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Using a statistical learning approach to identify sociodemographic and clinical predictors of response to clozapine.

Daniela Fonseca de FreitasGiouliana Kadra-ScalzoDeborah AgbedjroEmma FrancisIsobel RidlerMegan PritchardHitesh ShettyAviv SegevCecilia CasettaSophie E SmartJohnny DownsSøren Rahn ChristensenNikolaj BakBruce J KinonDaniel StahlJames H MacCabeRichard D Hayes
Published in: Journal of psychopharmacology (Oxford, England) (2022)
These findings suggest that women, people with a comorbid mood disorder and those who are most ill at baseline respond better to clozapine. However, the accuracy of the internally validated and recalibrated model was low. Therefore, future research should indicate whether a prediction model developed by including routinely collected data, in combination with biological information, presents adequate predictive ability to be applied in clinical settings.
Keyphrases
  • healthcare
  • electronic health record
  • type diabetes
  • pregnant women
  • depressive symptoms
  • pregnancy outcomes
  • artificial intelligence