{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T18:16:12Z","timestamp":1772302572952,"version":"3.50.1"},"reference-count":19,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,6]]},"abstract":"<jats:sec>\n            <jats:title>BACKGROUND:<\/jats:title>\n            <jats:p>Continuous arterial blood pressure (ABP) is typically recorded by placement of an intraarterial catheter. Recently, noninvasive ABP monitors have been shown to be comparable in accuracy to invasive measurements. In a previous study, we showed that the fluctuations in beat-to-beat ABP measurements were not random variations but had a complex dynamical structure, and that ABP dynamical complexity was inversely associated with surgical risk estimated using the Society of Thoracic Surgeons (STS) index. Dynamical complexity is a mathematical construct that reflects the capacity of a physiological system to adapt to stimuli. The objectives of present study were to: (1) determine whether noninvasive beat-to-beat ABP measurements also exhibit a complex temporal structure; (2) compare the complexity of noninvasive versus invasive ABP time series; and (3) quantify the relationship between the complexity of noninvasive ABP time series and the STS risk scores.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>METHODS:<\/jats:title>\n            <jats:p>Fifteen adult patients undergoing coronary artery bypass graft, valve, or combined coronary artery bypass graft\/valve surgery were enrolled in this observational study. Preoperative ABP waveforms were simultaneously recorded for \u226515 minutes using a radial artery catheter (invasive) and a continuous noninvasive arterial pressure monitor. Beat-to-beat systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure (PP), and mean arterial pressure (MAP) time series were extracted from the continuous waveforms. Complexity was assessed using the multiscale entropy method. The Wilcoxon signed-rank test was used to compare the mean ranks of indices derived from invasive versus noninvasive ABP time series. Spearman correlation coefficients were used to quantify the relationship between invasive and noninvasive indices. Linear regression analysis was used to quantify the association between each of the complexity indices and the STS risk scores.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>RESULTS:<\/jats:title>\n            <jats:p>Beat-to-beat fluctuations in noninvasive ABP measurements were not random but complex; however, their degree of complexity was lower than that of fluctuations in invasively obtained ABP signals (SBP: 7.05 vs 8.66, <jats:italic toggle=\"yes\">P<\/jats:italic> &lt; .001; DBP: 7.40 vs 8.41, <jats:italic toggle=\"yes\">P<\/jats:italic> &lt; .001; PP: 6.83 vs 8.82, <jats:italic toggle=\"yes\">P<\/jats:italic> &lt; .001; and MAP: 7.17 vs 8.68, <jats:italic toggle=\"yes\">P<\/jats:italic> &lt; .005). Invasive and noninvasive indices for MSE<jats:sub>\u03a3\u00b7slope<\/jats:sub> showed good correlation (<jats:italic toggle=\"yes\">r<\/jats:italic>\n                                 <jats:sub>s<\/jats:sub>) (0.53 for SBP, 0.79 for DBP, 0.42 for PP, 0.60 for MAP). The complexity of noninvasive ABP time series (\u22120.70 [\u22121.28 to \u22120.11]; <jats:italic toggle=\"yes\">P<\/jats:italic> = .023 for DBP), like that of invasive time series (\u22120.94 [\u22121.52 to \u22120.35]; <jats:italic toggle=\"yes\">P<\/jats:italic> = .004 for DBP), was inversely associated with estimated surgical risk in patients undergoing cardiovascular operations.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>CONCLUSIONS:<\/jats:title>\n            <jats:p>Our results support the use of noninvasive ABP monitoring in computations of complexity-based indices that correlate with estimated surgical risk.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1213\/ane.0000000000003894","type":"journal-article","created":{"date-parts":[[2018,11,6]],"date-time":"2018-11-06T20:18:17Z","timestamp":1541535497000},"page":"1653-1660","source":"Crossref","is-referenced-by-count":13,"title":["Comparison of Invasive and Noninvasive Blood Pressure Measurements for Assessing Signal Complexity and Surgical Risk in Cardiac Surgical Patients"],"prefix":"10.1213","volume":"130","author":[{"given":"Lauren E.","family":"Gibson","sequence":"first","affiliation":[{"name":"Department of Anesthesia, Critical Care, and Pain Medicine, Center for Anesthesia Research & Excellence (CARE), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts"}]},{"given":"Teresa S.","family":"Henriques","sequence":"additional","affiliation":[{"name":"Department of Anesthesia, Critical Care, and Pain Medicine, Center for Anesthesia Research & Excellence (CARE), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts"},{"name":"Margret and H.A. Rey Institute of Nonlinear Dynamics in Physiology and Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts"}]},{"given":"Madalena D.","family":"Costa","sequence":"additional","affiliation":[{"name":"Margret and H.A. Rey Institute of Nonlinear Dynamics in Physiology and Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts"}]},{"given":"Roger B.","family":"Davis","sequence":"additional","affiliation":[{"name":"Division of General Medicine and Primary Care, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts"}]},{"given":"Murray A.","family":"Mittleman","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts."}]},{"given":"Pooja","family":"Mathur","sequence":"additional","affiliation":[{"name":"Department of Anesthesia, Critical Care, and Pain Medicine, Center for Anesthesia Research & Excellence (CARE), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts"}]},{"given":"Balachundhar","family":"Subramaniam","sequence":"additional","affiliation":[{"name":"Department of Anesthesia, Critical Care, and Pain Medicine, Center for Anesthesia Research & Excellence (CARE), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts"}]}],"member":"276","reference":[{"key":"R1-20230721","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1186\/cc1489","article-title":"Clinical review: complications and risk factors of peripheral arterial catheters used for haemodynamic monitoring in anaesthesia and intensive care medicine.","volume":"6","author":"Scheer","year":"2002","journal-title":"Crit Care"},{"key":"R2-20230721","first-page":"22201","article-title":"American National Standard. Manual, electronic or automated sphygmomanometers.","volume":"1","year":"2002","journal-title":"ANSI"},{"key":"R3-20230721","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.1097\/ALN.0000000000000226","article-title":"Accuracy and precision of continuous noninvasive arterial pressure monitoring compared with invasive arterial pressure: a systematic review and meta-analysis.","volume":"120","author":"Kim","year":"2014","journal-title":"Anesthesiology"},{"key":"R4-20230721","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1113\/expphysiol.2005.030262","article-title":"Non-invasive pulsatile arterial pressure and stroke volume changes from the human finger.","volume":"90","author":"Bogert","year":"2005","journal-title":"Exp Physiol"},{"key":"R5-20230721","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10877-014-9619-x","article-title":"Continuous noninvasive arterial pressure measurement using the volume clamp method: an evaluation of the CNAP device in intensive care unit patients.","volume":"1","author":"Wagner","year":"2015","journal-title":"J Clin Monit Comput"},{"key":"R6-20230721","doi-asserted-by":"crossref","first-page":"21","DOI":"10.4103\/0019-5049.149444","article-title":"Evaluation of continuous non-invasive arterial pressure monitoring during induction of general anaesthesia in patients undergoing cardiac surgery.","volume":"59","author":"Kumar","year":"2015","journal-title":"Indian J Anaesth"},{"key":"R7-20230721","doi-asserted-by":"crossref","first-page":"180","DOI":"10.4103\/0971-9784.97973","article-title":"A comparison of a continuous noninvasive arterial pressure (CNAP\u2122) monitor with an invasive arterial blood pressure monitor in the cardiac surgical ICU.","volume":"15","author":"Jagadeesh","year":"2012","journal-title":"Ann Card Anaesth"},{"key":"R8-20230721","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1001\/jamasurg.2014.1700","article-title":"Changes over time in risk profiles of patients who undergo coronary artery bypass graft surgery: the Veterans Affairs Surgical Quality Improvement Program (VASQIP).","volume":"150","author":"Cornwell","year":"2015","journal-title":"JAMA Surg"},{"key":"R9-20230721","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1016\/0003-4975(94)90355-7","article-title":"First publications from the Society of Thoracic Surgeons National Database.","volume":"57","author":"Anderson","year":"1994","journal-title":"Ann Thorac Surg"},{"key":"R10-20230721","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.jtcvs.2007.09.011","article-title":"Reliability of risk algorithms in predicting early and late operative outcomes in high-risk patients undergoing aortic valve replacement.","volume":"135","author":"Dewey","year":"2008","journal-title":"J Thorac Cardiovasc Surg"},{"key":"R11-20230721","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/S1010-7940(01)01117-4","article-title":"Inaccuracy of four coronary surgery risk-adjusted models to predict mortality in individual patients.","volume":"21","author":"Pinna-Pintor","year":"2002","journal-title":"Eur J Cardiothorac Surg"},{"key":"R12-20230721","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1053\/j.jvca.2013.11.014","article-title":"Blood pressure variability: can nonlinear dynamics enhance risk assessment during cardiovascular surgery?","volume":"28","author":"Subramaniam","year":"2014","journal-title":"J Cardiothorac Vasc Anesth"},{"key":"R13-20230721","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":"R14-20230721","doi-asserted-by":"crossref","first-page":"021906","DOI":"10.1103\/PhysRevE.71.021906","article-title":"Multiscale entropy analysis of biological signals.","volume":"71","author":"Costa","year":"2005","journal-title":"Phys Rev E Stat Nonlin Soft Matter Phys"},{"key":"R15-20230721","article-title":"Complexity of preoperative blood pressure dynamics: possible utility in cardiac surgical risk assessment.","author":"Henriques","year":"2018","journal-title":"J Clin Monit Comput"},{"key":"R16-20230721","doi-asserted-by":"crossref","first-page":"E215","DOI":"10.1161\/01.CIR.101.23.e215","article-title":"PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals.","volume":"101","author":"Goldberger","year":"2000","journal-title":"Circulation"},{"key":"R17-20230721","first-page":"259","article-title":"An open-source algorithm to detect onset of arterial blood pressure pulses.","volume":"30","author":"Zong","year":"2003","journal-title":"Comput Cardiol"},{"key":"R18-20230721","doi-asserted-by":"crossref","first-page":"H2039","DOI":"10.1152\/ajpheart.2000.278.6.H2039","article-title":"Physiological time-series analysis using approximate entropy and sample entropy.","volume":"278","author":"Richman","year":"2000","journal-title":"Am J Physiol Heart Circ Physiol"},{"key":"R20-20230721","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1093\/bja\/aeq143","article-title":"Precision and accuracy of a new device (CNAPTM) for continuous non-invasive arterial pressure monitoring: assessment during general anaesthesia.","volume":"105","author":"Jeleazcov","year":"2010","journal-title":"Br J Anaesth"}],"container-title":["Anesthesia &amp; Analgesia"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.lww.com\/10.1213\/ANE.0000000000003894","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,21]],"date-time":"2023-07-21T14:07:32Z","timestamp":1689948452000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.lww.com\/10.1213\/ANE.0000000000003894"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6]]},"references-count":19,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2020]]}},"URL":"https:\/\/doi.org\/10.1213\/ane.0000000000003894","relation":{},"ISSN":["0003-2999"],"issn-type":[{"value":"0003-2999","type":"print"}],"subject":[],"published":{"date-parts":[[2020,6]]}}}