The characteristics of labor pain during the active phase of primipara
Bibliographic record
Abstract
Understanding on the characteristics of labor pain during the first stage of primipara is the first consideration of healthcare providers for pregnant women. The aim of this study was to describe the demographic characteristics and the characteristic of signs and symptoms of labor pain. One hundred and six subjects (pregnant women) were recruited from labor room, Khon Kaen Hospital. Each of them was evaluated all importance variables such as severity of labor pain (using Visual Analog Scale or VAS ratings), the characteristics of labor pain (using modified McGill pain questionnaire) and the body area of existing musculoskeletal pain (using modified Nordic Questionnaire). Results demonstrated that an average labor pain score was 5.95±1.99, which was classified as moderate level. Most of them (49.06 %) were found in this level. Ninety-five percent of subjects complained as “pain” which was correlated with the results using McGill pain questionnaire that found 90 % and 88 % of the subjects felt “cramping” and “dull” respectively. Considering the area of perceived pain, most of them (96 %) felt pain at the lower abdomen. Additionally, the results from Nordic Questionnaire showed that 80.20% had low back pain where as 49.50% had hip and thigh pain. It was concluded that labor pain during the first stage of primipara had severity of labor pain at a moderate level and the most of painful body-areas were lower abdomen, hip and thighs. Accordingly, this information may be used for considering the alternative-care techniques instead of using pain killer for labor pain.
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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) | 0.001 | 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".