Risk stratification for mortality in cardiovascular disease survivors: A survival conditional inference tree analysis.

Nutrition, Metabolism, and Cardiovascular Diseases : NMCD
Zhijun WuXiang Gao

Abstract

Efficient analysis strategies for complex network with cardiovascular disease (CVD) risk stratification remain lacking. We sought to identify an optimized model to study CVD prognosis using survival conditional inference tree (SCTREE), a machine-learning method. We identified 5379 new onset CVD from 2006 (baseline) to May, 2017 in the Kailuan I study including 101,510 participants (the training dataset). The second cohort composing 1,287 CVD survivors was used to validate the algorithm (the Kailuan II study, n = 57,511). All variables (e.g., age, sex, family history of CVD, metabolic risk factors, renal function indexes, heart rate, atrial fibrillation, and high sensitivity C-reactive protein) were measured at baseline and biennially during the follow-up period. Up to December 2017, we documented 1,104 deaths after CVD in the Kailuan I study and 170 deaths in the Kailuan II study. Older age, hyperglycemia and proteinuria were identified by the SCTREE as main predictors of post-CVD mortality. CVD survivors in the high risk group (presence of 2-3 of these top risk factors), had higher mortality risk in the training dataset (hazard ratio (HR): 5.41; 95% confidence Interval (CI): 4.49-6.52) and in the validation dataset (HR: 6.04; ...Continue Reading

References

Apr 1, 1994·Diabetes·L MykkänenM Laakso
Jan 14, 1999·The New England Journal of Medicine·R Ross
Apr 9, 2001·American Journal of Public Health·B RockhillG A Colditz
Jul 31, 2001·JAMA : the Journal of the American Medical Association·H C GersteinUNKNOWN HOPE Study Investigators
May 16, 2003·JAMA : the Journal of the American Medical Association·Aram V ChobanianUNKNOWN National High Blood Pressure Education Program Coordinating Committee
May 25, 2005·Archives of Internal Medicine·Marianne ZellerUNKNOWN Observatoire des Infarctus de Côte-d'Or Survey Working Group
May 6, 2009·Annals of Internal Medicine·Andrew S LeveyUNKNOWN CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration)
Aug 13, 2013·Catheterization and Cardiovascular Interventions : Official Journal of the Society for Cardiac Angiography & Interventions·Ki-Bum WonYangsoo Jang
Jul 26, 2014·Journal of Marital and Family Therapy·Katie Lee SalisK Daniel O'Leary
Feb 8, 2016·The American Journal of Cardiology·Alberto CorderoVicente Bertomeu-Martínez
Jan 28, 2017·International Journal of Cardiology·Eun Jung KimUNKNOWN KAMIR-NIH registry investigators
Apr 11, 2017·Nature Reviews. Nephrology·Anton Gisterå, Göran K Hansson
Aug 11, 2017·Circulation Research·Bharath Ambale-VenkateshJoão A C Lima
Aug 16, 2017·Journal of Clinical Lipidology·Radmila LyubarovaUNKNOWN Atherothrombosis Intervention in Metabolic Syndrome with Low HDL/High Triglycerides and Impact on Global Health Outcomes (AI
Jun 20, 2019·Journal of the American Heart Association·Shanshan LiXiang Gao

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