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The side effect profile of Clozapine in real world data of three large mental health hospitals

OBJECTIVE: Mining the data contained within Electronic Health Records (EHRs) can potentially generate a greater understanding of medication effects in the real world, complementing what we know from Randomised control trials (RCTs). We Propose a text mining approach to detect adverse events and medi...

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Autores principales: Iqbal, Ehtesham, Govind, Risha, Romero, Alvin, Dzahini, Olubanke, Broadbent, Matthew, Stewart, Robert, Smith, Tanya, Kim, Chi-Hun, Werbeloff, Nomi, MacCabe, James H., Dobson, Richard J. B., Ibrahim, Zina M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7723266/
https://www.ncbi.nlm.nih.gov/pubmed/33290433
http://dx.doi.org/10.1371/journal.pone.0243437
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author Iqbal, Ehtesham
Govind, Risha
Romero, Alvin
Dzahini, Olubanke
Broadbent, Matthew
Stewart, Robert
Smith, Tanya
Kim, Chi-Hun
Werbeloff, Nomi
MacCabe, James H.
Dobson, Richard J. B.
Ibrahim, Zina M.
author_facet Iqbal, Ehtesham
Govind, Risha
Romero, Alvin
Dzahini, Olubanke
Broadbent, Matthew
Stewart, Robert
Smith, Tanya
Kim, Chi-Hun
Werbeloff, Nomi
MacCabe, James H.
Dobson, Richard J. B.
Ibrahim, Zina M.
author_sort Iqbal, Ehtesham
collection PubMed
description OBJECTIVE: Mining the data contained within Electronic Health Records (EHRs) can potentially generate a greater understanding of medication effects in the real world, complementing what we know from Randomised control trials (RCTs). We Propose a text mining approach to detect adverse events and medication episodes from the clinical text to enhance our understanding of adverse effects related to Clozapine, the most effective antipsychotic drug for the management of treatment-resistant schizophrenia, but underutilised due to concerns over its side effects. MATERIAL AND METHODS: We used data from de-identified EHRs of three mental health trusts in the UK (>50 million documents, over 500,000 patients, 2835 of which were prescribed Clozapine). We explored the prevalence of 33 adverse effects by age, gender, ethnicity, smoking status and admission type three months before and after the patients started Clozapine treatment. Where possible, we compared the prevalence of adverse effects with those reported in the Side Effects Resource (SIDER). RESULTS: Sedation, fatigue, agitation, dizziness, hypersalivation, weight gain, tachycardia, headache, constipation and confusion were amongst the highest recorded Clozapine adverse effect in the three months following the start of treatment. Higher percentages of all adverse effects were found in the first month of Clozapine therapy. Using a significance level of (p< 0.05) our chi-square tests show a significant association between most of the ADRs and smoking status and hospital admission, and some in gender, ethnicity and age groups in all trusts hospitals. Later we combined the data from the three trusts hospitals to estimate the average effect of ADRs in each monthly interval. In gender and ethnicity, the results show significant association in 7 out of 33 ADRs, smoking status shows significant association in 21 out of 33 ADRs and hospital admission shows the significant association in 30 out of 33 ADRs. CONCLUSION: A better understanding of how drugs work in the real world can complement clinical trials.
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spelling pubmed-77232662020-12-16 The side effect profile of Clozapine in real world data of three large mental health hospitals Iqbal, Ehtesham Govind, Risha Romero, Alvin Dzahini, Olubanke Broadbent, Matthew Stewart, Robert Smith, Tanya Kim, Chi-Hun Werbeloff, Nomi MacCabe, James H. Dobson, Richard J. B. Ibrahim, Zina M. PLoS One Research Article OBJECTIVE: Mining the data contained within Electronic Health Records (EHRs) can potentially generate a greater understanding of medication effects in the real world, complementing what we know from Randomised control trials (RCTs). We Propose a text mining approach to detect adverse events and medication episodes from the clinical text to enhance our understanding of adverse effects related to Clozapine, the most effective antipsychotic drug for the management of treatment-resistant schizophrenia, but underutilised due to concerns over its side effects. MATERIAL AND METHODS: We used data from de-identified EHRs of three mental health trusts in the UK (>50 million documents, over 500,000 patients, 2835 of which were prescribed Clozapine). We explored the prevalence of 33 adverse effects by age, gender, ethnicity, smoking status and admission type three months before and after the patients started Clozapine treatment. Where possible, we compared the prevalence of adverse effects with those reported in the Side Effects Resource (SIDER). RESULTS: Sedation, fatigue, agitation, dizziness, hypersalivation, weight gain, tachycardia, headache, constipation and confusion were amongst the highest recorded Clozapine adverse effect in the three months following the start of treatment. Higher percentages of all adverse effects were found in the first month of Clozapine therapy. Using a significance level of (p< 0.05) our chi-square tests show a significant association between most of the ADRs and smoking status and hospital admission, and some in gender, ethnicity and age groups in all trusts hospitals. Later we combined the data from the three trusts hospitals to estimate the average effect of ADRs in each monthly interval. In gender and ethnicity, the results show significant association in 7 out of 33 ADRs, smoking status shows significant association in 21 out of 33 ADRs and hospital admission shows the significant association in 30 out of 33 ADRs. CONCLUSION: A better understanding of how drugs work in the real world can complement clinical trials. Public Library of Science 2020-12-08 /pmc/articles/PMC7723266/ /pubmed/33290433 http://dx.doi.org/10.1371/journal.pone.0243437 Text en © 2020 Iqbal et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Iqbal, Ehtesham
Govind, Risha
Romero, Alvin
Dzahini, Olubanke
Broadbent, Matthew
Stewart, Robert
Smith, Tanya
Kim, Chi-Hun
Werbeloff, Nomi
MacCabe, James H.
Dobson, Richard J. B.
Ibrahim, Zina M.
The side effect profile of Clozapine in real world data of three large mental health hospitals
title The side effect profile of Clozapine in real world data of three large mental health hospitals
title_full The side effect profile of Clozapine in real world data of three large mental health hospitals
title_fullStr The side effect profile of Clozapine in real world data of three large mental health hospitals
title_full_unstemmed The side effect profile of Clozapine in real world data of three large mental health hospitals
title_short The side effect profile of Clozapine in real world data of three large mental health hospitals
title_sort side effect profile of clozapine in real world data of three large mental health hospitals
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7723266/
https://www.ncbi.nlm.nih.gov/pubmed/33290433
http://dx.doi.org/10.1371/journal.pone.0243437
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