TY - JOUR
T1 - Development and external validation of the SMA2SH2ERS risk prediction model for aneurysmal subarachnoid haemorrhage in the general population
T2 - a population-based prospective cohort study
AU - Klieverik, Vita M.
AU - Kanning, Jos P.
AU - Rissanen, Ina L.
AU - Rannikmae, Kristiina
AU - Martinsen, Amy E.
AU - Winsvold, Bendik S.
AU - Geerlings, Mirjam I.
AU - Ruigrok, Ynte M.
N1 - Publisher Copyright:
© Author(s) (or their employer(s)) 2025. Re-use permitted under CC BY. Published by BMJ Group.
PY - 2025/1/15
Y1 - 2025/1/15
N2 - Objectives Aneurysmal subarachnoid haemorrhage (ASAH) is a severe stroke type, preventable by screening for intracranial aneurysms followed by treatment in high-risk individuals. We aimed to develop and validate a risk prediction model for ASAH in the general population to identify high-risk individuals. Design We used the population-based prospective cohort studies of the United Kingdom (UK) Biobank for model development and the Trøndelag Health (HUNT) Study for model validation. Participants Participants missing data were excluded. A total of 456 856 individuals from the UK Biobank and 46 483 individuals from the HUNT Study were included. Primary and secondary outcome measures Incident ASAH identified using the International Classification of Diseases codes, ICD-9 430 and ICD-10 I600 to I609 codes. Results In the development cohort, ASAH occurred in 738 (0.2%) during 5 407 909 person-years of follow-up. We developed a multivariable Cox regression model to identify predictors for ASAH. Predictive performance was assessed using discrimination and calibration, and we corrected for overfitting using bootstrapping techniques. Predictors for ASAH were sex (S), diabetes mellitus (M), age and alcohol consumption (A 2), smoking (S), hypertension and hypercholesterolaemia (H 2), educational attainment (E), regular physical activity (R) and family history of stroke (S; SMA 2 SH 2 ERS), and multiple interactions between these predictors. The concordance statistic (c-statistic) of the model in the development cohort was 0.62 (95% CI 0.60 to 0.64). Predicted absolute 10-year ASAH risk varied from 0.042% to 0.52%. In the validation cohort, 220 individuals developed ASAH, and the c-statistic of this model was 0.64 (95% CI 0.58 to 0.69). Both models showed reasonable calibration. Conclusions Our SMA 2 SH 2 ERS model provides ASAH risk estimates between 0.042% and 0.52% for the general population. While overall ASAH risk is low, the model identifies individuals with up to 12 times increased risk compared with those at the lowest risk.
AB - Objectives Aneurysmal subarachnoid haemorrhage (ASAH) is a severe stroke type, preventable by screening for intracranial aneurysms followed by treatment in high-risk individuals. We aimed to develop and validate a risk prediction model for ASAH in the general population to identify high-risk individuals. Design We used the population-based prospective cohort studies of the United Kingdom (UK) Biobank for model development and the Trøndelag Health (HUNT) Study for model validation. Participants Participants missing data were excluded. A total of 456 856 individuals from the UK Biobank and 46 483 individuals from the HUNT Study were included. Primary and secondary outcome measures Incident ASAH identified using the International Classification of Diseases codes, ICD-9 430 and ICD-10 I600 to I609 codes. Results In the development cohort, ASAH occurred in 738 (0.2%) during 5 407 909 person-years of follow-up. We developed a multivariable Cox regression model to identify predictors for ASAH. Predictive performance was assessed using discrimination and calibration, and we corrected for overfitting using bootstrapping techniques. Predictors for ASAH were sex (S), diabetes mellitus (M), age and alcohol consumption (A 2), smoking (S), hypertension and hypercholesterolaemia (H 2), educational attainment (E), regular physical activity (R) and family history of stroke (S; SMA 2 SH 2 ERS), and multiple interactions between these predictors. The concordance statistic (c-statistic) of the model in the development cohort was 0.62 (95% CI 0.60 to 0.64). Predicted absolute 10-year ASAH risk varied from 0.042% to 0.52%. In the validation cohort, 220 individuals developed ASAH, and the c-statistic of this model was 0.64 (95% CI 0.58 to 0.69). Both models showed reasonable calibration. Conclusions Our SMA 2 SH 2 ERS model provides ASAH risk estimates between 0.042% and 0.52% for the general population. While overall ASAH risk is low, the model identifies individuals with up to 12 times increased risk compared with those at the lowest risk.
KW - Cardiovascular Disease
KW - Intracerebral Haemorrhage
KW - Stroke
UR - http://www.scopus.com/inward/record.url?scp=85215403659&partnerID=8YFLogxK
U2 - 10.1136/bmjopen-2024-091756
DO - 10.1136/bmjopen-2024-091756
M3 - Article
AN - SCOPUS:85215403659
SN - 2044-6055
VL - 15
JO - BMJ Open
JF - BMJ Open
IS - 1
M1 - e091756
ER -