Projects per year
Comorbid illicit substance use is associated with poor clinical outcomes in established psychotic disorders. However, less is known about the impact of substance misuse in first episode psychosis (FEP). We conducted a largescale electronic health record (EHR) study using text mining software to investigate the associations of cannabis, cocaine, amphetamines and MDMA with risk of psychiatric hospitalization.
Data were obtained from 1,835 people with FEP in South London using the Clinical Record Interactive Search tool (CRIS). TextHunter was used to identify exposure to cannabis, cocaine, amphetamines or MDMA documented in free text EHRs. Their relationship with number of psychiatric hospital admissions over a 5-year period was analyzed using multivariable negative binomial regression with age, gender and ethnicity as covariates.
The most frequently used illicit substance was cannabis (58.5%) followed by cocaine (24.4%), amphetamines (3.7%) and MDMA (3.1%). Cannabis (IRR 1.58, 95% CI 1.37 to 1.83) and cocaine (1.36, 1.17 to 1.59) were associated with increased frequency of psychiatric hospital admission. Amphetamines showed no significant association (1.05, 0.77 to 1.45) while MDMA was associated with a reduction in frequency of admissions (0.59, 0.40 to 0.86).
Cannabis and cocaine are associated with a significant increase in frequency of psychiatric hospital admissions. These findings highlight the importance of addressing comorbid illicit substance use in people with FEP.
FingerprintDive into the research topics of 'F55. CLINICAL OUTCOMES ASSOCIATED WITH ILLICIT SUBSTANCE USE IN FIRST EPISODE PSYCHOSIS (FEP): A TEXT MINING STUDY OF ELECTRONIC HEALTH RECORDS'. Together they form a unique fingerprint.
- 2 Finished
Linking electronic health records with passive smartphone activity data to predict outcomes in psychotic disorders
14/02/2018 → 13/02/2021
Symptom dimensions in first episode psychosis: predicting clinical outcomes using natural language processing
3/10/2016 → 2/10/2018