Evaluating the effectiveness of NSAIDs and vasopressin receptor antagonists as primary dysmenorrhea treatments
Bibliographic record
Abstract
Primary dysmenorrhea describes the intensely painful uterine contractions experienced during menstruation. It is associated with elevated prostaglandin production in the uterine area and primarily affects adolescents. There are several treatment options available for primary dysmenorrhea, however, there is a lapse in research assessing their efficacy and reliability. The purpose of this review is to provide an overview and evaluation of two forms of treatment for primary dysmenorrhea: non-steroidal antiinflammatory drugs (NSAIDs) and vasopressin receptor antagonists. While studies conducted on the effectiveness of NSAIDs have shown consistent results, research conducted on vasopressin receptor antagonists remains contradictory. As such, the clinical efficacy of vasopressin receptor antagonists remains inconclusive, exposing several limitations and areas that require additional research. Furthermore, this review discusses the efficacy of promising novel treatments (i.e. levonorgestrel-releasing intrauterine devices, intravaginal rings, transdermal patches) and highlights the importance of additional studies for validation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".