Racial Differences in Pelvic Anatomy by Magnetic Resonance Imaging
Bibliographic record
Abstract
OBJECTIVES: To use static and dynamic magnetic resonance imaging (MRI) to compare dimensions of the bony pelvis and soft tissue structures in a sample of African-American and white women. METHODS: This study used data from 234 participants in the Childbirth and Pelvic Symptoms Imaging Study, a cohort study of 104 primiparous women with an obstetric anal sphincter tear, 94 who delivered vaginally without a recognized anal sphincter tear and 36 who underwent by cesarean delivery without labor. Race was self-reported. At 6-12 months postpartum, rapid acquisition T2-weighted pelvic MRIs were obtained. Bony and soft tissue dimensions were measured and compared between white and African-American participants using analysis of variance, while controlling for delivery type and age. RESULTS: The pelvic inlet was wider among 178 white women than 56 African-American women (10.7+/-0.7 cm compared with 10.0.+0.7 cm, P<.001). The outlet was also wider (mean intertuberous diameter 12.3+/-1.0 cm compared with 11.8+/-0.9 cm, P<.001). There were no significant differences between racial groups in interspinous diameter, angle of the subpubic arch, anteroposterior conjugate, levator thickness, or levator hiatus. In addition, among women who delivered vaginally without a sphincter tear, African-American women had more pelvic floor mobility than white women. This difference was not observed among women who had sustained an obstetric sphincter tear. CONCLUSION: White women have a wider pelvic inlet, wider outlet, and shallower anteroposterior outlet than African-American women. In addition, after vaginal delivery, white women demonstrate less pelvic floor mobility. These differences may contribute to observed racial differences in obstetric outcomes and to the development of pelvic floor disorders.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".