Obstetrician and Gynecologist’s Perspectives on the Definition and Management of Obesity in Pregnancy
Bibliographic record
Abstract
Introduction: Obesity is a complex disease affecting increasing numbers of reproductive aged women. Despite ongoing research efforts, many knowledge gaps remain when caring for women with obesity in pregnancy. Currently, there is no clearly defined, comprehensive standard of care for pregnant women with obesity. Consequently, obstetricians and gynecologists (OBGYNs) have developed different approaches. In this study, how the management of women with obesity differs from that of normal weight patients was explored. Another aim was to gain a better understanding of how OBGYNs define obesity, as there is currently no consensus definition. Methods: A mixed methods approach was used. Qualitative concept maps were generated through individual in-depth mapping sessions with seven OBGYNs and analyzed thematically. Major themes informed survey development. The resultant survey was distributed to OBs in Edmonton (n=58). Responses were entered into a Research Electronic Data Capture Database (REDCap) and descriptive statistics performed. Finally, semi-structured interviews with residents in obstetrics and gynecology were conducted until saturation about the current working definition and ideal definition of obesity in pregnancy. Ethics approval was obtained. Results/Conclusions: Obstetrics and Gynecology residents and staff physicians relied on varying subjective measures to classify patients as having obesity or not. They defined and appreciated risk secondary to obesity at different Body Mass Index (BMI) points. While they found it useful, BMI was not routinely used and on its own was felt to be insufficient to define obesity. Clinicians prefer a definition of obesity that incorporates a more comprehensive picture of patient health and wellbeing. This could include medical comorbidities and specific barriers to care that may provide insight into weight distribution. Establishing a consensus definition and classification of obesity in pregnancy would allow for more standardized care plans to be developed. Limited professional education opportunities, lack of specific counseling tools, time constraints, and negative bias toward women with obesity in pregnancy all act as barriers to providing evidence-based care to women with obesity. Education strategies addressing these barriers will help empower obstetrical care providers to become champions of weight management in the future. Current guidelines do not address many of the areas physicians identify as challenging and important in the care of women with obesity in pregnancy. Revision of national guidelines should incorporate those areas OBGYNs deem most crucial to providing high level care.
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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 | 0.019 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".