Literature DB >> 26312901

Cannabis use and treatment resistance in first episode psychosis: a natural language processing study.

Rashmi Patel1, Robin Wilson2, Richard Jackson3, Michael Ball3, Hitesh Shetty4, Matthew Broadbent4, Robert Stewart3, Philip McGuire2, Sagnik Bhattacharyya2.   

Abstract

BACKGROUND: Cannabis is frequently used among individuals with first episode psychosis and is associated with poor clinical outcomes. However, little is known about the effect of cannabis use on the response to antipsychotic medications and how use could affect outcomes. Using natural language processing on clinical data from a large electronic case register, we sought to investigate whether resistance to antipsychotic treatment mediated poor clinical outcomes associated with cannabis use.
METHODS: Data were obtained from 2026 people with first episode psychosis in south London, UK. Cannabis use documented in free text clinical records was identified with natural language processing. Data for age, sex, ethnicity, marital status, psychotic disorder diagnosis, subsequent hospital admission, and number of unique antipsychotic medications prescribed were obtained using the Clinical Record Interactive Search instrument. The association of these variables with cannabis use was analysed with multivariable regression and mediation analysis.
FINDINGS: 939 people (46·3%) with first episode psychosis were using cannabis at first presentation. Cannabis use was most strongly associated with being 16-25 years old, male, and single, and was also associated with an increase in number of hospital admissions (incidence rate ratio 1·50, 95% CI 1·25-1·80), compulsory hospital admission (odds ratio 1·55, 1·16-2·08), and number of days spent in hospital (β coefficient 35·1 days, 12·1-58·1) over 5 years' follow-up. An increase in number of unique antipsychotic medications mediated an increase in number of hospital admissions (natural indirect effect 1·11, 1·04-1·17; total effect 1·41, 1·22-1·64), compulsory hospital admission (1·27, 1·10-1·45; 1·71, 1·05-2·78), and number of days spent in hospital (16·1, 6·7-25·5; 19·9, 2·5-37·3).
INTERPRETATION: We showed that a substantial number of people with first episode psychosis used cannabis and that its use was associated with increased likelihood of hospital admission and number of days spent in hospital. These associations were partly mediated by an increase in number of unique antipsychotic medications prescribed. These findings suggest that cannabis might reduce response to conventional antipsychotic treatment and highlight the importance of strategies to reduce its use. FUNDING: National Institute for Health Research, UK Medical Research Council.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Year:  2015        PMID: 26312901     DOI: 10.1016/S0140-6736(15)60394-4

Source DB:  PubMed          Journal:  Lancet        ISSN: 0140-6736            Impact factor:   79.321


  8 in total

1.  Psychiatric symptom recognition without labeled data using distributional representations of phrases and on-line knowledge.

Authors:  Yaoyun Zhang; Olivia Zhang; Yonghui Wu; Hee-Jin Lee; Jun Xu; Hua Xu; Kirk Roberts
Journal:  J Biomed Inform       Date:  2017-06-15       Impact factor: 6.317

2.  Demographic and socioenvironmental predictors of premorbid marijuana use among patients with first-episode psychosis.

Authors:  Luca Pauselli; Michael L Birnbaum; Beatriz Paulina Vázquez Jaime; Enrico Paolini; Mary E Kelley; Beth Broussard; Michael T Compton
Journal:  Schizophr Res       Date:  2018-02-04       Impact factor: 4.939

3.  Using Natural Language Processing on Electronic Health Records to Enhance Detection and Prediction of Psychosis Risk.

Authors:  Jessica Irving; Rashmi Patel; Dominic Oliver; Craig Colling; Megan Pritchard; Matthew Broadbent; Helen Baldwin; Daniel Stahl; Robert Stewart; Paolo Fusar-Poli
Journal:  Schizophr Bull       Date:  2021-03-16       Impact factor: 9.306

4.  Development and Validation of a Natural Language Processing Algorithm to Extract Descriptors of Microbial Keratitis From the Electronic Health Record.

Authors:  Maria A Woodward; Nenita Maganti; Leslie M Niziol; Sejal Amin; Andrew Hou; Karandeep Singh
Journal:  Cornea       Date:  2021-12-01       Impact factor: 2.651

5.  Big data in mental health research - do the ns justify the means? Using large data-sets of electronic health records for mental health research.

Authors:  Peter Schofield
Journal:  BJPsych Bull       Date:  2017-06

6.  Analysis of diagnoses extracted from electronic health records in a large mental health case register.

Authors:  Yevgeniya Kovalchuk; Robert Stewart; Matthew Broadbent; Tim J P Hubbard; Richard J B Dobson
Journal:  PLoS One       Date:  2017-02-16       Impact factor: 3.240

7.  Adapting Word Embeddings from Multiple Domains to Symptom Recognition from Psychiatric Notes.

Authors:  Yaoyun Zhang; Hee-Jin Li; Jingqi Wang; Trevor Cohen; Kirk Roberts; Hua Xu
Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2018-05-18

8.  Investigating repetitive transcranial magnetic stimulation on cannabis use and cognition in people with schizophrenia.

Authors:  Karolina Kozak Bidzinski; Darby J E Lowe; Marcos Sanches; Maryam Sorkhou; Isabelle Boileau; Michael Kiang; Daniel M Blumberger; Gary Remington; Clement Ma; David J Castle; Rachel A Rabin; Tony P George
Journal:  Schizophrenia (Heidelb)       Date:  2022-02-24
  8 in total

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