Bibliographic record
Abstract
We read Dr Kelly and colleagues’ article1 along with Dr Harris’s editorial2 with great interest and considered it prudent to present data from a recent meta-analysis conducted by the Motherisk Program at the Hospital for Sick Children in Toronto, Ont. Our data, presented at the 2005 annual meeting of the Canadian Society for Clinical Pharmacology, are encouraging with respect to the safety of metformin use in the first trimester of pregnancy. In performing a meta-analytic summary, which included eight studies (only five of which could be analyzed statistically), we found an odds ratio of 0.50. Examining the numbers showed three malformed babies among the 172 cases in the exposed group. There were 17 among 236 in the control group. Examining all the data available on pregnancy outcomes (including those not included in the meta-analysis due to lack of controls), we arrived at an overall malformation rate of 1.01% in 496 first-trimester exposures, which is well within what we would expect to find in the general population. Our results also present the possibility of a protective effect of metformin during the first trimester. It is biologically possible that, by reversing insulin resistance, metformin does protect against malformation. Although our data are encouraging, it is important to note that we examined only major malformations. This being said, our study does encourage future research into the safety of metformin during the first trimester of pregnancy.
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 | 0.005 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.018 | 0.015 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".