New-onset atrial fibrillation prediction: the HARMS2-AF risk score

被引:35
作者
Segan, Louise [1 ,2 ,3 ]
Canovas, Rodrigo [2 ,4 ,5 ]
Nanayakkara, Shane [1 ,2 ,6 ]
Chieng, David [1 ,2 ,3 ]
Prabhu, Sandeep [1 ,2 ,3 ]
Voskoboinik, Aleksandr [1 ,2 ,3 ]
Sugumar, Hariharan [1 ,2 ,3 ]
Ling, Liang-Han [1 ,2 ,3 ]
Lee, Geoff [3 ,7 ]
Morton, Joseph [3 ,7 ]
LaGerche, Andre [1 ,2 ,3 ]
Kaye, David M. [1 ,2 ]
Sanders, Prashanthan [8 ,9 ]
Kalman, Jonathan M. [3 ,7 ]
Kistler, Peter M. [1 ,2 ,3 ,7 ]
机构
[1] Alfred Hosp, Dept Cardiol, 55 Commercial Rd, Melbourne, Vic 3004, Australia
[2] Baker Heart & Diabet Res Inst, Dept Clin Res, 75 Commercial Rd, Melbourne, Vic 3004, Australia
[3] Univ Melbourne, Dept Med Nursing & Hlth Sci, Melbourne, Vic 3010, Australia
[4] Baker Heart & Diabet Inst, Cambridge Baker Syst Genom Initiat, 75 Commercial Rd, Melbourne, Vic 3004, Australia
[5] Australian Ehlth Res Ctr, CSIRO Hlth & Biosecur, 343 Royal Parade, Melbourne, Vic 3052, Australia
[6] Monash Univ, Dept Med Nursing & Hlth Sci, Wellington Rd, Clayton, Vic 3800, Australia
[7] Royal Melbourne Hosp, Dept Cardiol, 300 Grattan St, Melbourne, Vic 3050, Australia
[8] Royal Adelaide Hosp, Dept Cardiol, Port Rd, Adelaide, SA 5000, Australia
[9] Univ Adelaide, Ctr Heart Rhythm Disorders, Port Rd, Adelaide, SA 5000, Australia
基金
英国医学研究理事会;
关键词
Atrial fibrillation; Lifestyle modification; Alcohol; Sleep apnoea; Obesity; Population screening; ALCOHOL-CONSUMPTION; PHYSICAL-ACTIVITY; LIFE-STYLE; ASSOCIATION; COHORT; REDUCTION; COMMUNITY; MORTALITY;
D O I
10.1093/eurheartj/ehad375
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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 & BULL;38) were not significant. The HARMS(2)-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 HARMS(2)-AF score (& GE;5 points) was associated with a heightened AF risk (score 5-9: HR 12.79; score 10-14: HR 38.70). The HARMS(2)-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 HARMS(2)-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.
引用
收藏
页码:3443 / 3452
页数:11
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