Do positive psychosocial factors contribute to the prediction of coronary artery disease? A UK Biobank-based machine learning approach

被引:0
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作者
Hefti, Rene [1 ,2 ]
Guemghar, Souad [1 ,2 ]
Battegay, Edouard [1 ,2 ,3 ,4 ]
Mueller, Christian [5 ]
Koenig, Harold G. [6 ]
Schaefert, Rainer [1 ,2 ]
Meinlschmidt, Gunther [1 ,2 ,7 ,8 ,9 ]
机构
[1] Univ Hosp Basel, Dept Psychosomat Med, Hebelstr 2, CH-4031 Basel, Switzerland
[2] Univ Basel, Hebelstr 2, CH-4031 Basel, Switzerland
[3] Univ Zurich, Int Ctr Multimorbid & Complex Med ICMC, Ramistr 71, CH-8006 Zurich, Switzerland
[4] Merian Iselin Klin, Fohrenstr 2, CH-4054 Basel, Switzerland
[5] Univ Hosp Basel, Cardiovasc Res Inst, Petersgraben 4, CH-4031 Basel, Switzerland
[6] Duke Univ, Med Ctr, Dept Med & Psychiat, 40 Duke Med Cir, Durham, NC 27710 USA
[7] Univ Hosp Basel, Dept Digital & Blended Psychosomat & Psychotherapy, Psychosomat Med, Hebelstrasse 2, CH-4031 Basel, Switzerland
[8] Trier Univ, Dept Psychol Clin Psychol & Psychotherapy Methods, Univ Sring 15, D-54296 Trier, Germany
[9] Int Psychoanalyt Univ IPU Berlin, Dept Clin Psychol & Cognit Behav Therapy, Stromstr 3b, D-10555 Berlin, Germany
关键词
Cardiovascular disease; Positive psychosocial factors; Disease prediction; Artificial intelligence; Preventive cardiology; HEART-DISEASE; CARDIOVASCULAR-DISEASE; RISK-FACTORS; MYOCARDIAL-INFARCTION; EUROPEAN-SOCIETY; SOCIAL-ISOLATION; TASK-FORCE; MORTALITY; ASSOCIATION; ADULTS;
D O I
10.1093/eurjpc/zwae237
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Aims Most prediction models for coronary artery disease (CAD) compile biomedical and behavioural risk factors using linear multivariate models. This study explores the potential of integrating positive psychosocial factors (PPFs), including happiness, satisfaction with life, and social support, into conventional and machine learning-based CAD-prediction models.Methods and results We included UK Biobank (UKB) participants without CAD at baseline. First, we estimated associations of individual PPFs with subsequent acute myocardial infarction (AMI) and chronic ischaemic heart disease (CIHD) using logistic regression. Then, we compared the performances of logistic regression and eXtreme Gradient Boosting (XGBoost) prediction models when adding PPFs as predictors to the Framingham Risk Score (FRS). Based on a sample size between 160 226 and 441 419 of UKB participants, happiness, satisfaction with health and life, and participation in social activities were linked to lower AMI and CIHD risk (all P-for-trend <= 0.04), while social support was not. In a validation sample, adding PPFs to the FRS using logistic regression and XGBoost prediction models improved neither AMI [area under the receiver operating characteristic curve (AUC) change: 0.02 and 0.90%, respectively] nor CIHD (AUC change: -1.10 and -0.88%, respectively) prediction.Conclusion Positive psychosocial factors were individually linked to CAD risk, in line with previous studies, and as reflected by the new European Society of Cardiology guidelines on cardiovascular disease prevention. However, including available PPFs in CAD-prediction models did not improve prediction compared with the FRS alone. Future studies should explore whether PPFs may act as CAD-risk modifiers, especially if the individual's risk is close to a decision threshold. Positive psychosocial factors (PPFs) like happiness, satisfaction with health and life, social support, and social activities can aid in successfully managing life's challenges, stress, and disease. Consequently, they may help lower the risk and progression of cardiovascular disease. The study confirmed that PPFs were associated with lower risks of myocardial infarction and chronic ischaemic heart disease. These findings underscore the role of PPFs as risk modifiers for coronary artery disease (CAD), as recommended by the 2021 ESC Guidelines on cardiovascular disease prevention. This means that the individual risk of getting a CAD can be shifted to the next lower risk category by higher levels of happiness, satisfaction with health and life, and social support. Graphical Abstract
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页数:10
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