Investigating the relationship between thought interference, somatic passivity and outcomes in patients with psychosis: a natural language processing approach using a clinical records search platform in south London

TY - JOUR

T1 - Investigating the relationship between thought interference, somatic passivity and outcomes in patients with psychosis

T2 - a natural language processing approach using a clinical records search platform in south London

AU - Magrangeas, Thibault Thierry

AU - Kolliakou, Anna

AU - Sanyal, Jyoti

AU - Patel, Rashmi

AU - Stewart, Robert

N1 - Funding Information: RS, RP and AK are part funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust and King’s College London. RS is additionally part funded by: (1) an NIHR Senior Investigator Award; (2) the National Institute for Health Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King’s College Hospital NHS Foundation Trust; (3) the DATAMIND HDR UK Mental Health Data Hub (MRC grant MR/W014386). RP has received funding from an NIHR Advanced Fellowship (NIHR301690), a Medical Research Council (MRC) Health Data Research UK Fellowship (MR/S003118/1) and a Starter Grant for Clinical Lecturers (SGL015/1020) supported by the Academy of Medical Sciences, The Wellcome Trust, MRC, British Heart Foundation, Arthritis Research UK, the Royal College of Physicians and Diabetes UK. Publisher Copyright: © 2022 Authors.

PY - 2022/8/2

Y1 - 2022/8/2

N2 - OBJECTIVES: We aimed to apply natural language processing algorithms in routine healthcare records to identify reported somatic passivity (external control of sensations, actions and impulses) and thought interference symptoms (thought broadcasting, insertion, withdrawal), first-rank symptoms traditionally central to diagnosing schizophrenia, and determine associations with prognosis by analysing routine outcomes. DESIGN: Four algorithms were developed on deidentified mental healthcare data and applied to ascertain recorded symptoms over the 3 months following first presentation to a mental healthcare provider in a cohort of patients with a primary schizophreniform disorder (ICD-10 F20-F29) diagnosis. SETTING AND PARTICIPANTS: From the electronic health records of a large secondary mental healthcare provider in south London, 9323 patients were ascertained from 2007 to the data extraction date (25 February 2020). OUTCOMES: The primary binary dependent variable for logistic regression analyses was any negative outcome (Mental Health Act section, >2 antipsychotics prescribed, >22 days spent in crisis care) over the subsequent 2 years. RESULTS: Final adjusted models indicated significant associations of this composite outcome with baseline somatic passivity (prevalence 4.9%; adjusted OR 1.61, 95% CI 1.37 to 1.88), thought insertion (10.7%; 1.24, 95% CI 1.15 to 1.55) and thought withdrawal (4.9%; 1.36, 95% CI 1.10 to 1.69), but not independently with thought broadcast (10.3%; 1.05, 95% CI 0.91 to 1.22). CONCLUSIONS: Symptoms traditionally central to the diagnosis of schizophrenia, but under-represented in current diagnostic frameworks, were thus identified as important predictors of short-term to medium-term prognosis in schizophreniform disorders.

AB - OBJECTIVES: We aimed to apply natural language processing algorithms in routine healthcare records to identify reported somatic passivity (external control of sensations, actions and impulses) and thought interference symptoms (thought broadcasting, insertion, withdrawal), first-rank symptoms traditionally central to diagnosing schizophrenia, and determine associations with prognosis by analysing routine outcomes. DESIGN: Four algorithms were developed on deidentified mental healthcare data and applied to ascertain recorded symptoms over the 3 months following first presentation to a mental healthcare provider in a cohort of patients with a primary schizophreniform disorder (ICD-10 F20-F29) diagnosis. SETTING AND PARTICIPANTS: From the electronic health records of a large secondary mental healthcare provider in south London, 9323 patients were ascertained from 2007 to the data extraction date (25 February 2020). OUTCOMES: The primary binary dependent variable for logistic regression analyses was any negative outcome (Mental Health Act section, >2 antipsychotics prescribed, >22 days spent in crisis care) over the subsequent 2 years. RESULTS: Final adjusted models indicated significant associations of this composite outcome with baseline somatic passivity (prevalence 4.9%; adjusted OR 1.61, 95% CI 1.37 to 1.88), thought insertion (10.7%; 1.24, 95% CI 1.15 to 1.55) and thought withdrawal (4.9%; 1.36, 95% CI 1.10 to 1.69), but not independently with thought broadcast (10.3%; 1.05, 95% CI 0.91 to 1.22). CONCLUSIONS: Symptoms traditionally central to the diagnosis of schizophrenia, but under-represented in current diagnostic frameworks, were thus identified as important predictors of short-term to medium-term prognosis in schizophreniform disorders.

KW - adult psychiatry

KW - health informatics

KW - schizophrenia & psychotic disorders

UR - http://www.scopus.com/inward/record.url?scp=85135423666&partnerID=8YFLogxK

U2 - 10.1136/bmjopen-2021-057433

DO - 10.1136/bmjopen-2021-057433

M3 - Article

C2 - 35918110

AN - SCOPUS:85135423666

SN - 2044-6055

VL - 12

SP - e057433

JO - BMJ Open

JF - BMJ Open

IS - 8

M1 - e057433

ER -