TY - JOUR
T1 - New-onset atrial fibrillation prediction
T2 - the HARMS2-AF risk score
AU - Segan, Louise
AU - Canovas, Rodrigo
AU - Nanayakkara, Shane
AU - Chieng, David
AU - Prabhu, Sandeep
AU - Voskoboinik, Aleksandr
AU - Sugumar, Hariharan
AU - Ling, Liang Han
AU - Lee, Geoff
AU - Morton, Joseph
AU - Lagerche, Andre
AU - Kaye, David M.
AU - Sanders, Prashanthan
AU - Kalman, Jonathan M.
AU - Kistler, Peter M.
N1 - Funding Information:
L.S. is supported by a co-funded NHMRC/NHF post-graduate PhD scholarship. D.C. is supported by a co-funded NHMRC/NHF post-graduate scholarship. The following industry funding sources regarding activities outside the submitted work have been declared in accordance with ICMJE guidelines. P.M.K. has received funding from Abbott Medical for consultancy and speaking engagements and has served on the advisory board with fellowship support from Biosense Webster. J.M.K. has received fellowship support from Medtronic and Biosense Webster. P.S. has served on the advisory board of Medtronic, Abbott Medical, Boston Scientific, CathRx, and PaceMate and has received funding for research and consultancy from Medtronic, Abbott Medical, Boston Scientific, and Microport. G.L. has received consulting fees from Biosense Webster.
Publisher Copyright:
© 2023 The Author(s). Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved.
PY - 2023/9/21
Y1 - 2023/9/21
N2 - Aims: Lifestyle risk factors are a modifiable target in atrial fibrillation (AF) management. The relative contribution of individual lifestyle risk factors to AF development has not been described. Development and validation of an AF lifestyle risk score to identify individuals at risk of AF in the general population are the aims of the study. Methods and results: The UK Biobank (UKB) and Framingham Heart Study (FHS) are large prospective cohorts with outcomes measured >10 years. Incident AF was based on International Classification of Diseases version 10 coding. Prior AF was excluded. Cox proportional hazards regression identified independent AF predictors, which were evaluated in a multivariable model. A weighted score was developed in the UKB and externally validated in the FHS. Kaplan-Meier estimates ascertained the risk of AF development. Among 314 280 UKB participants, AF incidence was 5.7%, with median time to AF 7.6 years (interquartile range 4.5-10.2). Hypertension, age, body mass index, male sex, sleep apnoea, smoking, and alcohol were predictive variables (all P < 0.001); physical inactivity [hazard ratio (HR) 1.01, 95% confidence interval (CI) 0.96-1.05, P = 0.80] and diabetes (HR 1.03, 95% CI 0.97-1.09, P = 0·38) were not significant. The HARMS2-AF score had similar predictive performance [area under the curve (AUC) 0.782] to the unweighted model (AUC 0.802) in the UKB. External validation in the FHS (AF incidence 6.0% of 7171 participants) demonstrated an AUC of 0.757 (95% CI 0.735-0.779). A higher HARMS2-AF score (≥5 points) was associated with a heightened AF risk (score 5-9: HR 12.79; score 10-14: HR 38.70). The HARMS2-AF risk model outperformed the Framingham-AF (AUC 0.568) and ARIC (AUC 0.713) risk models (both P < 0.001) and was comparable to the CHARGE-AF risk score (AUC 0.754, P = 0.73). Conclusion: The HARMS2-AF score is a novel lifestyle risk score which may help identify individuals at risk of AF in the general community and assist population screening.
AB - Aims: Lifestyle risk factors are a modifiable target in atrial fibrillation (AF) management. The relative contribution of individual lifestyle risk factors to AF development has not been described. Development and validation of an AF lifestyle risk score to identify individuals at risk of AF in the general population are the aims of the study. Methods and results: The UK Biobank (UKB) and Framingham Heart Study (FHS) are large prospective cohorts with outcomes measured >10 years. Incident AF was based on International Classification of Diseases version 10 coding. Prior AF was excluded. Cox proportional hazards regression identified independent AF predictors, which were evaluated in a multivariable model. A weighted score was developed in the UKB and externally validated in the FHS. Kaplan-Meier estimates ascertained the risk of AF development. Among 314 280 UKB participants, AF incidence was 5.7%, with median time to AF 7.6 years (interquartile range 4.5-10.2). Hypertension, age, body mass index, male sex, sleep apnoea, smoking, and alcohol were predictive variables (all P < 0.001); physical inactivity [hazard ratio (HR) 1.01, 95% confidence interval (CI) 0.96-1.05, P = 0.80] and diabetes (HR 1.03, 95% CI 0.97-1.09, P = 0·38) were not significant. The HARMS2-AF score had similar predictive performance [area under the curve (AUC) 0.782] to the unweighted model (AUC 0.802) in the UKB. External validation in the FHS (AF incidence 6.0% of 7171 participants) demonstrated an AUC of 0.757 (95% CI 0.735-0.779). A higher HARMS2-AF score (≥5 points) was associated with a heightened AF risk (score 5-9: HR 12.79; score 10-14: HR 38.70). The HARMS2-AF risk model outperformed the Framingham-AF (AUC 0.568) and ARIC (AUC 0.713) risk models (both P < 0.001) and was comparable to the CHARGE-AF risk score (AUC 0.754, P = 0.73). Conclusion: The HARMS2-AF score is a novel lifestyle risk score which may help identify individuals at risk of AF in the general community and assist population screening.
KW - Alcohol
KW - Atrial fibrillation
KW - Lifestyle modification
KW - Obesity
KW - Population screening
KW - Sleep apnoea
UR - http://www.scopus.com/inward/record.url?scp=85172423758&partnerID=8YFLogxK
U2 - 10.1093/eurheartj/ehad375
DO - 10.1093/eurheartj/ehad375
M3 - Article
C2 - 37350480
AN - SCOPUS:85172423758
SN - 0195-668X
VL - 44
SP - 3443
EP - 3452
JO - European Heart Journal
JF - European Heart Journal
IS - 36
ER -
