The Relationship between Metformin and Obstructive Sleep Apnea.
Bibliographic record
Abstract
OBJECTIVES: This study aimed to assess if metformin had any associations with the prevalence of obstructive sleep apnea in an adult type 2 diabetes population in the Midwest. HYPOTHESIS: Use of metformin is associated with decreased prevalence of obstructive sleep apnea in a adult type 2 diabetes population. METHODS: A retrospective secondary database analysis was carried out with metformin use by patients with type 2 diabetes as the primary variable of interest and obstructive sleep apnea status as the primary outcome. A sample population of 9,853 type 2 diabetes patients with one year of follow-up was used. Other variables that were analyzed included age, gender, race, hypertension, Congestive Heart Failure, Hemoglobin A1c (HbA1c), and Body Mass Index. A p-value of <0.01 was considered significant. RESULTS: Metformin usage was not significantly associated with obstructive sleep apnea prevalence (Odds Ratio: 1.17, Confidence Interval: 1.00-1.36, p = 0.049), but trended in the direction where metformin usage was associated with having obstructive sleep apnea. Lower HbA1c was found to be significantly associated with lower prevalence of obstructive sleep apnea (p <0.001). The rest of the variables followed previously published associations. CONCLUSIONS: Metformin therapy may improve sleep quality, but it may not be through methods that reduce the likelihood of developing obstructive sleep apnea. Future studies that can prove causation about this association should be considered.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".