Multimodal Monitoring in the Pediatric Intensive Care Unit: New Modalities and Informatics Challenges

Seminars in Pediatric Neurology - Tập 21 - Trang 291-298 - 2014
Zachary M. Grinspan1,2,3,4, Steven Pon2,4, Jeffrey P. Greenfield4,5, Sameer Malhotra3,4,6, Barry E. Kosofsky2,4
1Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY
2Department of Pediatrics, Weill Cornell Medical College, New York, NY;
3Center for Healthcare Informatics and Policy, Weill Cornell Medical College, New York, NY
4New York Presbyterian Hospital, New York, NY
5Department of Neurologic Surgery, Weill Cornell Medical College, New York, NY
6Physician Organization, Weill Cornell Medical College, New York, NY

Tài liệu tham khảo

Kochanek, 2012, Guidelines for the acute medical management of severe traumatic brain injury in infants, children, and adolescents—Second edition, Pediatr Crit Care Med, 13, S1, 10.1097/PCC.0b013e318259ee85 Adler-Milstein, 2014, More than half of US hospitals have at least a basic EHR, but stage 2 criteria remain challenging for most, Health Aff (Millwood), 33, 1664, 10.1377/hlthaff.2014.0453 Geri, 2011, The information age measurement paradox: Collecting too much data, Informing Sci, 14, 47, 10.28945/1356 Hemphill, 2011, Multimodal monitoring and neurocritical care bioinformatics, Nat Rev. Neurol, 7, 451, 10.1038/nrneurol.2011.101 Sivaganesan, 2014, Informatics for neurocritical care: Challenges and opportunities, Neurocrit Care, 20, 132, 10.1007/s12028-013-9872-8 Oddo, 2012, Brain multimodality monitoring: An update, Curr Opin Crit Care, 18, 111, 10.1097/MCC.0b013e32835132a5 Allen, 2014, Age-specific cerebral perfusion pressure thresholds and survival in children and adolescents with severe traumatic brain injury, Pediatr Crit Care Med, 15, 62, 10.1097/PCC.0b013e3182a556ea Meixensberger, 1993, Xenon 133—CBF measurements in severe head injury and subarachnoid haemorrhage, Acta Neurochir Suppl, 59, 28 Stiefel, 2006, Conventional neurocritical care and cerebral oxygenation after traumatic brain injury, J Neurosurg, 105, 568, 10.3171/jns.2006.105.4.568 Cruz, 1995, Cerebral blood flow, vascular resistance, and oxygen metabolism in acute brain trauma: Redefining the role of cerebral perfusion pressure?, Crit Care Med, 23, 1412, 10.1097/00003246-199508000-00016 Figaji, 2008, Does adherence to treatment targets in children with severe traumatic brain injury avoid brain hypoxia? A brain tissue oxygenation study, Neurosurgery, 63, 83, 10.1227/01.NEU.0000335074.39728.00 Brain Trauma Foundation, 2007, Guidelines for the management of severe traumatic brain injury, J Neurotrauma, 24, S1 Bohman, 2011, Medical management of compromised brain oxygen in patients with severe traumatic brain injury, Neurocrit Care, 14, 361, 10.1007/s12028-011-9526-7 Figaji, 2009, Pressure autoregulation, intracranial pressure, and brain tissue oxygenation in children with severe traumatic brain injury, J Neurosurg Pediatr, 4, 420, 10.3171/2009.6.PEDS096 Figaji, 2009, Brain tissue oxygen tension monitoring in pediatric severe traumatic brain injury. Part 1: Relationship with outcome, Childs Nerv Syst, 25, 1325, 10.1007/s00381-009-0822-x Figaji, 2009, Brain tissue oxygen tension monitoring in pediatric severe traumatic brain injury. Part 2: Relationship with clinical, physiological, and treatment factors, Childs Nerv Syst, 25, 1335, 10.1007/s00381-009-0821-y Stippler, 2012, Brain tissue oxygen monitoring after severe traumatic brain injury in children: Relationship to outcome and association with other clinical parameters, J Neurosurg. Pediatr, 10, 383, 10.3171/2012.8.PEDS12165 Figaji, 2014, Oxygen monitoring, J Neurosurg Pediatr, 13, 122, 10.3171/2012.11.PEDS12486 Allen, 2011, Continuous brain tissue oxygenation monitoring in the management of pediatric stroke, Neurocrit Care, 15, 529, 10.1007/s12028-011-9531-x O׳Brien, 2012, Brain tissue oxygenation-guided management of diabetic ketoacidosis induced cerebral edema, Pediatr Crit Care Med, 13, e383, 10.1097/PCC.0b013e3182601132 Robertson, 1995, SjvO2 monitoring in head-injured patients, J Neurotrauma, 12, 891, 10.1089/neu.1995.12.891 Macmillan, 2001, Increased jugular bulb saturation is associated with poor outcome in traumatic brain injury, J Neurol Neurosurg Psychiatry, 70, 101, 10.1136/jnnp.70.1.101 Greisen, 2011, Has the time come to use near-infrared spectroscopy as a routine clinical tool in preterm infants undergoing intensive care?, Philos Transact A Math Phys Eng Sci, 369, 4440, 10.1098/rsta.2011.0261 Moerman, 2010, Near-infrared spectroscopy (NIRS) monitoring in contemporary anesthesia and critical care, Acta Anaesthesiol Belg, 61, 185 Buchner, 2000, Near-infrared spectroscopy—Not useful to monitor cerebral oxygenation after severe brain injury, Zentralbl Neurochir, 61, 69, 10.1055/s-2000-8262 Maeda, 1997, Evaluation of post-mortem oxymetry with reference to the causes of death, Forensic Sci Int, 87, 201, 10.1016/S0379-0738(97)00050-9 Leal-Noval, 2010, Invasive and noninvasive assessment of cerebral oxygenation in patients with severe traumatic brain injury, Intensive Care Med, 36, 1309, 10.1007/s00134-010-1920-7 Carter, 1993, Cerebral blood flow (CBF) monitoring in intensive care by thermal diffusion, Acta Neurochir Suppl, 59, 43 Sioutos, 1995, Continuous regional cerebral cortical blood flow monitoring in head-injured patients, Neurosurgery, 36, 943, 10.1227/00006123-199505000-00009 Vajkoczy, 2003, Regional cerebral blood flow monitoring in the diagnosis of delayed ischemia following aneurysmal subarachnoid hemorrhage, J Neurosurg, 98, 1227, 10.3171/jns.2003.98.6.1227 Ragan, 2013, Alterations in cerebral oxygen metabolism after traumatic brain injury in children, J Cereb Blood Flow Metab, 33, 48, 10.1038/jcbfm.2012.130 Rostami, 2014, Imaging of cerebral blood flow in patients with severe traumatic brain injury in the neurointensive care, Front Neurol, 5, 114, 10.3389/fneur.2014.00114 Sahuquillo, 2014, Lactate and the lactate-to-pyruvate molar ratio cannot be used as independent biomarkers for monitoring brain energetic metabolism: A microdialysis study in patients with traumatic brain injuries, PLoS One, 9, e102540, 10.1371/journal.pone.0102540 Oddo, 2012, Brain lactate metabolism in humans with subarachnoid hemorrhage, Stroke, 43, 1418, 10.1161/STROKEAHA.111.648568 Cesarini, 2002, Early cerebral hyperglycolysis after subarachnoid haemorrhage correlates with favourable outcome, Acta Neurochir (Wien), 144, 1121, 10.1007/s00701-002-1011-9 Timofeev, 2011, Interaction between brain chemistry and physiology after traumatic brain injury: Impact of autoregulation and microdialysis catheter location, J Neurotrauma, 28, 849, 10.1089/neu.2010.1656 Timofeev, 2011, Cerebral extracellular chemistry and outcome following traumatic brain injury: A microdialysis study of 223 patients, Brain, 134, 484, 10.1093/brain/awq353 Charalambides, 2010, Intracerebral microdialysis in children, Childs Nerv Syst, 26, 215, 10.1007/s00381-009-1031-3 Tolias, 2002, Investigation of extracellular amino acid release in children with severe head injury using microdialysis. A pilot study, Acta Neurochir Suppl, 81, 377 Richards, 2003, Extracellular glutamine to glutamate ratio may predict outcome in the injured brain: A clinical microdialysis study in children, Pharmacol Res, 48, 101 Ahlsson, 2004, Treatment of extreme hyperglycemia monitored with intracerebral microdialysis, Pediatr Crit Care Med, 5, 89, 10.1097/01.PCC.0000102396.02043.22 Tay, 2006, Nonconvulsive status epilepticus in children: Clinical and EEG characteristics, Epilepsia, 47, 1504, 10.1111/j.1528-1167.2006.00623.x Arndt, 2013, Subclinical early posttraumatic seizures detected by continuous EEG monitoring in a consecutive pediatric cohort, Epilepsia, 54, 1780, 10.1111/epi.12369 Vespa, 2010, Nonconvulsive seizures after traumatic brain injury are associated with hippocampal atrophy, Neurology, 75, 792, 10.1212/WNL.0b013e3181f07334 Vespa, 2007, Nonconvulsive electrographic seizures after traumatic brain injury result in a delayed, prolonged increase in intracranial pressure and metabolic crisis, Crit Care Med, 35, 2830, 10.1097/01.CCM.0000295667.66853.BC Sanchez, 2013, Electroencephalography monitoring in critically ill children: Current practice and implications for future study design, Epilepsia, 54, 1419, 10.1111/epi.12261 Gallentine, 2013, Utility of continuous EEG in children with acute traumatic brain injury, Journal of clinical neurophysiology: official publication of the American Electroencephalographic Society, 30, 126, 10.1097/WNP.0b013e3182872adf Foreman, 2012, Quantitative EEG for the detection of brain ischemia, Crit Care, 16, 216, 10.1186/cc11230 Kilbride, 2009, How seizure detection by continuous electroencephalographic monitoring affects the prescribing of antiepileptic medications, Arch Neurol, 66, 723, 10.1001/archneurol.2009.100 Ney, 2013, Continuous and routine EEG in intensive care: utilization and outcomes, United States 2005-2009, Neurology, 81, 2002, 10.1212/01.wnl.0000436948.93399.2a Centers for Medicare and Medicaid Services. The Official Web Site for the Medicare and Medicaid Electronic Health Records (EHR) Incentive Programs. Available at: 〈http://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/index.html〉. Accessed Aug 24, 2014 Celi, 2013, “Big data” in the intensive care unit. Closing the data loop, Am J Respir Crit Care Med, 187, 1157, 10.1164/rccm.201212-2311ED Spooner, 2007, Special requirements of electronic health record systems in pediatrics, Pediatrics, 119, 631, 10.1542/peds.2006-3527 Williams, 2012, Achieving interoperability: What׳s happening out there?, Biomed Instrum Technol, 46, 14, 10.2345/0899-8205-46.1.14 Williams, 2009, For the kids: Managing medical equipment in children׳s hospitals, Biomed Instrum Technol, 43, 360, 10.2345/0899-8205-43.5.360 Halpern, 2014, Innovative designs for the smart ICU: Part 3: Advanced ICU informatics, Chest, 145, 903, 10.1378/chest.13-0005 Goldstein, 2003, Physiologic data acquisition system and database for the study of disease dynamics in the intensive care unit, Crit Care Med, 31, 433, 10.1097/01.CCM.0000050285.93097.52 Frisch, 2006, Design of an enterprise-wide physiological and clinical data solution, Conf Proc IEEE Eng Med Biol Soc, 1, 109, 10.1109/IEMBS.2006.259304 Aboukhalil, 2008, Reducing false alarm rates for critical arrhythmias using the arterial blood pressure waveform, J Biomed Inform, 41, 442, 10.1016/j.jbi.2008.03.003 Cao, 2006, A simple non-physiological artifact filter for invasive arterial blood pressure monitoring: A study of 1852 trauma ICU patients, Conf Proc IEEE Eng Med Biol Soc, 1, 1417, 10.1109/IEMBS.2006.260684 Health Level Seven International. http://www.hl7.org ASTM International. F2761-09(2013) Medical Devices and Medical Systems—Essential safety requirements for equipment comprising the patient-centric integrated clinical environment (ICE)—Part 1: General requirements and conceptual model. http://www.astm.org/Standards/F2761.htm Brito, 2010, A sensor middleware for integration of heterogeneous medical devices, Conf Proc IEEE Eng Med Biol Soc, 2010, 5189 Excel Medical Electronics. BedMasterEx. Available at: http://www.excel-medical.com/BedMasterEx. Accessed Aug 24, 2014 Kaye, 2005, When minutes count—The fallacy of accurate time documentation during in-hospital resuscitation, Resuscitation, 65, 285, 10.1016/j.resuscitation.2004.12.020 Ornato, 1998, Synchronization of timepieces to the atomic clock in an urban emergency medical services system, Ann Emerg Med, 31, 483, 10.1016/S0196-0644(98)70258-6 Ferguson, 2005, Time out! Is timepiece variability a factor in critical care?, Am J Crit Care, 14, 113, 10.4037/ajcc2005.14.2.113 Hawthorne, 2014, Monitoring of intracranial pressure in patients with traumatic brain injury, Front Neurol, 5, 121, 10.3389/fneur.2014.00121 Steiner, 2002, Continuous monitoring of cerebrovascular pressure reactivity allows determination of optimal cerebral perfusion pressure in patients with traumatic brain injury, Crit Care Med, 30, 733, 10.1097/00003246-200204000-00002 Brady, 2009, Continuous monitoring of cerebrovascular pressure reactivity after traumatic brain injury in children, Pediatrics, 124, e1205, 10.1542/peds.2009-0550 Di Ieva, 2013, Analysis of intracranial pressure: Past, present, and future, Neuroscientist, 19, 592, 10.1177/1073858412474845 Fairchild, 2013, Predictive monitoring for early detection of sepsis in neonatal ICU patients, Curr Opin Pediatr, 25, 172, 10.1097/MOP.0b013e32835e8fe6 Moorman, 2011, Cardiovascular oscillations at the bedside: Early diagnosis of neonatal sepsis using heart rate characteristics monitoring, Physiol Meas, 32, 1821, 10.1088/0967-3334/32/11/S08 Schmidt, 2014, Heart rate variability for preclinical detection of secondary complications after subarachnoid hemorrhage, Neurocrit Care, 20, 382, 10.1007/s12028-014-9966-y Akre, 2010, Sensitivity of the pediatric early warning score to identify patient deterioration, Pediatrics, 125, e763, 10.1542/peds.2009-0338 Pollack, 1996, PRISM III: An updated pediatric risk of mortality score, Crit Care Med, 24, 743, 10.1097/00003246-199605000-00004 Liu, 2013, An electronic simplified acute physiology score-based risk adjustment score for critical illness in an integrated healthcare system, Crit Care Med, 41, 41, 10.1097/CCM.0b013e318267636e Manor-Shulman, 2008, Quantifying the volume of documented clinical information in critical illness, J Crit Care, 23, 245, 10.1016/j.jcrc.2007.06.003 Malhotra, 2007, Workflow modeling in critical care: Piecing together your own puzzle, J Biomed Inform, 40, 81, 10.1016/j.jbi.2006.06.002 Han, 2005, Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system, Pediatrics, 116, 1506, 10.1542/peds.2005-1287 Cheng, 2003, The effects of CPOE on ICU workflow: An observational study, AMIA Annu Symp Proc, 150 Abraham, 2012, Bridging gaps in handoffs: A continuity of care based approach, J Biomed Inform, 45, 240, 10.1016/j.jbi.2011.10.011 Pickering, 2010, Novel representation of clinical information in the ICU: Developing user interfaces which reduce information overload, Appl Clin Inform, 1, 116, 10.4338/ACI-2009-12-CR-0027 Koch, 2013, Evaluation of the effect of information integration in displays for ICU nurses on situation awareness and task completion time: A prospective randomized controlled study, Int J Med Inform, 82, 665, 10.1016/j.ijmedinf.2012.10.002 Sebastian, 2012, Multi-signal visualization of physiology (MVP): A novel visualization dashboard for physiological monitoring of traumatic brain injury patients, Conf Proc IEEE Eng Med Biol Soc, 2012, 2000 Ordo´n~ez, 2012, Visualization of multivariate time series data in a neonatal ICU, IBM J Res Dev, 56, 1 Riviello, 2013, Digital trend analysis in the pediatric and neonatal intensive care units, J Clin Neurophysiol, 30, 143, 10.1097/WNP.0b013e3182872b0e Ray, 2011, Question 1. Is cerebral function monitoring as accurate as conventional EEG in the detection of neonatal seizures?, Arch Dis Child, 96, 314, 10.1136/adc.2010.210054 Akman, 2011, Seizure detection using digital trend analysis: Factors affecting utility, Epilepsy Res, 93, 66, 10.1016/j.eplepsyres.2010.10.018 Abend, 2008, Neonatal seizure detection using multichannel display of envelope trend, Epilepsia, 49, 349, 10.1111/j.1528-1167.2007.01425.x Smielewski, 2005, ICM+: Software for on-line analysis of bedside monitoring data after severe head trauma, Acta Neurochir Suppl, 95, 43, 10.1007/3-211-32318-X_10 Moberg Research. CNS EEG & Multimodal Neuromonitor. http://www.mobergresearch.com/products-services/neuromonitoring/cns-eeg-multimodal-neuromonitor Mitka, 2013, Joint commission warns of alarm fatigue multitude of alarms from monitoring devices problematic, J Am Med Assoc, 309, 2315, 10.1001/jama.2013.6032 Healthcare Technology Safety Institute. Using data to drive alarm system improvement efforts: The Johns Hopkins Hospital experience, 2012. http://www.aami.org/htsi/SI_Series/Johns_Hopkins_White_Paper.pdf Schmid, 2013, Patient monitoring alarms in the ICU and in the operating room, Crit Care, 17, 216, 10.1186/cc12525 Scalzo, 2013, Reducing false intracranial pressure alarms using morphological waveform features, IEEE Trans Biomed Eng, 60, 235, 10.1109/TBME.2012.2210042