ArticleAmerican journal of translational research2025
Combinatorial classification model for predicting antipsychotic-induced hyperprolactinemia risk.
Article in American journal of translational research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Development and External Validation of a Nomogram for Individualized Risk Prediction of Hyperprolactinemia in Chronic Kidney Disease: A Retrospective Multicenter Study.International journal of general medicine · 2026Article
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6 authors.
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Abstract
objectivesTo develop a risk prediction model for antipsychotic-induced hyperprolactinemia in female patients with schizophrenia.
methodsA total of 200 female patients with first-episode schizophrenia who underwent antipsychotic monotherapy at Huzhou Third Municipal Hospital from February 2022 to December 2023 were enrolled in this study. Venous blood samples were collected before treatment to measure thyroid function, cortisol, and sex hormones. Based on the levels of prolactin (PRL) and macroprolactin (MPRL) after four weeks of treatment, patients were divided into two groups: the hyperprolactinemia group (n = 92) and the macroprolactinemia group (n = 108). Baseline clinical data were compared between groups, and a risk prediction model was constructed and evaluated using receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA). External validation was performed in an independent cohort of 57 patients with schizophrenia admitted between January and July 2024.
resultsUnivariate and multivariate analyses identified body mass index (BMI), free thyroxine (FT4), thyroid-stimulating hormone (TSH), and cortisol as significant predictors of antipsychotic-induced hyperprolactinemia (
conclusionsThe proposed model accurately predicts the risk of antipsychotic-induced hyperprolactinemia in female patients with schizophrenia, offering a valuable tool for early clinical risk assessment.
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