{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T23:11:41Z","timestamp":1781133101238,"version":"3.54.1"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"S17","license":[{"start":{"date-parts":[[2020,12,1]],"date-time":"2020-12-01T00:00:00Z","timestamp":1606780800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2020,12,14]],"date-time":"2020-12-14T00:00:00Z","timestamp":1607904000000},"content-version":"vor","delay-in-days":13,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Prediction of patient outcome in medical intensive care units (ICU) may help for development and investigation of early interventional strategies. Several ICU scoring systems have been developed and are used to predict clinical outcome of ICU patients. These scores are calculated from clinical physiological and biochemical characteristics of patients. Heart rate variability (HRV) is a correlate of cardiac autonomic regulation and has been evident as a marker of poor clinical prognosis. HRV can be measured from the electrocardiogram non-invasively and monitored in real time. HRV has been identified as a promising \u2018electronic biomarker\u2019 of disease severity. Traumatic brain injury (TBI) is a subset of critically ill patients admitted to ICU, with significant morbidity and mortality, and often difficult to predict outcomes. Changes of HRV for brain injured patients have been reported in several studies. This study aimed to utilize the continuous HRV collection from admission across the first 24\u00a0h in the ICU in severe TBI patients to develop a patient outcome prediction system.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>A feature extraction strategy was applied to measure the HRV fluctuation during time. A prediction model was developed based on HRV measures with\u00a0a genetic algorithm for feature selection. The result (AUC: 0.77) was compared with earlier reported scoring systems (highest AUC: 0.76), encouraging further development and practical application.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>The prediction models built with different feature sets indicated that HRV based parameters may help predict brain injury patient outcome better than the previously adopted illness severity scores.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-020-03814-w","type":"journal-article","created":{"date-parts":[[2020,12,14]],"date-time":"2020-12-14T01:02:38Z","timestamp":1607907758000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Utilizing heart rate variability to predict ICU patient outcome in traumatic brain injury"],"prefix":"10.1186","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3907-1127","authenticated-orcid":false,"given":"Ping","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tegan","family":"Roberts","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brent","family":"Richards","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luke J.","family":"Haseler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,12,14]]},"reference":[{"key":"3814_CR1","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1016\/S1474-4422(18)30415-0","volume":"18","author":"GBD 2016 Traumatic Brain Injury and Spinal Cord Injury Collaborators","year":"2019","unstructured":"GBD 2016 Traumatic Brain Injury and Spinal Cord Injury Collaborators. Global, regional, and national burden of traumatic brain injury and spinal cord injury, 1990\u20132016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18:56\u201387.","journal-title":"Lancet Neurol"},{"key":"3814_CR2","unstructured":"World Health Organization. Violence and injury prevention and disability. https:\/\/www.who.int\/violence_injury_prevention\/road_traffic\/activities\/neurotrauma\/en\/. Accessed 5 June 2020."},{"issue":"8","key":"3814_CR3","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1097\/00003246-198108000-00008","volume":"9","author":"W Knaus","year":"1981","unstructured":"Knaus W, Zimmerman J, Wagner D, Draper E, Lawrence D. APACHE-acute physiology and chronic health evaluation: a physiologically based classification system. Crit Care Med. 1981;9(8):591\u20137.","journal-title":"Crit Care Med"},{"issue":"10","key":"3814_CR4","doi-asserted-by":"publisher","first-page":"818","DOI":"10.1097\/00003246-198510000-00009","volume":"13","author":"W Knaus","year":"1985","unstructured":"Knaus W, Draper E, Wagner D, Zimmerman J. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13(10):818\u201329.","journal-title":"Crit Care Med"},{"issue":"6","key":"3814_CR5","doi-asserted-by":"publisher","first-page":"1619","DOI":"10.1378\/chest.100.6.1619","volume":"100","author":"W Knaus","year":"1991","unstructured":"Knaus W, Wagner D, Draper E, Zimmerman J, Bergner M, Bastos P, Sirio C, Murphy D, Lotring T, Damiano A, Harrell J. The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. Chest. 1991;100(6):1619\u201336.","journal-title":"Chest"},{"issue":"5","key":"3814_CR6","doi-asserted-by":"publisher","first-page":"1297","DOI":"10.1097\/01.CCM.0000215112.84523.F0","volume":"34","author":"J Zimmerman","year":"2006","unstructured":"Zimmerman J, Kramer A, McNair D, Malila F. Acute Physiology and Chronic Health Evaluation (APACHE) IV: hospital mortality assessment for today\u2019s critically ill patients. Crit Care Med. 2006;34(5):1297\u2013310.","journal-title":"Crit Care Med"},{"issue":"24","key":"3814_CR7","doi-asserted-by":"publisher","first-page":"2957","DOI":"10.1001\/jama.1993.03510240069035","volume":"270","author":"J Le Gall","year":"1993","unstructured":"Le Gall J, Lemeshow S, Saulnier F. A new Simplified Acute Physiology Score (SAPS II) based on a European\/North American multicenter study. JAMA. 1993;270(24):2957\u201363.","journal-title":"JAMA"},{"issue":"10","key":"3814_CR8","doi-asserted-by":"publisher","first-page":"1638","DOI":"10.1097\/00003246-199510000-00007","volume":"23","author":"J Marshall","year":"1995","unstructured":"Marshall J, Cook D, Christou N, Bernard G, Sprung C, Sibbald W. Multiple organ dysfunction score: a reliable descriptor of a complex clinical outcome. Crit Care Med. 1995;23(10):1638\u201352.","journal-title":"Crit Care Med"},{"issue":"7","key":"3814_CR9","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1007\/BF01709751","volume":"22","author":"J Vincent","year":"1996","unstructured":"Vincent J, Moreno R, Takala J, Willatts S, De Mendon\u00e7a A, Bruining H, Reinhart C, Suter P, Thijs L. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction\/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996;22(7):707\u201310.","journal-title":"Intensive Care Med"},{"issue":"3","key":"3814_CR10","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1097\/00005373-197403000-00001","volume":"14","author":"S Baker","year":"1974","unstructured":"Baker S, O\u2019Neill B, Haddon W, Long W. The Injury Severity Score: a method for describing patients with multiple injuries and evaluating emergency care. J Trauma. 1974;14(3):187\u201396.","journal-title":"J Trauma"},{"issue":"1","key":"3814_CR11","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1097\/00005373-198801000-00010","volume":"28","author":"W Copes","year":"1988","unstructured":"Copes W, Champion H, Sacco W, Lawnick M, Keast S, Bain L. The injury severity score revisited. J Trauma. 1988;28(1):69\u201377.","journal-title":"J Trauma"},{"issue":"4","key":"3814_CR12","doi-asserted-by":"publisher","first-page":"220","DOI":"10.4103\/0972-5229.130573","volume":"18","author":"A Rapsang","year":"2014","unstructured":"Rapsang A, Shyam D. Scoring systems in the intensive care unit: a compendium. Indian J Crit Care Med. 2014;18(4):220\u20138.","journal-title":"Indian J Crit Care Med"},{"key":"3814_CR13","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1186\/s40560-016-0143-6","volume":"4","author":"R Kao","year":"2016","unstructured":"Kao R, Priestap F, Donner A. To develop a regional ICU mortality prediction model during the first 24 h of ICU admission utilizing MODS and NEMS with six other independent variables from the Critical Care Information System (CCIS) Ontario, Canada. J Intensive Care. 2016;4:16.","journal-title":"J Intensive Care"},{"issue":"7","key":"3814_CR14","doi-asserted-by":"publisher","first-page":"1177","DOI":"10.1097\/00003246-199507000-00005","volume":"23","author":"DCS Wong","year":"1995","unstructured":"Wong DCS, Gomez M, McGuire GP, Byrick RJ. Evaluation of predictive ability of APACHE II system and hospital outcome in Canadian intensive care unit patients. Crit Care Med. 1995;23(7):1177\u201383.","journal-title":"Crit Care Med"},{"issue":"6","key":"3814_CR15","doi-asserted-by":"publisher","first-page":"574","DOI":"10.1007\/s001340050618","volume":"24","author":"R Rivera-Fern\u00e1ndez","year":"1998","unstructured":"Rivera-Fern\u00e1ndez R, V\u00e1zquez-Mata G, Bravo M, Aguayo-Hoyos E, Zimmerman J, Wagner D, Knaus W. The Apache III prognostic system: customized mortality predictions for Spanish ICU patients. Intensive Care Med. 1998;24(6):574\u201381.","journal-title":"Intensive Care Med"},{"key":"3814_CR16","doi-asserted-by":"publisher","first-page":"R161","DOI":"10.1186\/cc7160","volume":"12","author":"L Minne","year":"2008","unstructured":"Minne L, Abu-Hanna A, de Jonge E. Evaluation of SOFA-based models for predicting mortality in the ICU: a systematic review. Crit Care. 2008;12:R161.","journal-title":"Crit Care"},{"issue":"2","key":"3814_CR17","doi-asserted-by":"publisher","first-page":"102","DOI":"10.4266\/acc.2018.00185","volume":"33","author":"S Jeong","year":"2018","unstructured":"Jeong S. Scoring systems for the patients of intensive care unit. Acute Crit Care. 2018;33(2):102\u20134.","journal-title":"Acute Crit Care"},{"key":"3814_CR18","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1016\/j.ijmedinf.2019.07.002","volume":"129","author":"J Todd","year":"2019","unstructured":"Todd J, Gepp A, Richards B, Vanstone BJ. Improving mortality models in the ICU with high-frequency data. Int J Med Inform. 2019;129:318\u201323.","journal-title":"Int J Med Inform"},{"key":"3814_CR19","volume-title":"The essential book of traditional chinese medicine: clinical practice","author":"Y Liu","year":"1988","unstructured":"Liu Y. The essential book of traditional chinese medicine: clinical practice, vol. 2. New York: Columbia University Press; 1988."},{"key":"3814_CR20","doi-asserted-by":"publisher","first-page":"1043","DOI":"10.1161\/01.CIR.93.5.1043","volume":"93","author":"Task Force of the European Society of Cardiology the North American Society of Pacing Electrophysiology","year":"1996","unstructured":"Task Force of the European Society of Cardiology the North American Society of Pacing Electrophysiology. Heart rate variability: standards of measurement, physiological interpretation, and clinical use. Circulation. 1996;93:1043\u201365.","journal-title":"Circulation"},{"key":"3814_CR21","doi-asserted-by":"publisher","first-page":"258","DOI":"10.3389\/fpubh.2017.00258","volume":"5","author":"F Shaffer","year":"2017","unstructured":"Shaffer F, Ginsberg J. An overview of heart rate variability metrics and norms. Front Public Health. 2017;5:258. https:\/\/doi.org\/10.3389\/fpubh.2017.00258.","journal-title":"Front Public Health"},{"issue":"6","key":"3814_CR22","doi-asserted-by":"publisher","first-page":"774","DOI":"10.1017\/cjn.2016.290","volume":"43","author":"R Nguyen","year":"2016","unstructured":"Nguyen R, Fiest KM, McChesney J, Kwon CS, Jette N, Frolkis AD, Gallagher C. The international incidence of traumatic brain injury: a systematic review and meta-analysis. Can J Neurol Sci. 2016;43(6):774\u201385.","journal-title":"Can J Neurol Sci"},{"key":"3814_CR23","unstructured":"World Health Organisation. Injuries and violences the facts. https:\/\/apps.who.int\/iris\/bitstream\/handle\/10665\/149798\/9789241508018_eng.pdf?sequence=1&isAllowed=y,2014. Accessed 27 Sept 2019."},{"issue":"6","key":"3814_CR24","doi-asserted-by":"publisher","first-page":"927","DOI":"10.1097\/00005373-199712000-00010","volume":"43","author":"R Winchell","year":"1997","unstructured":"Winchell R, Hoyt D. Analysis of heart-rate variability: a noninvasive predictor of death and poor outcome in patients with severe head injury. J Trauma. 1997;43(6):927\u201333.","journal-title":"J Trauma"},{"issue":"12","key":"3814_CR25","doi-asserted-by":"publisher","first-page":"3907","DOI":"10.1097\/00003246-200012000-00030","volume":"28","author":"A Biswas","year":"2000","unstructured":"Biswas A, Sommerauer SWJ, Luckett P. Heart rate variability after acute traumatic brain injury in children. Crit Care Med. 2000;28(12):3907\u201312.","journal-title":"Crit Care Med"},{"issue":"6","key":"3814_CR26","doi-asserted-by":"publisher","first-page":"1173","DOI":"10.1097\/CCM.0000000000001624","volume":"44","author":"M Sykora","year":"2016","unstructured":"Sykora M, Czosnyka M, Liu X, Donnelly J, Nasr N, Diedler J, Okoroafor F, Hutchinson P, Menon D, Smielewski P. Autonomic impairment in severe traumatic brain injury: a multimodal neuromonitoring study. Crit Care Med. 2016;44(6):1173\u201381. https:\/\/doi.org\/10.1097\/CCM.0000000000001624.","journal-title":"Crit Care Med"},{"key":"3814_CR27","doi-asserted-by":"publisher","first-page":"626","DOI":"10.1016\/S0140-6736(77)92060-8","volume":"309","author":"R Lowensohn","year":"1977","unstructured":"Lowensohn R, Weiss M, Hon E. Heart-rate variability in brain-damaged adults. Lancet. 1977;309:626\u20138.","journal-title":"Lancet"},{"key":"3814_CR28","doi-asserted-by":"publisher","first-page":"445","DOI":"10.1080\/026990597123421","volume":"11","author":"M King","year":"1997","unstructured":"King M, Lichtman S, Seliger G, Ehert F, Steinberg J. Heart-rate variability in chronic traumatic brain injury. Brain Inj. 1997;11:445\u201353.","journal-title":"Brain Inj"},{"issue":"8","key":"3814_CR29","doi-asserted-by":"publisher","first-page":"605","DOI":"10.1080\/02699050400024946","volume":"19","author":"O Keren","year":"2005","unstructured":"Keren O, Yupatov S, Elad-Yarum RMR, Faraggi D, Abboud S, Ring HGZ. Heart rate variability (HRV) of patients with traumatic brain injury (TBI) during the post-insult sub-acute period. Brain Inj. 2005;19(8):605\u201311.","journal-title":"Brain Inj"},{"key":"3814_CR30","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1007\/s004060050016","volume":"248","author":"H Hildebrandt","year":"1998","unstructured":"Hildebrandt H, Zieger A, Engel A, Fritz K, Bussmann B. Differentiation of autonomic nervous activity in different stages of coma displayed by power spectrum analysis of heart rate variability. Eur Arch Psychiatry Clin Neurosci. 1998;248:46\u201352.","journal-title":"Eur Arch Psychiatry Clin Neurosci"},{"key":"3814_CR31","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1006\/jsre.1996.0214","volume":"63","author":"RJ Winchell","year":"1996","unstructured":"Winchell RJ, Hoyt DB. Spectral analysis of heart rate variability in the ICU: a measure of autonomic function. J Surg Res. 1996;63:11\u20136.","journal-title":"J Surg Res"},{"key":"3814_CR32","doi-asserted-by":"publisher","first-page":"2578","DOI":"10.1097\/00003246-200007000-00066","volume":"28","author":"P Haji-Michael","year":"2000","unstructured":"Haji-Michael P, Degaute VJJ, van de Borne P. Power spectral analysis of cardiovascular variability in critically ill neurosurgical patients. Crit Care Med. 2000;28:2578\u201383.","journal-title":"Crit Care Med"},{"key":"3814_CR33","doi-asserted-by":"publisher","first-page":"747","DOI":"10.1089\/neu.2011.2035","volume":"29","author":"M Kox","year":"2012","unstructured":"Kox M, Vrouwenvelder M, Pompe J, van der Hoeven J, Pickkers P, Hoedemaekers C. The effects of brain injury on heart rate variability and the innate immune response in critically ill patients. J Neurotrauma. 2012;29:747\u201355.","journal-title":"J Neurotrauma"},{"key":"3814_CR34","doi-asserted-by":"publisher","first-page":"306","DOI":"10.1097\/00003246-200202000-00007","volume":"30","author":"C Baillard","year":"2002","unstructured":"Baillard C, Mansier VBP, Mangin L, Jasson S, Riou B, Swynghedauw B. Brain death assessment using instant spectral analysis of heart rate variability. Crit Care Med. 2002;30:306\u201310.","journal-title":"Crit Care Med"},{"issue":"1","key":"3814_CR35","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1097\/PCC.0000000000001759","volume":"20","author":"JA Piantino","year":"2019","unstructured":"Piantino JA, Lin A, Crowder D, Williams CN, Perez-Alday E, Tereshchenko LG, Newgard CD. Early heart rate variability and electroencephalographic abnormalities in acutely brain-injured children who progress to brain death. Pediatr Crit Care Med. 2019;20(1):38\u201346.","journal-title":"Pediatr Crit Care Med"},{"issue":"2","key":"3814_CR36","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1016\/j.aucc.2017.12.011","volume":"31","author":"T Roberts","year":"2018","unstructured":"Roberts T, Richards B, Haseler L, Wells M. Reduced heart rate variability across the first 24 h of intensive care unit in non-survivable traumatic brain injuries. Aust Crit Care. 2018;31(2):115.","journal-title":"Aust Crit Care"},{"issue":"1","key":"3814_CR37","doi-asserted-by":"publisher","first-page":"210220","DOI":"10.1016\/j.cmpb.2013.07.024","volume":"113","author":"M Tarvainen","year":"2014","unstructured":"Tarvainen M, Niskanen J, Lipponen J, Ranta-Aho P, Karjalainen P. Kubios HRV\u2013heart rate variability analysis software. Comput Methods Programs Biomed. 2014;113(1):210220.","journal-title":"Comput Methods Programs Biomed"},{"key":"3814_CR38","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.chemolab.2005.05.004","volume":"80","author":"CD Brown","year":"2006","unstructured":"Brown CD, Davis HT. Receiver operating characteristic curves and related decision measures: a tutorial. Chemom Intell Lab Syst. 2006;80:24\u201338.","journal-title":"Chemom Intell Lab Syst"},{"issue":"1","key":"3814_CR39","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1002\/1097-0142(1950)3:1<32::AID-CNCR2820030106>3.0.CO;2-3","volume":"3","author":"WJ Youden","year":"1950","unstructured":"Youden WJ. Index for rating diagnostic tests. Cancer. 1950;3(1):32\u20135.","journal-title":"Cancer"},{"issue":"7","key":"3814_CR40","doi-asserted-by":"publisher","first-page":"909","DOI":"10.1016\/j.patrec.2004.09.053","volume":"26","author":"P Zhang","year":"2005","unstructured":"Zhang P, Verma B, Kumar K. Neural vs. statistical classifier in conjunction with genetic algorithm based feature selection. Pattern Recognit Lett. 2005;26(7):909\u201319.","journal-title":"Pattern Recognit Lett"},{"key":"3814_CR41","doi-asserted-by":"publisher","first-page":"S11","DOI":"10.1186\/1471-2105-15-S16-S11","volume":"15","author":"P Johnson","year":"2014","unstructured":"Johnson P, Vanderwater L, Wilson W, Maruff P, Savage G, Graham P, Macaulay L, Ellis K, Szeoke C, Martins R, Rowe C, Masters C, Ames D, Zhang P. Genetic algorithm with logistic regression for prediction of progression to Alzheimer\u2019s disease. BMC Bioinform. 2014;15:S11.","journal-title":"BMC Bioinform"},{"issue":"18","key":"3814_CR42","doi-asserted-by":"publisher","first-page":"S1","DOI":"10.1186\/1471-2105-16-S18-S1","volume":"16","author":"L Vandewater","year":"2015","unstructured":"Vandewater L, Brusic V, Wilson W, Macaulay L, Zhang P. An adaptive genetic algorithm for selection of blood-based biomarkers for prediction of Alzheimer\u2019s disease progression. BMC Bioinform. 2015;16(18):S1.","journal-title":"BMC Bioinform"},{"key":"3814_CR43","doi-asserted-by":"crossref","unstructured":"Zhang P, Roberts T, Richards B, Haseler LJ. Predicting intensive care outcomes in traumatic brain injury using heart rate variability measures with feature extraction strategies. In: IEEE international conference on bioinformatics and biomedicine (BIBM), San Diego, CA, USA, pp 2222\u20132227; 2019.","DOI":"10.1109\/BIBM47256.2019.8983177"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-020-03814-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s12859-020-03814-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-020-03814-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,14]],"date-time":"2020-12-14T01:04:08Z","timestamp":1607907848000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-020-03814-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12]]},"references-count":43,"journal-issue":{"issue":"S17","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["3814"],"URL":"https:\/\/doi.org\/10.1186\/s12859-020-03814-w","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12]]},"assertion":[{"value":"6 October 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 October 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 December 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Ethics and Site approval were obtained from the Gold Coast University Hospital Human Research Ethics Committee (HREC\/12\/QGC\/225) (SSA\/15\/QGC\/299). A waiver of consent for patient data collection was granted in the ethics approval.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"Authors have no competing interests relevant to this paper.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"481"}}