Longitudinal associations between stroke and psychosis: a population-based study

Psychol Med. 2023 Dec;53(16):7698-7706. doi: 10.1017/S0033291723001575. Epub 2023 Jun 5.

Abstract

Background: The co-occurrence of stroke and psychosis is a serious neuropsychiatric condition but little is known about the course of this comorbidity. We aimed to estimate longitudinal associations between stroke and psychosis over 10 years.

Methods: A 10-year population-based study using data from the English Longitudinal Study of Ageing. A structured health assessment recorded (i) first-occurrence stroke and (ii) psychosis, at each wave. Each were considered exposures and outcomes in separate analyses. Logistic and Cox proportional hazards regression and Kaplan-Meier methods were used. Models were adjusted for demographic and health behaviour covariates, with missing covariates imputed using random forest multiple imputation.

Results: Of 19 808 participants, 24 reported both stroke and psychosis (median Wave 1 age 63, 71% female, 50% lowest quintile of net financial wealth) at any point during follow-up. By 10 years, the probability of an incident first stroke in participants with psychosis was 21.4% [95% confidence interval (CI) 12.1-29.6] compared to 8.3% (95% CI 7.8-8.8) in those without psychosis (absolute difference: 13.1%; 95% CI 20.8-4.3, log rank p < 0.001; fully-adjusted hazard ratio (HR): 3.57; 95% CI 2.18-5.84). The probability of reporting incident psychosis in participants with stroke was 2.3% (95% CI 1.4-3.2) compared to 0.9% (95% CI 0.7-1.1) in those without (absolute difference: 1.4%; 95% CI 0.7-2.1, log rank p < 0.001; fully-adjusted HR: 4.98; 95% CI 2.55-9.72).

Conclusions: Stroke is an independent predictor of psychosis (and vice versa), after adjustment for potential confounders.

Keywords: Delusions; hallucinations; neuropsychiatry; psychotic disorder; stroke.

MeSH terms

  • Comorbidity
  • Female
  • Humans
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Proportional Hazards Models
  • Psychotic Disorders* / epidemiology
  • Risk Factors
  • Stroke* / epidemiology