A nationwide Scottish cohort study of the association between pre-existing mental illness and out-of-hospital cardiac arrest survival

Scritto il 08/05/2026
da Raied Alotaibi

Resusc Plus. 2026 Jan 12;29:101218. doi: 10.1016/j.resplu.2026.101218. eCollection 2026 May.

ABSTRACT

AIM: To investigate the association between pre-existing mental illness and out-of-hospital cardiac arrest (OHCA) survival.

METHODS: We performed a nationwide retrospective cohort study using Scottish Ambulance Service OHCA data linked to unscheduled care and death data in Scotland. We identified adults 18 years or older with non-traumatic OHCA between 2011 and 2022 and defined pre-existing mental illness as a record of mental illness within an unscheduled acute hospital admission or a record of unscheduled psychiatric hospital admission prior to OHCA. We used logistic regression models to obtain crude and adjusted odds ratios (ORs) for the association between mental illness and OHCA 30-day survival and conducted subgroup analyses based on patient and event characteristics, including age, sex, initial heart rhythm and bystander cardiopulmonary resuscitation.

RESULTS: We included 30,523 patients with OHCA, of whom 12.8% had a pre-existing mental illness. Those with pre-existing mental illness had a higher prevalence of physical comorbidities, lower rates of initial shockable heart rhythm and significantly lower odds of 30-day survival compared to those without mental illness, after adjusting for age (OR 0.22, 95% confidence interval 0.18-0.26). This association persisted after adjusting the model for sex, year of arrest, comorbidities and deprivation, and was consistent across the different subgroups analysed.

CONCLUSION: Compared to people without pre-existing mental illness, those with pre-existing mental illness have lower odds of OHCA survival even after accounting for patient and event characteristics. Further research should investigate factors that may be responsible for this association and inform interventions to address disparities.

PMID:42100669 | PMC:PMC13148002 | DOI:10.1016/j.resplu.2026.101218