{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T18:08:37Z","timestamp":1776276517128,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T00:00:00Z","timestamp":1648598400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"US Army Medical Research and Medical Command","award":["D-022-2011-USAISR and D-009-2014-USAISR"],"award-info":[{"award-number":["D-022-2011-USAISR and D-009-2014-USAISR"]}]},{"name":"Congressionally Directed Medical Research Program","award":["DM180240"],"award-info":[{"award-number":["DM180240"]}]},{"name":"Office of Naval Research and Naval Information Warfare Systems Command","award":["No. N66001-12-D-0088, N00014-18-D-7001, N00014-19-C-2017"],"award-info":[{"award-number":["No. N66001-12-D-0088, N00014-18-D-7001, N00014-19-C-2017"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The application of artificial intelligence (AI) has provided new capabilities to develop advanced medical monitoring sensors for detection of clinical conditions of low circulating blood volume such as hemorrhage. The purpose of this study was to compare for the first time the discriminative ability of two machine learning (ML) algorithms based on real-time feature analysis of arterial waveforms obtained from a non-invasive continuous blood pressure system (Finometer\u00ae) signal to predict the onset of decompensated shock: the compensatory reserve index (CRI) and the compensatory reserve metric (CRM). One hundred ninety-one healthy volunteers underwent progressive simulated hemorrhage using lower body negative pressure (LBNP). The least squares means and standard deviations for each measure were assessed by LBNP level and stratified by tolerance status (high vs. low tolerance to central hypovolemia). Generalized Linear Mixed Models were used to perform repeated measures logistic regression analysis by regressing the onset of decompensated shock on CRI and CRM. Sensitivity and specificity were assessed by calculation of receiver-operating characteristic (ROC) area under the curve (AUC) for CRI and CRM. Values for CRI and CRM were not distinguishable across levels of LBNP independent of LBNP tolerance classification, with CRM ROC AUC (0.9268) being statistically similar (p = 0.134) to CRI ROC AUC (0.9164). Both CRI and CRM ML algorithms displayed discriminative ability to predict decompensated shock to include individual subjects with varying levels of tolerance to central hypovolemia. Arterial waveform feature analysis provides a highly sensitive and specific monitoring approach for the detection of ongoing hemorrhage, particularly for those patients at greatest risk for early onset of decompensated shock and requirement for implementation of life-saving interventions.<\/jats:p>","DOI":"10.3390\/s22072642","type":"journal-article","created":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T21:28:39Z","timestamp":1648675719000},"page":"2642","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["AI-Enabled Advanced Development for Assessing Low Circulating Blood Volume for Emergency Medical Care: Comparison of Compensatory Reserve Machine-Learning Algorithms"],"prefix":"10.3390","volume":"22","author":[{"given":"Victor A.","family":"Convertino","sequence":"first","affiliation":[{"name":"Battlefield Health & Trauma Center for Human Integrative Physiology, US Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA"},{"name":"Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA"},{"name":"Department of Emergency Medicine, University of Texas Health, San Antonio, TX 77030, USA"}]},{"given":"Robert W.","family":"Techentin","sequence":"additional","affiliation":[{"name":"Special Purpose Processor Development Group, Mayo Clinic, Rochester, MN 55902, USA"}]},{"given":"Ruth J.","family":"Poole","sequence":"additional","affiliation":[{"name":"Special Purpose Processor Development Group, Mayo Clinic, Rochester, MN 55902, USA"}]},{"given":"Ashley C.","family":"Dacy","sequence":"additional","affiliation":[{"name":"Naval Medical Research Unit-San Antonio, JBSA Fort Sam Houston, San Antonio, TX 78234, USA"}]},{"given":"Ashli N.","family":"Carlson","sequence":"additional","affiliation":[{"name":"Battlefield Health & Trauma Center for Human Integrative Physiology, US Army Institute of Surgical Research, JBSA Fort Sam Houston, San Antonio, TX 78234, USA"}]},{"given":"Sylvain","family":"Cardin","sequence":"additional","affiliation":[{"name":"Naval Medical Research Unit-San Antonio, JBSA Fort Sam Houston, San Antonio, TX 78234, USA"}]},{"given":"Clifton R.","family":"Haider","sequence":"additional","affiliation":[{"name":"Special Purpose Processor Development Group, Mayo Clinic, Rochester, MN 55902, USA"}]},{"given":"David R.","family":"Holmes III","sequence":"additional","affiliation":[{"name":"Biomedical Analytics and Computational Engineering Laboratory, Mayo Clinic, Rochester, MN 55902, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6458-0142","authenticated-orcid":false,"given":"Chad C.","family":"Wiggins","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN 55902, USA"}]},{"given":"Michael J.","family":"Joyner","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN 55902, USA"}]},{"given":"Timothy B.","family":"Curry","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN 55902, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7952-1794","authenticated-orcid":false,"given":"Omer T.","family":"Inan","sequence":"additional","affiliation":[{"name":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,30]]},"reference":[{"key":"ref_1","first-page":"1531","article-title":"The physiology of human hemorrhage and compensation","volume":"11","author":"Convertino","year":"2020","journal-title":"Comp. Physiol."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Convertino, V.A., Schauer, S.G., Weitzel, E.K., Cardin, S., Stackle, M.E., Talley, M.J., Sawka, M.N., and Inan, O.T. (2020). Wearable sensors integrated with compensatory reserve monitoring in critically injured trauma patients. Sensors, 20.","DOI":"10.3390\/s20226413"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"S150","DOI":"10.1111\/trf.15632","article-title":"The compensatory reserve: Potential for accurate individualized goal-directed whole blood resuscitation","volume":"60","author":"Convertino","year":"2020","journal-title":"Transfusion"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1196","DOI":"10.1152\/japplphysiol.00668.2013","article-title":"Estimation of individual-specific progression to impending cardiovascular instability using arterial waveforms","volume":"115","author":"Convertino","year":"2013","journal-title":"J. Appl. Physiol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1097\/SHK.0000000000000559","article-title":"The compensatory reserve for early and accurate prediction of hemodynamic compromise: A review of the underlying physiology","volume":"45","author":"Convertino","year":"2016","journal-title":"Shock"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"S57","DOI":"10.1097\/TA.0000000000001430","article-title":"Measuring the compensatory reserve to identify shock","volume":"82","author":"Convertino","year":"2017","journal-title":"J. Trauma Acute Care Surg."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1097\/TA.0b013e3182aa811a","article-title":"Running on empty? The compensatory reserve index","volume":"75","author":"Moulton","year":"2013","journal-title":"J. Trauma Acute Care Surg."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1097\/SHK.0000000000000323","article-title":"A novel measurement for accurate assessment of clinical status in patients with significant blood loss: The compensatory reserve","volume":"44","author":"Convertino","year":"2015","journal-title":"Shock"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1097\/SHK.0000000000000632","article-title":"Specificity of compensatory reserve and tissue oxygenation as early predictors of tolerance to progressive reductions in central blood volume","volume":"46","author":"Howard","year":"2016","journal-title":"Shock"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1097\/SHK.0000000000000480","article-title":"Predictors of the onset of hemodynamic decompensation during progressive central hypovolemia: Comparison of the peripheral perfusion index, pulse pressure variability, and compensatory reserve index","volume":"44","author":"Janak","year":"2015","journal-title":"Shock"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1097\/SHK.0000000000001034","article-title":"Comparisons of traditional metabolic markers and compensatory reserve as early predictors of tolerance to central hypovolemia in humans","volume":"50","author":"Schiller","year":"2018","journal-title":"Shock"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"892","DOI":"10.1097\/TA.0000000000000423","article-title":"Detection of low-volume blood loss: The compensatory reserve index versus traditional vital signs","volume":"77","author":"Stewart","year":"2014","journal-title":"J. Trauma Acute Care Surg."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"S161","DOI":"10.1097\/TA.0000000000002605","article-title":"Predictors of hemodynamic decompensation in progressive hypovolemia: Compensatory reserve versus heart rate variability","volume":"89","author":"Schlotman","year":"2020","journal-title":"J. Trauma Acute Care Surg."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"S169","DOI":"10.1097\/TA.0000000000002586","article-title":"Validating clinical threshold values for a dashboard view of the compensatory reserve measurement for hemorrhage detection","volume":"89","author":"Convertino","year":"2020","journal-title":"J. Trauma Acute Care Surg."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1097\/SHK.0000000000000959","article-title":"Compensatory reserve index: Performance of a novel monitoring technology to identify the bleeding trauma patient","volume":"49","author":"Johnson","year":"2018","journal-title":"Shock"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1097\/SHK.0000000000000178","article-title":"The value of non-invasive mesurement of the compensatory reserve index in monitoring and triage of patients experiencing minimal blood loss","volume":"42","author":"Nadler","year":"2014","journal-title":"Shock"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"S71","DOI":"10.1097\/TA.0000000000001474","article-title":"The effect of blood transfusion on compensatory reserve: A prospective clinical trial","volume":"83","author":"Benov","year":"2017","journal-title":"J. Trauma Acute Care Surg."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"S153","DOI":"10.1097\/TA.0000000000002648","article-title":"Evaluation of sepsis using compensatory reserve measurement: A prospective clinical trial","volume":"89","author":"Benov","year":"2020","journal-title":"J. Trauma Acute Care Surg."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"S167","DOI":"10.1111\/trf.16494","article-title":"Compensatory reserve detects subclinical phases of shock with more expeditious prediction for need of life-saving interventions compared to vital signs and arterial lactate","volume":"61","author":"Convertino","year":"2021","journal-title":"Transfusion"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"S174","DOI":"10.1111\/trf.16498","article-title":"Efficacy of the compensatory reserve measurement in an emergency department trauma population","volume":"61","author":"Schauer","year":"2021","journal-title":"Transfusion"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"874","DOI":"10.1177\/1535370217694099","article-title":"The physiology of blood loss and shock: New insights from a human laboratory model of hemorrhage","volume":"242","author":"Schiller","year":"2017","journal-title":"Exp. Biol. Med."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1152\/japplphysiol.00640.2013","article-title":"Validation of lower body negative pressure as an experimental model of hemorrhage","volume":"116","author":"Shade","year":"2014","journal-title":"J. Appl. Physiol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/s10286-011-0151-5","article-title":"Autonomic mechanisms associated with heart rate and vasoconstrictor reserves","volume":"22","author":"Convertino","year":"2012","journal-title":"Clin. Auton. Res."},{"key":"ref_24","first-page":"R837","article-title":"Application of acute maximal exercise to protect orthostatic tolerance after simulated microgravity","volume":"271","author":"Engelke","year":"1996","journal-title":"Am. J. Physiol."},{"key":"ref_25","first-page":"73","article-title":"G-Factor as a tool in basic research: Mechanisms of orthostatic tolerance","volume":"6","author":"Convertino","year":"1999","journal-title":"J. Gravit. Physiol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"H609","DOI":"10.1152\/ajpheart.00420.2018","article-title":"Differentiating compensatory mechanisms associated with low tolerance to central hypovolemia in women","volume":"316","author":"Schlotman","year":"2019","journal-title":"Am. J. Physiol. Heart Circ. Physiol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"614","DOI":"10.3357\/ASEM.3204.2012","article-title":"Blood pressure measurement for accurate assessment of patient status in emergency medical settings","volume":"83","author":"Convertino","year":"2012","journal-title":"Aviat. Space Environ. Med."},{"key":"ref_28","first-page":"S25","article-title":"Use of advanced machine-learning techniques for non-invasive monitoring of hemorrhage","volume":"71","author":"Convertino","year":"2011","journal-title":"J. Trauma"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"R1154","DOI":"10.1152\/ajpregu.00304.2015","article-title":"Comparison of comensatory reserve during lower-body negative pressure and hemorrhage in nonhuman primates","volume":"310","author":"Howard","year":"2016","journal-title":"Am. J. Physiol. Regul. Integr. Comp. Physiol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"807","DOI":"10.1152\/physrev.00006.2018","article-title":"Lower body negative pressure: Physiological effects, applications and implementations","volume":"99","author":"Goswami","year":"2019","journal-title":"Physiol. Rev."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1152\/japplphysiol.00070.2014","article-title":"Reductions in central venous pressure by lower body negative pressure or blood loss elicit similar hemodynamic responses","volume":"117","author":"Johnson","year":"2014","journal-title":"J. Appl. Physiol."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Techentin, R.W., Felton, C.L., Schlotman, T.E., Gilbert, B.K., Joyner, M.J., Curry, T.B., Convertino, V.A., Holmes, D.R., and Haider, C.R. (2019, January 23\u201327). 1D Convolutional neural networks for estimation of compensatory reserve from blood pressure waveforms. Proceedings of the 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany.","DOI":"10.1109\/EMBC.2019.8857116"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/S0167-5877(00)00115-X","article-title":"Principles and practical application of the receiver-operating characteristic analysis for diagnostic tests","volume":"45","author":"Greiner","year":"2000","journal-title":"Prev. Vet. Med."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1097\/SHK.0000000000000647","article-title":"The Compensatory reserve index following injury: Results of a prospective clinical trial","volume":"46","author":"Stewart","year":"2016","journal-title":"Shock"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1097\/MCC.0b013e32836091ae","article-title":"Haemodynamic monitoring using arterial waveform analysis","volume":"19","author":"Chew","year":"2013","journal-title":"Curr. Opin. Crit. Care"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1097\/ALN.0000000000002300","article-title":"Machine-learning algorithm to predict hypotension based on high-fidelity arterial pressure waveform analysis","volume":"129","author":"Hatib","year":"2018","journal-title":"Anesthesiology"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"766","DOI":"10.1213\/ANE.0b013e31822773ec","article-title":"Arterial waveform analysis for the anesthesiologist: Past, present, and future concepts","volume":"113","author":"Thiele","year":"2011","journal-title":"Anesth. Analg."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1097\/ALN.0b013e31816c89e1","article-title":"Utility of the photoplethysmogram in circulatory monitoring","volume":"108","author":"Reisner","year":"2008","journal-title":"Anesthesiology"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1379","DOI":"10.1097\/TA.0000000000000235","article-title":"Automated prediction of early blood transfusion and mortality in trauma patients","volume":"76","author":"Mackenzie","year":"2014","journal-title":"J. Trauma Acute Care Surg."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/7\/2642\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:46:19Z","timestamp":1760136379000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/7\/2642"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,30]]},"references-count":39,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["s22072642"],"URL":"https:\/\/doi.org\/10.3390\/s22072642","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,30]]}}}