMBG; (7) barriers to appropriate use of SMBG; and (8) methods and end points for appropriate future clinical trials. The panel emphasized recent studies, which reflect the current approach for applying this intervention. Among the participants there was consensus that: SMBG is an established practice for patients with NIT T2DM, and to be most effective, it should be performed in a structured format where information obtained from this measurement is used to guide treatment; New, high-quality efficacy data from RCTs have demonstrated efficacy of SMBG in NIT T2DM in trials reported since 2008; Both patients and health care professionals require education on how to respond to the data for SMBG to be effective; and Additional well-defined studies are needed to assess the benefits and costs of SMBG with end points not limited to hemoglobin A1c.
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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 | 0.125 | 0.190 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.011 | 0.007 |
| Research integrity | 0.020 | 0.024 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".