Diagnosis and treatment of premenstrual dysphoric disorder: an update.
Bibliographic record
Abstract
Premenstrual dysphoric disorder (PMDD) appears in the appendix of the DSM-IV under the heading 'depressive disorder not otherwise specified'. Yet, recently, a group of experts reached a consensus that PMDD is a distinct clinical entity with characteristic symptoms of irritability, anger, internal tension, dysphoria, and mood lability. PMDD is the more severe form of premenstrual symptomatology, whereas premenstrual syndrome (PMS) is milder and more prevalent and both must be differentiated from premenstrual magnification/exacerbation of an underlying major psychiatric disorder or a medical condition. Accurate assessment and diagnosis of significant premenstrual symptomatology is paramount and can be influenced by subjective perception, retrospective versus prospective reporting, and cultural context. The serotonergic system, which is in a close reciprocal relationship with the gonadal hormones, has been identified as the most plausible target for intervention. Results from randomized placebo-controlled trials in women with PMDD have clearly demonstrated that serotonin reuptake inhibitors (SSRIs), with daily or intermittent dosing, have excellent efficacy and minimal adverse effects and should be considered first-line treatment. Luteal phase only SSRI administration may offer an attractive treatment option for a disorder that is itself intermittent. Hormonal interventions, in particular the suppression of ovulation will eliminate premenstrual symptomatology; however, the benefits-risk ratio of these approaches should be carefully evaluated with the patient.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".