Gender Differences in Serum Prolactin Levels in Drug Naïve First Episode Schizophrenia
Bibliographic record
Abstract
Objective: To determine if there is a significant rise in serum prolactin (PRL) in acute psychosis related to disease process and weather there is a significant gender difference in the level of PRL and its correlation psychopathology. Procedure: Naturalistic study involved 60 consenting outpatients and inpatients in a tertiary psychiatric setting. Patient base was comprised of men (n = 30) and women (n = 30) with 83% in the age range of 21 - 40 years old. All subjects had confirmed first episode diagnosis set forth by the Diagnostic and Statistical Manual of Mental Disorders. Patients were drug free and drug na?ve. Standardization for control was done using 15 control PRL samples obtained from healthy individuals. Methodology involved assessment by radioimmunoassay, the Brief Psychiatric Rating Scale and the Positive and Negative Syndrome Scale at day 1, 3 weeks and again at 6 weeks. All patients were treated with atypical antipsychotic drugs. Results: Serum PRL was elevated on baseline in 75% of first episode psychosis schizophrenia, yet found to have a negative correlation to psychopathology at base week 3 and week 6 samples. Conclusions: Elevated serum PRL is not a potential indicator of acute schizophrenia. Levels are higher in females than in males, yet females respond better to treatment at a lower dose than males.
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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 | 0.001 |
| 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) | 0.002 | 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".