Identifying neurocognitive outcomes and cerebral oxygenation in critically ill adults on acute kidney replacement therapy in the intensive care unit: the INCOGNITO-AKI study protocol

Natasha Arianne Jawa, Rachel M Holden, Samuel A Silver, Stephen H Scott, Andrew G Day, Patrick A Norman, Benjamin Y M Kwan, David M Maslove, John Muscedere, John Gordon Boyd, Natasha Arianne Jawa, Rachel M Holden, Samuel A Silver, Stephen H Scott, Andrew G Day, Patrick A Norman, Benjamin Y M Kwan, David M Maslove, John Muscedere, John Gordon Boyd

Abstract

Introduction: Initiation of acute kidney replacement therapy (KRT) is common in critically ill adults admitted to the intensive care unit (ICU), and associated with increased morbidity and mortality. KRT has been linked to poor neurocognitive outcomes, leading to reduced quality of life and increased utilisation of healthcare resources. Adults on dialysis in the ICU may be particularly at risk of neurocognitive impairment, as survivors of critical illness are already predisposed to developing cerebrovascular disease and cognitive dysfunction long-term relative to healthy controls. Regional cerebral oxygen saturation may provide a critical early marker of long-term neurocognitive impairment in this population. This study aims to understand cerebral oxygenation in patients undergoing KRT (continuous or intermittent) in the ICU. These findings will be correlated with long-term cognitive and functional outcomes, and structural brain pathology.

Methods and analysis: 108 patients scheduled to undergo treatment for acute kidney injury with KRT in the Kingston Health Sciences Centre ICU will be recruited into this prospective observational study. Enrolled patients will be assessed with intradialytic cerebral oximetry using near infrared spectroscopy. Delirium will be assessed daily with the Confusion Assessment Method-ICU (CAM-ICU) and severity quantified as cumulative CAM-ICU-7 scores. Neurocognitive impairment will be assessed at 3 and 12 months after hospital discharge using the Kinarm and Repeatable Battery for the Assessment of Neuropsychological Status. Structural brain pathology on MRI will also be measured at the same timepoints. Driving safety, adverse events and medication adherence will be assessed at 12 months to evaluate the impact of neurocognitive impairment on functional outcomes.

Ethics and dissemination: This study is approved by the Queen's University Health Sciences/Affiliated Teaching Hospitals Research Ethics Board (DMED-2424-20). Results will be presented at critical care conferences, and a lay summary will be provided to patients in their preferred format.

Trial registration number: NCT04722939.

Keywords: acute renal failure; adult intensive & critical care; adult neurology; dialysis.

Conflict of interest statement

Competing interests: SHS is cofounder and CSO of Kinarm that commercialises the Kinarm robotic technology used in the present study. NAJ, RMH, SAS, AGD, PAN, BYMK, DMM, JM and JGB have no conflicts of interest to declare.

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1
Figure 1
Hypothesised causal pathway. AE, adverse events; AKI, acute kidney injury; KRT, kidney replacement therapy; rSO2, regional cerebral oxygen saturation. Neurocognitive function is defined as performance on the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and Kinarm tasks.
Figure 2
Figure 2
Study schema. APACHE II, Acute Physiological Assessment and Chronic Health Evaluation; CAM-ICU, Confusion Assessment Method-Intensive Care Unit; CDRS, Clinical Dementia Rating Scale; CFS, Clinical Frailty Scale; CKRT, continuous KRT; iHD, intermittent haemodialysis; KRT, kidney replacement therapy; RBANS, Repeatable Battery for the Assessment of Neuropsychological Status; rSO2, regional cerebral oxygen saturation; MARS, Medication Adherence Rating Scale; MDBQ, Machester Driver Behavior Questionnaire.

References

    1. Rawal G, Yadav S, Kumar R. Post-intensive care syndrome: an overview. J Transl Int Med 2017;5:90–2. 10.1515/jtim-2016-0016
    1. Pandharipande PP, Girard TD, Jackson JC, et al. . Long-term cognitive impairment after critical illness. N Engl J Med 2013;369:1306–16. 10.1056/NEJMoa1301372
    1. Quasim T, Brown J, Kinsella J. Employment, social dependency and return to work after intensive care. J Intensive Care Soc 2015;16:31–6. 10.1177/1751143714556238
    1. Kamdar BB, Suri R, Suchyta MR, et al. . Return to work after critical illness: a systematic review and meta-analysis. Thorax 2020;75:17–27. 10.1136/thoraxjnl-2019-213803
    1. Girard TD, Jackson JC, Pandharipande PP, et al. . Delirium as a predictor of long-term cognitive impairment in survivors of critical illness. Crit Care Med 2010;38:1513–20. 10.1097/CCM.0b013e3181e47be1
    1. Maldonado JR. Acute brain failure: pathophysiology, diagnosis, management, and sequelae of delirium. Crit Care Clin 2017;33:461–519. 10.1016/j.ccc.2017.03.013
    1. , Wood MD, et al. , Cerebral Oxygenation and Neurological Outcomes Following Critical Illness (CONFOCAL) Research Group, Canadian Critical Care Trials Group . Low brain tissue oxygenation contributes to the development of delirium in critically ill patients: a prospective observational study. J Crit Care 2017;41:289–95. 10.1016/j.jcrc.2017.06.009
    1. Siew ED, Fissell WH, Tripp CM, et al. . Acute kidney injury as a risk factor for delirium and coma during critical illness. Am J Respir Crit Care Med 2017;195:1597–607. 10.1164/rccm.201603-0476OC
    1. Levey AS, Eckardt K-U, Dorman NM, et al. . Nomenclature for kidney function and disease: report of a kidney disease: improving global outcomes (KDIGO) consensus conference. Kidney Int 2020;97:1117–29. 10.1016/j.kint.2020.02.010
    1. Wald R, McArthur E, Adhikari NKJ, et al. . Changing incidence and outcomes following dialysis-requiring acute kidney injury among critically ill adults: a population-based cohort study. Am J Kidney Dis 2015;65:870–7. 10.1053/j.ajkd.2014.10.017
    1. Hoste EAJ, Bagshaw SM, Bellomo R, et al. . Epidemiology of acute kidney injury in critically ill patients: the multinational AKI-EPI study. Intensive Care Med 2015;41:1411–23. 10.1007/s00134-015-3934-7
    1. Uchino S, Kellum JA, Bellomo R, et al. . Acute renal failure in critically ill patients: a multinational, multicenter study. JAMA 2005;294:813–8. 10.1001/jama.294.7.813
    1. Seliger SL, Weiner DE. Cognitive impairment in dialysis patients: focus on the blood vessels? Am J Kidney Dis 2013;61:187–90. 10.1053/j.ajkd.2012.12.002
    1. Khwaja A. KDIGO clinical practice guidelines for acute kidney injury. Nephron Clin Pract 2012;120:c179–84. 10.1159/000339789
    1. Hsu RK, McCulloch CE, Dudley RA, et al. . Temporal changes in incidence of dialysis-requiring AKI. J Am Soc Nephrol 2013;24:37–42. 10.1681/ASN.2012080800
    1. Hsu RK, McCulloch CE, Heung M, et al. . Exploring potential reasons for the temporal trend in dialysis-requiring AKI in the United States. Clin J Am Soc Nephrol 2016;11:14–20. 10.2215/CJN.04520415
    1. Wonnacott A, Meran S, Amphlett B, et al. . Epidemiology and outcomes in community-acquired versus hospital-acquired AKI. Clin J Am Soc Nephrol 2014;9:1007–14. 10.2215/CJN.07920713
    1. Pannu N, Gibney RN. Renal replacement therapy in the intensive care unit. Ther Clin Risk Manag 2005;1:141–50. 10.2147/tcrm.1.2.141.62908
    1. Fathima N, Kashif T, Janapala RN, et al. . Single-best choice between intermittent versus continuous renal replacement therapy: a review. Cureus 2019;11:e5558. 10.7759/cureus.5558
    1. Chaves RCdeF, Tafner PFdoA, Chen FK, et al. . Near-infrared spectroscopy parameters in patients undergoing continuous venovenous hemodiafiltration. Einstein 2019;17:eAO4439. 10.31744/einstein_journal/2019AO4439
    1. Schramm P, Closhen D, Wojciechowski J, et al. . Cerebrovascular autoregulation in critically ill patients during continuous hemodialysis. Can J Anaesth 2013;60:564–9. 10.1007/s12630-013-9912-z
    1. Polinder-Bos HA, García DV, Kuipers J, et al. . Hemodialysis induces an acute decline in cerebral blood flow in elderly patients. J Am Soc Nephrol 2018;29:1317–25. 10.1681/ASN.2017101088
    1. Polinder-Bos HA, Elting JWJ, Aries MJ, et al. . Changes in cerebral oxygenation and cerebral blood flow during hemodialysis - a simultaneous near-infrared spectroscopy and positron emission tomography study. J Cereb Blood Flow Metab 2020;40:328–40. 10.1177/0271678X18818652
    1. Steiner LA, Pfister D, Strebel SP, et al. . Near-infrared spectroscopy can monitor dynamic cerebral autoregulation in adults. Neurocrit Care 2009;10:122–8. 10.1007/s12028-008-9140-5
    1. Ferrari M, Mottola L, Quaresima V. Principles, techniques, and limitations of near infrared spectroscopy. Can J Appl Physiol 2004;29:463–87. 10.1139/h04-031
    1. Ito K, Ookawara S, Ueda Y, et al. . Factors affecting cerebral oxygenation in hemodialysis patients: cerebral oxygenation associates with pH, hemodialysis duration, serum albumin concentration, and diabetes mellitus. PLoS One 2015;10:e0117474. 10.1371/journal.pone.0117474
    1. Kovarova L, Valerianova A, Kmentova T, et al. . Low cerebral oxygenation is associated with cognitive impairment in chronic hemodialysis patients. Nephron 2018;139:113–9. 10.1159/000487092
    1. Findlay MD, Dawson J, Dickie DA, et al. . Investigating the relationship between cerebral blood flow and cognitive function in hemodialysis patients. J Am Soc Nephrol 2019;30:147–58. 10.1681/ASN.2018050462
    1. Miyazawa H, Ookawara S, Ito K, et al. . Association of cerebral oxygenation with estimated glomerular filtration rate and cognitive function in chronic kidney disease patients without dialysis therapy. PLoS One 2018;13:e0199366. 10.1371/journal.pone.0199366
    1. Tian F, Morriss MC, Chalak L, et al. . Impairment of cerebral autoregulation in pediatric extracorporeal membrane oxygenation associated with neuroimaging abnormalities. Neurophotonics 2017;4:041410. 10.1117/1.NPh.4.4.041410
    1. Lee KF, Wood MD, Maslove DM, et al. . Dysfunctional cerebral autoregulation is associated with delirium in critically ill adults. J Cereb Blood Flow Metab 2019;39:2512–20. 10.1177/0271678X18803081
    1. Shiao C-C, Wu P-C, Huang T-M, et al. . Long-term remote organ consequences following acute kidney injury. Crit Care 2015;19:438. 10.1186/s13054-015-1149-5
    1. Wu V-C, Wu P-C, Wu C-H, et al. . The impact of acute kidney injury on the long-term risk of stroke. J Am Heart Assoc 2014;3. 10.1161/JAHA.114.000933. [Epub ahead of print: 15 Jul 2014].
    1. Liu M, Liang Y, Chigurupati S, et al. . Acute kidney injury leads to inflammation and functional changes in the brain. J Am Soc Nephrol 2008;19:1360–70. 10.1681/ASN.2007080901
    1. Baumgaertel MW, Kraemer M, Berlit P. Neurologic complications of acute and chronic renal disease. Handb Clin Neurol 2014;119:383–93. 10.1016/B978-0-7020-4086-3.00024-2
    1. Vanderlinden JA, Semrau JS, Silver SA, et al. . Acute kidney injury is associated with subtle but quantifiable neurocognitive impairments. Nephrol Dial Transplant 2021. 10.1093/ndt/gfab161. [Epub ahead of print: 21 Apr 2021] (published Online First: 2021/04/22).
    1. Iyasere O, Brown EA. Cognitive function before and after dialysis initiation in adults with chronic kidney disease-a new perspective on an old problem? Kidney Int 2017;91:784–6. 10.1016/j.kint.2017.01.022
    1. Pereira AA, Weiner DE, Scott T, et al. . Subcortical cognitive impairment in dialysis patients. Hemodial Int 2007;11:309–14. 10.1111/j.1542-4758.2007.00185.x
    1. Sarnak MJ, Tighiouart H, Scott TM, et al. . Frequency of and risk factors for poor cognitive performance in hemodialysis patients. Neurology 2013;80:471–80. 10.1212/WNL.0b013e31827f0f7f
    1. Kalirao P, Pederson S, Foley RN, et al. . Cognitive impairment in peritoneal dialysis patients. Am J Kidney Dis 2011;57:612–20. 10.1053/j.ajkd.2010.11.026
    1. Murray AM, Tupper DE, Knopman DS, et al. . Cognitive impairment in hemodialysis patients is common. Neurology 2006;67:216–23. 10.1212/01.wnl.0000225182.15532.40
    1. Kurella Tamura M, Wadley V, Yaffe K, et al. . Kidney function and cognitive impairment in US adults: the reasons for geographic and racial differences in stroke (regards) study. Am J Kidney Dis 2008;52:227–34. 10.1053/j.ajkd.2008.05.004
    1. Weiner DE, Scott TM, Giang LM, et al. . Cardiovascular disease and cognitive function in maintenance hemodialysis patients. Am J Kidney Dis 2011;58:773–81. 10.1053/j.ajkd.2011.03.034
    1. Costa AS, Tiffin-Richards FE, Holschbach B, et al. . Clinical predictors of individual cognitive fluctuations in patients undergoing hemodialysis. Am J Kidney Dis 2014;64:434–42. 10.1053/j.ajkd.2014.02.012
    1. Sedaghat S, Cremers LGM, de Groot M, et al. . Kidney function and microstructural integrity of brain white matter. Neurology 2015;85:154–61. 10.1212/WNL.0000000000001741
    1. Rogova IV, Fomin VV, Damulin IV, et al. . [Specific features of cognitive impairments in patients with predialysis chronic kidney disease]. Ter Arkh 2013;85:25–30.
    1. Ikram MA, Vernooij MW, Hofman A, et al. . Kidney function is related to cerebral small vessel disease. Stroke 2008;39:55–61. 10.1161/STROKEAHA.107.493494
    1. Naganuma T, Takemoto Y, Shoji T, et al. . Factors associated with cerebral white matter hyperintensities in haemodialysis patients. Nephrology 2012;17:561–8. 10.1111/j.1440-1797.2012.01596.x
    1. Yoshimitsu T, Hirakata H, Fujii K, et al. . Cerebral ischemia as a causative mechanism for rapid progression of brain atrophy in chronic hemodialysis patients. Clin Nephrol 2000;53:445–51.
    1. Gunther ML, Morandi A, Krauskopf E, et al. . The association between brain volumes, delirium duration, and cognitive outcomes in intensive care unit survivors: the visions cohort magnetic resonance imaging study*. Crit Care Med 2012;40:2022–32. 10.1097/CCM.0b013e318250acc0
    1. Meyer J, Waldmann C, Driving WC. Driving (or not) after critical illness. J Intensive Care Soc 2015;16:186–8. 10.1177/1751143714564817
    1. STARRT-AKI Investigators, Canadian Critical Care Trials Group, Australian and New Zealand Intensive Care Society Clinical Trials Group, et al. . Timing of initiation of renal-replacement therapy in acute kidney injury. N Engl J Med 2020;383:240–51. 10.1056/NEJMoa2000741
    1. Khan BA, Perkins AJ, Gao S, et al. . The confusion assessment method for the ICU-7 delirium severity scale: a novel delirium severity instrument for use in the ICU. Crit Care Med 2017;45:851–7. 10.1097/CCM.0000000000002368
    1. Tosh W, Patteril M. Cerebral oximetry. BJA Educ 2016;16:417–21. 10.1093/bjaed/mkw024
    1. Simmatis LER, Early S, Moore KD, et al. . Statistical measures of motor, sensory and cognitive performance across repeated robot-based testing. J Neuroeng Rehabil 2020;17:86. 10.1186/s12984-020-00713-2
    1. Wood MD, Maslove DM, Muscedere J, et al. . Robotic technology provides objective and quantifiable metrics of neurocognitive functioning in survivors of critical illness:A feasibility study. J Crit Care 2018;48:228–36. 10.1016/j.jcrc.2018.09.011
    1. KST summary (analysis version 3.8) online, 2019. Available: [Accessed 05 Jan 2021].
    1. Semrau JA, Herter TM, Scott SH, et al. . Examining differences in patterns of sensory and motor recovery after stroke with robotics. Stroke 2015;46:3459–69. 10.1161/STROKEAHA.115.010750
    1. Randolph C, Tierney MC, Mohr E, et al. . The repeatable battery for the assessment of neuropsychological status (RBANS): preliminary clinical validity. J Clin Exp Neuropsychol 1998;20:310–9. 10.1076/jcen.20.3.310.823
    1. McAuliffe MJ, Lalonde FM, McGarry D. "Medical image processing, analysis and visualization in clinical research," proceedings 14th IEEE symposium on computer-based medical systems. CBMS 2001:381–6. 10.1109/CBMS.2001.941749
    1. Woolrich MW, Jbabdi S, Patenaude B, et al. . Bayesian analysis of neuroimaging data in fsl. Neuroimage 2009;45:S173–86. 10.1016/j.neuroimage.2008.10.055
    1. Sled JG, Zijdenbos AP, Evans AC. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging 1998;17:87–97. 10.1109/42.668698
    1. Andersson JL, Jenkinson M, Smith S. Non-linear registration a.k.a. spatial normalisation. In: FMRIB technical report. Oxford, United Kingdom: FMRIB Centre, 2007.
    1. Smith SM. Fast robust automated brain extraction. Hum Brain Mapp 2002;17:143–55. 10.1002/hbm.10062
    1. Patenaude B, Smith SM, Kennedy DN, et al. . A bayesian model of shape and appearance for subcortical brain segmentation. Neuroimage 2011;56:907–22. 10.1016/j.neuroimage.2011.02.046
    1. Whitwell JL, Crum WR, Watt HC, et al. . Normalization of cerebral volumes by use of intracranial volume: implications for longitudinal quantitative MR imaging. AJNR Am J Neuroradiol 2001;22:1483–9.
    1. Khan JM, Wood MD, Lee KFH, et al. . Delirium, cerebral perfusion, and high-frequency vital-sign monitoring in the critically ill. The CONFOCAL-2 feasibility study. Ann Am Thorac Soc 2021;18:112–21. 10.1513/AnnalsATS.202002-093OC
    1. Wood MD, Khan J, Lee KFH, et al. . Assessing the relationship between near-infrared spectroscopy-derived regional cerebral oxygenation and neurological dysfunction in critically ill adults: a prospective observational multicentre protocol, on behalf of the Canadian critical care trials group. BMJ Open 2019;9:e029189. 10.1136/bmjopen-2019-029189
    1. Semrau JS, Scott SH, Hamilton AG, et al. . Quantified pre-operative neurological dysfunction predicts outcome after coronary artery bypass surgery. Aging Clin Exp Res 2020;32:289–97. 10.1007/s40520-019-01184-9

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