Twice-Daily vs 4-Times-Daily Glucose Testing in Women With Gestational Diabetes Mellitus: A Pilot Study
Bibliographic record
Abstract
OBJECTIVES: In women with gestational diabetes mellitus (GDM), glycemic control is typically assessed by capillary blood glucose (BG) self-monitoring. Currently, the standard method of monitoring is by 4-times-daily self-measurements. The goal of our study was to determine whether twice-daily capillary BG testing is comparable with 4-times-daily testing in women with GDM. METHODS: Thirty-two women with GDM completed initial dietary counselling and recorded consecutive fasting and 2-h postprandial BG over a 14-day period. We randomly selected 2 of 4 BG measurements on each given day and compared mean (95% confidence interval [CI]) twice-daily vs 4-times-daily BG measurements using paired t tests and Bland-Altman plots. The proportion of 14-day BG measurements above glycemic targets was also compared between twice-daily vs 4-times-daily testing for fasting and postprandial readings. RESULTS: Comparing twice-daily vs 4-times-daily mean BG, there was a small difference for fasting BG (0.09 mmol/L; 95% CI, 0.03 to 0.14), but not for 2-h postbreakfast (-0.05 mmol/L; 95% CI, -0.17 to 0.06), 2-h postlunch (-0.03 mmol/L; 95% CI, -0.13 to 0.08) or 2-h postdinner (0.05 mmol/L; 95% CI, -0.09 to 0.19) BG. Bland-Altman plots showed general agreement and minimal bias between twice-daily vs 4-times-daily BG, whether fasting or postprandial. There was no significant difference in the proportion of 14-day BG measurements above glycemic targets comparing twice-daily vs 4-times-daily testing in the fasting or postprandial states. CONCLUSIONS: Twice-daily BG testing appears to generate 14-day average values similar to 4-times-daily BG testing. In women with GDM, whose BG is in target range, twice-daily BG monitoring may reduce inconvenience and cost.
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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".