Evaluation of the effects of ice massage applied to large intestine 4 (hegu) on postpartum pain during the active phase of labor.
Bibliographic record
Abstract
BACKGROUND: The uterus continues to contract after childbirth. The pain caused by the contractions of the uterus can be as severe as labor pain. The study was aimed to evaluate the effects of ice massage applied to the large intestine 4 (LI4) on postpartum pain during the active phase of labor. MATERIALS AND METHODS: The study was designed as a randomized controlled trial with three groups and carried out in two stages. The study sample comprised of 150 pregnant women, who were referred to a maternity hospital. In the experimental group, ice massage was applied to LI4 during four contractions within the active phase of labor. In the placebo group, pressure was applied to LI4 using silicone balloons and the third group was the control group. The Visual Analog Scale (VAS) and The McGill (Melzack) Pain Questionnaire (MPQ) were compared among the experimental, placebo, and control groups. RESULTS: The mothers in the ice application group had the lowest mean VAS score. It was determined that ice massage applied to LI4 during the active phase of labor did not lead to any statistical differences in mothers in the first 24 hours postpartum in terms of the characteristics of the pain with MPQ and VAS. CONCLUSIONS: In the study, the perception of pain was tried to be minimized by applying pressure with ice balloons to LI4. However, although the application was determined to have made no difference in the pain intensity, the mothers' statements in the ice application group suggested that they felt more comfortable than did the mothers in the other groups.
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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 | 0.001 |
| 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) | 0.001 | 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".