Peripartum care of persons with obesity: a scoping review of recommendations and practical tools for implementation
Bibliographic record
Abstract
Objective: Despite the growing prevalence of obesity among reproductive aged persons in the USA, evidence-based guidelines for peripartum care are lacking. The objective of this scoping review is to identify obesity-related recommendations for peripartum care, evaluate grades of evidence for each recommendation, and identify practical tools (eg, checklists, toolkits, care pathways and bundles) to support their implementation in clinical practice. Data sources: We searched MEDLINE, EMBASE, CINAHL, the Cochrane Central Register of Controlled Trials and ClinicalTrials.gov from inception to December 2020 for eligible studies addressing peripartum care in persons with obesity. Study eligibility criteria: Inclusion criteria were published evidence-rated recommendations and practical tools for peripartum care of persons with obesity. Study appraisal and synthesis methods: Pairs of independent reviewers extracted data (source, publication year, content and number of recommendations, level and grade of evidence, description of tool) and identified similarities and differences among the articles. Results: Of 18,315 screened articles, 18 were included including 7 articles with evidence-rated recommendations and 11 practical tools (3 checklists, 3 guidelines, 1 care bundle, 1 flowchart, 1 care pathway, 1 care map and 1 protocol). Thirteen of 39 evidence-rated recommendations were based on expert opinion. Recommendations related to surgical antibiotic prophylaxis and subcutaneous tissue closure at caesarean delivery received the highest grade of evidence. Some of the practical tools included a checklist from the USA regarding anticoagulation after caesarean delivery (evidence-supported recommendation), a bundle for surgical site infections after caesarean delivery in Australia (evidence did not support recommendation) and a checklist with content for several aspects of peripartum care from Canada (evidence supported seven of nine definitive recommendations). Conclusion: The recommendations for peripartum care for persons with obesity are based on limited evidence and few practical tools for implementation exist. Future work should focus on developing practical tools based on high-quality studies.
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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 | 0.112 | 0.326 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.025 | 0.018 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".