TY - JOUR
T1 - Anticoagulation for atrial fibrillation in people with serious mental illness in the general hospital setting
AU - Farran, Dina
AU - Bean, Daniel
AU - Wang, Tao
AU - Msosa, Yamiko
AU - Casetta, Cecilia
AU - Dobson, Richard
AU - Teo, James
AU - Scott, Paul Andrew
AU - Gaughran, Fiona
N1 - Funding Information:
TW and YM are supported by the Maudsley Charity Grant (No. 1517 ).
Funding Information:
RD's work is supported by the following: (1) NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK; (2) Health Data Research UK , which is funded by the UK Medical Research Council , Engineering and Physical Sciences Research Council , Economic and Social Research Council , Department of Health and Social Care (England) , Chief Scientist Office of the Scottish Government Health and Social Care Directorates , Health and Social Care Research and Development Division (Welsh Government) , Public Health Agency (Northern Ireland) , British Heart Foundation and Wellcome Trust ; (3) The BigData@Heart Consortium , funded by the Innovative Medicines Initiative-2 Joint Undertaking under grant agreement No. 116074. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA; it is chaired by DE Grobbee and SD Anker, partnering with 20 academic and industry partners and ESC; (4) the National Institute for Health Research University College London Hospitals Biomedical Research Centre ; (5) the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London ; (6) the UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare ; (7) the National Institute for Health Research ( NIHR ) Applied Research Collaboration South London ( NIHR ARC South London) at King's College Hospital NHS Foundation Trust.
Funding Information:
J.T.T. has received research grant funding support from Innovate UK , NHSX , Office of Life Sciences , National Institutes of Health Research, Bristol-Meyers Squibb , and Pfizer .
Funding Information:
This project was conducted under London South East Research Ethics Committee approval (reference 18/LO/2048) granted to the King's Electronic Records Research Interface (KERRI), project ID 20200201.DF is supported by the National Institute for Health Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King's College Hospital NHSFoundation Trust and by the KCL funded Centre for Doctoral Training (CDT) in Data-Driven Health.DB holds a UKRI Fellowship as part of HDRUK MR/S00310X/1.TW and YM are supported by the Maudsley Charity Grant (No.1517).RD's work is supported by the following: (1) NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK; (2) Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome Trust; (3) The BigData@Heart Consortium, funded by the Innovative Medicines Initiative-2 Joint Undertaking under grant agreement No. 116074. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA; it is chaired by DE Grobbee and SD Anker, partnering with 20 academic and industry partners and ESC; (4) the National Institute for Health Research University College London Hospitals Biomedical Research Centre; (5) the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London; (6) the UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare; (7) the National Institute for Health Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King's College Hospital NHSFoundation Trust.J.T.T. has received research grant funding support from Innovate UK, NHSX, Office of Life Sciences, National Institutes of Health Research, Bristol-Meyers Squibb, and Pfizer.FG is in part supported by the National Institute for Health Research's (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, by the Maudsley Charity and by the National Institute for Health Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King's College Hospital NHSFoundation Trust.J.T.T. has received speaker honoraria from Bayer, Bristol-Meyers Squibb, Pfizer, and Goldman Sachs; hospitality from iRhythm Technologies; copyright fees from Wiley-Blackwell; and owns public shares in Apple, Nvidia, Amazon, and Alphabet.
Funding Information:
DF is supported by the National Institute for Health Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King's College Hospital NHSFoundation Trust and by the KCL funded Centre for Doctoral Training (CDT) in Data-Driven Health .
Funding Information:
FG is in part supported by the National Institute for Health Research's ( NIHR ) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, by the Maudsley Charity and by the National Institute for Health Research ( NIHR ) Applied Research Collaboration South London ( NIHR ARC South London) at King's College Hospital NHS Foundation Trust.
Publisher Copyright:
© 2022
PY - 2022/9
Y1 - 2022/9
N2 - Objective: People with serious mental illnesses (SMI) have an increased risk of stroke compared to the general population. This study aims to evaluate oral anticoagulation prescription trends in atrial fibrillation (AF) patients with and without a comorbid SMI.Methods: An open-source retrieval system for clinical data (CogStack) was used to identify a cohort of AF patients with SMI who ever had an inpatient admission to King's College Hospital from 2011 to 2020. A Natural Language Processing pipeline was used to calculate CHA2DS2-VASc and HASBLED risk scores from Electronic Health Records free text. Antithrombotic prescriptions of warfarin and Direct acting oral anti-coagulants (DOACs) (apixaban, rivaroxaban, dabigatran, edoxaban) were extracted from discharge summaries.Results: Among patients included in the study (n = 16 916), 2.7% had a recorded co-morbid SMI diagnosis. Compared to non-SMI patients, those with SMI had significantly higher CHA2DS2-VASc (mean (SD): 5.3 (1.96) vs 4.7 (2.08), p < 0.001) and HASBLED scores (mean (SD): 3.2 (1.27) vs 2.5 (1.29), p < 0.001). Among AF patients having a CHA2DS2-VASc ≥2, those with co-morbid SMI were less likely than non-SMI patients to be prescribed an OAC (44% vs 54%, p < 0.001). However, there was no evidence of a significant difference between the two groups since 2019.Conclusion: Over recent years, DOAC prescription rates have increased among AF patients with SMI in acute hospitals. More research is needed to confirm whether the introduction of DOACs has reduced OAC treatment gaps in people with serious mental illness and to assess whether the use of DOACs has improved health outcomes in this population.
AB - Objective: People with serious mental illnesses (SMI) have an increased risk of stroke compared to the general population. This study aims to evaluate oral anticoagulation prescription trends in atrial fibrillation (AF) patients with and without a comorbid SMI.Methods: An open-source retrieval system for clinical data (CogStack) was used to identify a cohort of AF patients with SMI who ever had an inpatient admission to King's College Hospital from 2011 to 2020. A Natural Language Processing pipeline was used to calculate CHA2DS2-VASc and HASBLED risk scores from Electronic Health Records free text. Antithrombotic prescriptions of warfarin and Direct acting oral anti-coagulants (DOACs) (apixaban, rivaroxaban, dabigatran, edoxaban) were extracted from discharge summaries.Results: Among patients included in the study (n = 16 916), 2.7% had a recorded co-morbid SMI diagnosis. Compared to non-SMI patients, those with SMI had significantly higher CHA2DS2-VASc (mean (SD): 5.3 (1.96) vs 4.7 (2.08), p < 0.001) and HASBLED scores (mean (SD): 3.2 (1.27) vs 2.5 (1.29), p < 0.001). Among AF patients having a CHA2DS2-VASc ≥2, those with co-morbid SMI were less likely than non-SMI patients to be prescribed an OAC (44% vs 54%, p < 0.001). However, there was no evidence of a significant difference between the two groups since 2019.Conclusion: Over recent years, DOAC prescription rates have increased among AF patients with SMI in acute hospitals. More research is needed to confirm whether the introduction of DOACs has reduced OAC treatment gaps in people with serious mental illness and to assess whether the use of DOACs has improved health outcomes in this population.
KW - Atrial fibrillation
KW - DOACs
KW - Oral anticoagulation
KW - Serious mental illness
KW - Warfarin
UR - http://www.scopus.com/inward/record.url?scp=85133874254&partnerID=8YFLogxK
U2 - 10.1016/j.jpsychires.2022.06.044
DO - 10.1016/j.jpsychires.2022.06.044
M3 - Article
C2 - 35816976
AN - SCOPUS:85133874254
SN - 0022-3956
VL - 153
SP - 167
EP - 173
JO - Journal of psychiatric research
JF - Journal of psychiatric research
ER -