Efficacy of Osteopathic Manipulative Treatment for Management of Postpartum Pain
Bibliographic record
Abstract
CONTEXT: Pain is one of the most common postpartum complaints by women in the United States, and the pain varies in its location. Research on intervention strategies for postpartum pain has focused primarily on the lower back, but pain management for other types of postpartum pain remains unclear. OBJECTIVE: To investigate the effects of osteopathic manipulative treatment (OMT) on postpartum pain; the location, quality, and timing of pain; and the difference in pain between vaginal and cesarean delivery. METHODS: Postpartum patients who reported having pain were recruited at St Barnabas Hospital in Bronx, New York. The short-form McGill Pain Questionnaire was administered along with a screening questionnaire. Second- or third-year residents in neuromusculoskeletal medicine and osteopathic manipulative medicine examined patients and then diagnosed and managed somatic dysfunction with OMT for approximately 25 minutes. The short-form McGill Pain Questionnaire was again administered after OMT. Paired t tests and McNemar tests were used to analyze changes before and after OMT for continuous and categorical variables, respectively. Differences in visual analog scale (VAS) pain scores between patients who had vaginal vs cesarean delivery were tested using analysis of variance, and group differences in pain location were tested using a Pearson χ2 test. RESULTS: A total of 59 patients were included in the study. The mean VAS score for pain was 5.0 before OMT and 2.9 after OMT (P<.001). The VAS scores before OMT significantly differed between patients who had a vaginal delivery and those who had a cesarean delivery (P<.001), but the mean decrease in VAS score was similar in both groups. Decreases in low back pain (34 [57.6%] before and 16 [27.1%] after OMT), abdominal pain (32 [54.2%] before and 22 [37.3%] after OMT), and vaginal pain (11 [18.6%] before and 5 [8.5%] after OMT) were reported after OMT (P<.05). CONCLUSION: Preliminary results demonstrate that OMT is efficacious for postpartum pain management. The lack of a control group precludes the ability to make causal claims. Future studies are needed to solidify OMT efficacy and generalizability.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".