Effect of Spinal Manipulation on Pelvic Floor Functional Changes in Pregnant and Nonpregnant Women: A Preliminary Study
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to investigate whether a single session of spinal manipulation of pregnant women can alter pelvic floor muscle function as measured using ultrasonographic imaging. METHODS: In this preliminary, prospective, comparative study, transperineal ultrasonographic imaging was used to assess pelvic floor anatomy and function in 11 primigravid women in their second trimester recruited via notice boards at obstetric caregivers, pregnancy keep-fit classes, and word of mouth and 15 nulliparous women recruited from a convenience sample of female students at the New Zealand College of Chiropractic. Following bladder voiding, 3-/4-dimensional transperineal ultrasonography was performed on all participants in the supine position. Levator hiatal area measurements at rest, on maximal pelvic floor contraction, and during maximum Valsalva maneuver were collected before and after either spinal manipulation or a control intervention. RESULTS: Levator hiatal area at rest increased significantly (P < .05) after spinal manipulation in the pregnant women, with no change postmanipulation in the nonpregnant women at rest or in any of the other measured parameters. CONCLUSION: Spinal manipulation of pregnant women in their second trimester increased the levator hiatal area at rest and thus appears to relax the pelvic floor muscles. This did not occur in the nonpregnant control participants, suggesting that it may be pregnancy related.
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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 | 0.001 | 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".