Bibliographic record
Abstract
OBJECTIVE: To evaluate the strength of evidence for treatments for premenstrual syndrome (PMS) and to derive a set of practical guidelines for managing PMS in family practice. QUALITY OF EVIDENCE: An advanced MEDLINE search was conducted from January 1990 to December 2001. The Cochrane Library and personal contacts were also used. Quality of evidence in studies ranged from level I to level III, depending on the intervention. MAIN MESSAGE: Good scientific evidence shows that calcium carbonate (1200 mg/d) and selective serotonin reuptake inhibitors are effective treatments for PMS. The most commonly used therapies (including vitamin B6, evening primrose oil, and oral contraceptives) are based on inconclusive evidence. Other treatments for which there is inconclusive evidence include aerobic exercise, stress reduction, cognitive therapy, spironolactone, magnesium, nonsteroidal anti-inflammatory drugs, various hormonal regimens, and a complex carbohydrate-rich diet. Although evidence for them is inconclusive, it is reasonable to recommend healthy lifestyle changes given their overall health benefits. Progesterone and bromocriptine, which are still widely used, are ineffective. CONCLUSION: Calcium carbonate should be recommended as first-line therapy for women with mild-to-moderate PMS. Selective serotonin reuptake inhibitors can be considered as first-line therapy for women with severe affective symptoms and for women with milder symptoms who have failed to respond to other therapies. Other therapies may be tried if these measures fail to provide adequate relief.
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 | 0.009 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".