Obesity in Pregnancy
Bibliographic record
Abstract
OBJECTIVE: To review the evidence and provide recommendations for the counselling and management of obese parturients. OUTCOMES: OUTCOMES evaluated include the impact of maternal obesity on the provision of antenatal and intrapartum care, maternal morbidity and mortality, and perinatal morbidity and mortality. EVIDENCE: Literature was retrieved through searches of Statistics Canada, Medline, and The Cochrane Library on the impact of obesity in pregnancy on antepartum and intrapartum care, maternal morbidity and mortality, obstetrical anaesthesia, and perinatal morbidity and mortality. Results were restricted to systematic reviews, randomized controlled trials/controlled clinical trials, and observational studies. There were no date or language restrictions. Searches were updated on a regular basis and incorporated in the guideline to April 2009. Grey (unpublished) literature was identified through searching the websites of health technology assessment and health technology assessment-related agencies, clinical practice guideline collections, clinical trial registries, and national and international medical specialty societies. VALUES: The evidence obtained was reviewed and evaluated by the Maternal Fetal Medicine and Clinical Practice Obstetric Committees of the SOGC under the leadership of the principal authors, and recommendations were made according to guidelines developed by the Canadian Task Force on Preventive Health Care. BENEFITS, HARMS, AND COSTS: Implementation of the recommendations in this guideline should increase recognition of the issues clinicians need to be aware of when managing obese women in pregnancy, improve communication and consultation amongst the obstetrical care team, and encourage federal and provincial agencies to educate Canadians about the values of entering pregnancy with as healthy a weight as possible.
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 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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, 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".