How Hyperprolactinemia Affects Sexual Function in Patients Under Antipsychotic Treatment
Bibliographic record
Abstract
OBJECTIVE: We aimed to study the relationship between hyperprolactinemia (HPRL) and sexual dysfunction (SED) in a sample of patients being prescribed a dose-stable antipsychotic medication, and to evaluate sex differences in the prevalence of HPRL and SED and their relationship. METHOD: A cross-sectional study was carried out including patients between 18 and 55 years of age with a psychotic spectrum diagnosis who were attending community mental health services or hospitalized in medium and long stay units. Positive and Negative Syndrome scale, Calgary depression scale for schizophrenia, Personal and Social Performance scale, and Changes in Sexual Functioning questionnaire-short form were administered. Not later than 3 months, a determination of prolactin, follicle-stimulating hormone, luteinizing hormone, estrogen (only in women) and testosterone was performed. RESULTS: A final sample of 101 patients (30 women and 71 men) was recruited. Seventy-two patients (71.3%) showed HPRL. Sexual dysfunction was significantly higher in HPRL patients than in non-HPRL patients (79.17% vs 51.72%) (P = 0.006), and mean prolactin values were significantly higher in case of SED (P = 0.020). No sex differences were found in prevalence of HPRL or SED. Low Personal and Social Performance scale scores and HPRL were factors independently associated with SED, whereas alcohol use was an independent protector factor. CONCLUSIONS: In our study, SED was significantly related to HPRL without showing sex differences. Prevalence of HPRL and SED observed was higher than that in previous studies, which should be taken into consideration because these have been associated with higher morbimortality, and noncompliance and relapse, respectively.
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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".