{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:38:03Z","timestamp":1760236683333,"version":"build-2065373602"},"reference-count":47,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T00:00:00Z","timestamp":1639526400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Natural Science Foundation of China","award":["Grant No.11974231 and No.11774212"],"award-info":[{"award-number":["Grant No.11974231 and No.11774212"]}]},{"name":"the Natural Science Foundation of Shaanxi Province, China","award":["Grant No.2020SF-134"],"award-info":[{"award-number":["Grant No.2020SF-134"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Investigation of the risk factors associated with cardiovascular disease (CVD) plays an important part in the prevention and treatment of CVD. This study investigated whether alteration in the multi-scale time irreversibility of sleeping heart rate variability (HRV) was a risk factor for cardiovascular events. The D-value, based on analysis of multi-scale increments in HRV series, was used as the measurement of time irreversibility. Eighty-four subjects from an open-access database (i.e., the Sleep Heart Health Study) were included in this study. None of them had any CVD history at baseline; 42 subjects had cardiovascular events within 1 year after baseline polysomnography and were classed as the CVD group, and the other 42 subjects in the non-CVD group were age matched with those in the CVD group and had no cardiovascular events during the 15-year follow-up period. We compared D-values of sleeping HRV between the CVD and non-CVD groups and found that the D-values of the CVD group were significantly lower than those of the non-CVD group on all 10 scales, even after adjusting for gender and body mass index. Moreover, we investigated the performance of a machine learning model to classify CVD and non-CVD subjects. The model, which was fed with a feature space based on the D-values on 10 scales and trained by a random forest algorithm, achieved an accuracy of 80.8% and a positive prediction rate of 86.7%. These results suggest that the decreased time irreversibility of sleeping HRV is an independent predictor of cardiovascular events that could be used to assist the intelligent prediction of cardiovascular events.<\/jats:p>","DOI":"10.3390\/sym13122424","type":"journal-article","created":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T21:47:36Z","timestamp":1639604856000},"page":"2424","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Investigation on the Prediction of Cardiovascular Events Based on Multi-Scale Time Irreversibility Analysis"],"prefix":"10.3390","volume":"13","author":[{"given":"Xiaochuan","family":"Wu","sequence":"first","affiliation":[{"name":"School of Science, China Pharmaceutical University, Nanjing 211198, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qianru","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Science, China Pharmaceutical University, Nanjing 211198, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Physics & Information Technology, Shaanxi Normal University, Xi\u2019an 710119, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fengzhen","family":"Hou","sequence":"additional","affiliation":[{"name":"School of Science, China Pharmaceutical University, Nanjing 211198, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,15]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2021, June 20). Cardiovascular Diseases (CVDs). Available online:https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/cardiovascular-diseases-(cvds)."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.cnc.2016.04.002","article-title":"The Normal Electrocardiogram: Resting 12-Lead and Electrocardiogram Monitoring in the Hospital","volume":"28","author":"Harris","year":"2016","journal-title":"Crit. Care Nurs. Clin. N. Am."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1186\/s12967-019-02184-z","article-title":"Reduced heart rate variability predicts fatigue severity in individuals with chronic fatigue syndrome\/myalgic encephalomyelitis","volume":"18","author":"Ramos","year":"2020","journal-title":"J. Transl. Med."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Yan, X., Zhang, L., Li, J., Du, D., and Hou, F. (2020). Entropy-Based Measures of Hypnopompic Heart Rate Variability Contribute to the Automatic Prediction of Cardiovascular Events. Entropy, 22.","DOI":"10.3390\/e22020241"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"121101","DOI":"10.1063\/1.5134833","article-title":"Autonomic control is a source of dynamical chaos in the cardiovascular system","volume":"29","author":"Karavaev","year":"2019","journal-title":"Chaos"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"4335","DOI":"10.1088\/0031-9155\/57\/13\/4335","article-title":"Study of time reversibility\/irreversibility of cardiovascular data: Theoretical results and application to laser Doppler flowmetry and heart rate variability signals","volume":"57","author":"Rousseau","year":"2012","journal-title":"Phys. Med. Biol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"056208","DOI":"10.1103\/PhysRevE.69.056208","article-title":"Testing time symmetry in time series using data compression dictionaries","volume":"69","author":"Kennel","year":"2004","journal-title":"Phys. Rev. E Stat. Nonlin. Soft. Matter. Phys."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"110040","DOI":"10.1016\/j.chaos.2020.110040","article-title":"Classifying of welding time series based on multi-scale time irreversibility analysis and extreme learning machine","volume":"139","author":"Huang","year":"2020","journal-title":"Chaos Solitons Fractals"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Lucia, U., Grisolia, G., and Kuzemsky, A.L. (2020). Time, Irreversibility and Entropy Production in Nonequilibrium Systems. Entropy, 22.","DOI":"10.3390\/e22080887"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.physa.2014.01.016","article-title":"Classifying of financial time series based on multiscale entropy and multiscale time irreversibility","volume":"400","author":"Xia","year":"2014","journal-title":"Phys. A Stat. Mech. Its Appl."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"907","DOI":"10.1007\/s11071-020-05506-9","article-title":"Permutation-based time irreversibility in epileptic electroencephalograms","volume":"100","author":"Yao","year":"2020","journal-title":"Nonlinear Dyn."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1619","DOI":"10.3389\/fphys.2019.01619","article-title":"Time Irreversibility of Resting-State Activity in the Healthy Brain and Pathology","volume":"10","author":"Zanin","year":"2019","journal-title":"Front. Physiol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1649","DOI":"10.1016\/j.chaos.2006.03.126","article-title":"Time reversal, symbolic series and irreversibility of human heartbeat","volume":"32","author":"Cammarota","year":"2006","journal-title":"Chaos Solitons Fractals"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"198102","DOI":"10.1103\/PhysRevLett.95.198102","article-title":"Broken asymmetry of the human heartbeat: Loss of time irreversibility in aging and disease","volume":"95","author":"Costa","year":"2005","journal-title":"Phys. Rev. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1747","DOI":"10.1088\/0967-3334\/33\/10\/1747","article-title":"Multiscale time irreversibility of heart rate and blood pressure variability during orthostasis","volume":"33","author":"Chladekova","year":"2012","journal-title":"Physiol. Meas."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/j.pnpbp.2012.06.023","article-title":"Heart rate time irreversibility is impaired in adolescent major depression","volume":"39","author":"Tonhajzerova","year":"2012","journal-title":"Prog. Neuropsychopharmacol. Biol. Psychiatry"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1038\/nrendo.2009.23","article-title":"Effects of poor and short sleep on glucose metabolism and obesity risk","volume":"5","author":"Spiegel","year":"2009","journal-title":"Nat. Rev. Endocrinol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.smrv.2011.05.001","article-title":"Immune, inflammatory and cardiovascular consequences of sleep restriction and recovery","volume":"16","author":"Faraut","year":"2012","journal-title":"Sleep Med. Rev."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1007\/s00426-011-0335-6","article-title":"System consolidation of memory during sleep","volume":"76","author":"Born","year":"2012","journal-title":"Psychol. Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.physa.2018.08.043","article-title":"Symbolic dynamics of electroencephalography is associated with the sleep depth and overall sleep quality in healthy adults","volume":"513","author":"Ma","year":"2018","journal-title":"Phys. A Stat. Mech. Its Appl."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1002\/da.1041","article-title":"Sleep disturbances and mood disorders: An epidemiologic perspective","volume":"14","author":"Ford","year":"2001","journal-title":"Depress. Anxiety"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"411","DOI":"10.5665\/sleep.4500","article-title":"Relationships between sleep stages and changes in cognitive function in older men: The MrOS Sleep Study","volume":"38","author":"Song","year":"2015","journal-title":"Sleep"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1093\/gerona\/61.4.405","article-title":"Poor sleep is associated with impaired cognitive function in older women: The study of osteoporotic fractures","volume":"61","author":"Blackwell","year":"2006","journal-title":"J. Gerontol. A Biol. Sci. Med. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1097\/WNP.0000000000000544","article-title":"Heart Rate Variability During Nocturnal Sleep and Daytime Naps in Patients With Narcolepsy Type 1 and Type 2","volume":"36","author":"Aslan","year":"2019","journal-title":"J. Clin. Neurophysiol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1408","DOI":"10.1113\/EP087784","article-title":"Cardiovascular and respiratory profiles during the sleep-wake cycle of rats previously submitted to chronic intermittent hypoxia","volume":"104","author":"Bazilio","year":"2019","journal-title":"Exp. Physiol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"E1402","DOI":"10.1073\/pnas.1516953113","article-title":"Circadian misalignment increases cardiovascular disease risk factors in humans","volume":"113","author":"Morris","year":"2016","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1080\/10903127.2016.1194928","article-title":"Exploratory Study of Heart Rate Variability and Sleep among Emergency Medical Services Shift Workers","volume":"21","author":"Neufeld","year":"2017","journal-title":"Prehosp. Emerg. Care"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1177\/0193945919864700","article-title":"Increased Activity in Patients with Cardiovascular Risk Factors Increases Heart Rate Variability","volume":"42","author":"Nakayama","year":"2020","journal-title":"West J. Nurs. Res."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1038\/hr.2010.61","article-title":"Increased heart rate variability during sleep is a predictor for future cardiovascular events in patients with type 2 diabetes","volume":"33","author":"Eguchi","year":"2010","journal-title":"Hypertens. Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"zsy174","DOI":"10.1093\/sleep\/zsy174","article-title":"Posttraumatic stress disorder diagnosis is associated with reduced parasympathetic activity during sleep in US veterans and military service members of the Iraq and Afghanistan wars","volume":"41","author":"Ulmer","year":"2018","journal-title":"Sleep"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.sleep.2019.11.1259","article-title":"Sleep heart rate variability assists the automatic prediction of long-term cardiovascular outcomes","volume":"67","author":"Zhang","year":"2020","journal-title":"Sleep Med."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1177\/1099800419877442","article-title":"Heart Rate Variability and Risk of All-Cause Death and Cardiovascular Events in Patients With Cardiovascular Disease: A Meta-Analysis of Cohort Studies","volume":"22","author":"Fang","year":"2020","journal-title":"Biol. Res. Nurs."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.5665\/sleep.5774","article-title":"Scaling Up Scientific Discovery in Sleep Medicine: The National Sleep Research Resource","volume":"39","author":"Dean","year":"2016","journal-title":"Sleep"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1109\/TBME.1985.325532","article-title":"A real-time QRS detection algorithm","volume":"32","author":"Pan","year":"1985","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"068102","DOI":"10.1103\/PhysRevLett.89.068102","article-title":"Multiscale entropy analysis of complex physiologic time series","volume":"89","author":"Costa","year":"2002","journal-title":"Phys. Rev. Lett."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"754","DOI":"10.1016\/j.physa.2009.10.003","article-title":"Analysis of heartbeat asymmetry based on multi-scale time irreversibility test","volume":"389","author":"Hou","year":"2009","journal-title":"Phys. A Stat. Mech. Its Appl."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1016\/j.medengphy.2011.01.002","article-title":"High-dimensional time irreversibility analysis of human interbeat intervals","volume":"33","author":"Hou","year":"2011","journal-title":"Med. Eng. Phys."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1043","DOI":"10.1161\/01.CIR.93.5.1043","article-title":"Heart rate variability: Standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology","volume":"93","author":"Camm","year":"1996","journal-title":"Circulation"},{"key":"ref_39","first-page":"3133","article-title":"Do we need hundreds of classifiers to solve real world classification problems?","volume":"15","author":"Cernadas","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/BF00058655","article-title":"Bagging predictors","volume":"24","author":"Breiman","year":"1996","journal-title":"Mach. Learn."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2691","DOI":"10.1109\/TIFS.2018.2825953","article-title":"Constrained Convolutional Neural Networks: A New Approach Towards General Purpose Image Manipulation Detection","volume":"13","author":"Bayar","year":"2018","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"994","DOI":"10.1093\/eurheartj\/ehi819","article-title":"Cardiovascular diseases in women: A statement from the policy conference of the European Society of Cardiology","volume":"27","author":"Fox","year":"2006","journal-title":"Eur. Heart J."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"968","DOI":"10.1161\/01.CIR.67.5.968","article-title":"Obesity as an independent risk factor for cardiovascular disease: A 26-year follow-up of participants in the Framingham Heart Study","volume":"67","author":"Hubert","year":"1983","journal-title":"Circulation"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/S0197-4580(01)00266-4","article-title":"What is physiologic complexity and how does it change with aging and disease?","volume":"23","author":"Goldberger","year":"2002","journal-title":"Neurobiol. Aging"},{"key":"ref_46","unstructured":"Porta, A., Guzzetti, S., Montano, N., Gnecchi-Ruscone, T., Furlan, R., and Malliani, A. (2006, January 17\u201320). Time Reversibility in Short-Term Heart Period Variability. Proceedings of the 2006 Computers in Cardiology, Valencia, Spain."},{"key":"ref_47","first-page":"1359","article-title":"Assessment of cardiovascular regulation through irreversibility analysis of heart period variability: A 24 hours Holter study in healthy and chronic heart failure populations","volume":"367","author":"Porta","year":"2009","journal-title":"Philos. Trans. A Math Phys. Eng. Sci."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/13\/12\/2424\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:48:14Z","timestamp":1760168894000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/13\/12\/2424"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,15]]},"references-count":47,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2021,12]]}},"alternative-id":["sym13122424"],"URL":"https:\/\/doi.org\/10.3390\/sym13122424","relation":{},"ISSN":["2073-8994"],"issn-type":[{"type":"electronic","value":"2073-8994"}],"subject":[],"published":{"date-parts":[[2021,12,15]]}}}