Comparing the analgesic effect of heat patch containing iron chip and ibuprofen for primary dysmenorrhea: a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Primary dysmenorrhea is a common and sometimes disabling condition. In recent years, some studies aimed to improve the treatment of dysmenorrhea, and therefore, introduced several therapeutic measures. This study was designed to compare the analgesic effect of iron chip containing heat wrap with ibuprofen for the treatment of primary dysmenorrhea. METHODS: In this randomized (IRCT201107187038N2) controlled trial, 147 students (18-30 years old) with the diagnosis of primary dysmenorrhea were enrolled considering the CONSORT guideline. Screening for primary dysmenorrhea was done by a two-question screening tool. The participants were randomly assigned into one of the intervention groups (heat Patch and ibuprofen). Data regarding the severity and emotional impact of the pain were recorded by a shortened version of McGill Pain Questionnaire (SF-MPQ). Student's t test was used for statistical analysis. RESULTS: The maximum and minimum pain severities were observed at 2 and 24 hours in both groups. The severity of sensual pain at 8, 12, and 24 hours was non-significantly less in the heat Patch group. There was also no significant difference between the groups regarding the emotional impact of pain at the first 2, 4, 8, 12 and 12 hours of menstruation. CONCLUSIONS: Heat patch containing Iron chip has comparable analgesic effects to ibuprofen and can possibly be used for primary dysmenorrhea. TRIAL REGISTRATION: IRCT201107187038N2.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".