The endogenous oxytocin after manipulative osteopathic treatment in full-term pregnant women.
Bibliographic record
Abstract
OBJECTIVE: The aim of this study is to assess whether the touch of osteopathic manipulative treatment (OMT) can affect the endogenous production of oxytocin in full-term pregnant women and the assessment of well-being following the treatment. PATIENTS AND METHODS: In this study have been enrolled 57 pregnant women at full-term pregnancy (37th-41st week) for evaluation of the concentration of salivary oxytocin 2 minutes before and 2 minutes after a single session of OMT by an osteopath lasting for 30 minutes. Pre-OMT and post-OMT saliva samples were collected with the use of Salivette® salivary swabs. 7 salivary swabs were excluded from the analysis. 50 samples were analyzed with an appropriate ELISA kit. RESULTS: The mean OT salivary concentration pre-OMT was 89.98±16.39, and post-OMT was 100.60±19.13 tends to increase with p=0.0000051. In multivariate analysis, two subgroups show interesting data in the mean difference in OT salivary concentration post-OMT: women with painful contractions (p=0.06) and women under 35 years (p=0.09). CONCLUSIONS: The results of this study demonstrate that the effectiveness of OMT-increasing endogenous oxytocin is statistically significant in full-term pregnant women. The sensation of well-being found in most women indicates that there has been a predominantly central rather than peripheral oxytocin release after OMT.
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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 | 0.001 |
| 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".