Brainstem response patterns in deeply-sedated critically-ill patients predict 28-day mortality

Benjamin Rohaut, Raphael Porcher, Tarik Hissem, Nicholas Heming, Patrick Chillet, Kamel Djedaini, Guy Moneger, Stanislas Kandelman, Jeremy Allary, Alain Cariou, Romain Sonneville, Andréa Polito, Marion Antona, Eric Azabou, Djillali Annane, Shidasp Siami, Fabrice Chrétien, Jean Mantz, Tarek Sharshar, Groupe d’Exploration Neurologique en Réanimation (GENER), Benjamin Rohaut, Raphael Porcher, Tarik Hissem, Nicholas Heming, Patrick Chillet, Kamel Djedaini, Guy Moneger, Stanislas Kandelman, Jeremy Allary, Alain Cariou, Romain Sonneville, Andréa Polito, Marion Antona, Eric Azabou, Djillali Annane, Shidasp Siami, Fabrice Chrétien, Jean Mantz, Tarek Sharshar, Groupe d’Exploration Neurologique en Réanimation (GENER)

Abstract

Background and purpose: Deep sedation is associated with acute brain dysfunction and increased mortality. We had previously shown that early-assessed brainstem reflexes may predict outcome in deeply sedated patients. The primary objective was to determine whether patterns of brainstem reflexes might predict mortality in deeply sedated patients. The secondary objective was to generate a score predicting mortality in these patients.

Methods: Observational prospective multicenter cohort study of 148 non-brain injured deeply sedated patients, defined by a Richmond Assessment sedation Scale (RASS) <-3. Brainstem reflexes and Glasgow Coma Scale were assessed within 24 hours of sedation and categorized using latent class analysis. The Full Outline Of Unresponsiveness score (FOUR) was also assessed. Primary outcome measure was 28-day mortality. A "Brainstem Responses Assessment Sedation Score" (BRASS) was generated.

Results: Two distinct sub-phenotypes referred as homogeneous and heterogeneous brainstem reactivity were identified (accounting for respectively 54.6% and 45.4% of patients). Homogeneous brainstem reactivity was characterized by preserved reactivity to nociceptive stimuli and a partial and topographically homogenous depression of brainstem reflexes. Heterogeneous brainstem reactivity was characterized by a loss of reactivity to nociceptive stimuli associated with heterogeneous brainstem reflexes depression. Heterogeneous sub-phenotype was a predictor of increased risk of 28-day mortality after adjustment to Simplified Acute Physiology Score-II (SAPS-II) and RASS (Odds Ratio [95% confidence interval] = 6.44 [2.63-15.8]; p<0.0001) or Sequential Organ Failure Assessment (SOFA) and RASS (OR [95%CI] = 5.02 [2.01-12.5]; p = 0.0005). The BRASS (and marginally the FOUR) predicted 28-day mortality (c-index [95%CI] = 0.69 [0.54-0.84] and 0.65 [0.49-0.80] respectively).

Conclusion: In this prospective cohort study, around half of all deeply sedated critically ill patients displayed an early particular neurological sub-phenotype predicting 28-day mortality, which may reflect a dysfunction of the brainstem.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1. Flow chart.
Fig 1. Flow chart.
NMBA: neuromuscular-blocking agent; RASS: Richmond Assessment Sedation Scale.
Fig 2. Representation of homogeneous and heterogeneous…
Fig 2. Representation of homogeneous and heterogeneous profiles.
The percentage of abolition of each tested neurological responses in homogeneous and heterogeneous profiles are depicted. The heterogeneous profile is characterized by a greater and more heterogeneous abolition of neurological responses.
Fig 3. 28-day mortality probability according to…
Fig 3. 28-day mortality probability according to the BRASS.
Mortality probability expressed in mean [95%CI], BRASS: Brainstem Responses Assessment Sedation Score.

References

    1. Barr J, Fraser GL, Puntillo K, Ely EW, Gélinas C, Dasta JF, et al. Clinical Practice Guidelines for the Management of Pain, Agitation, and Delirium in Adult Patients in the Intensive Care Unit. Crit Care Med. 2013. January;41(1):278–80.
    1. Shehabi Y, Bellomo R, Mehta S, Riker R, Takala J. Intensive care sedation: the past, present and the future. Crit Care. 2013;17(3):322 10.1186/cc12679
    1. Ely EW, Truman B, Shintani A, Thomason JWW, Wheeler AP, Gordon S, et al. Monitoring sedation status over time in ICU patients: reliability and validity of the Richmond Agitation-Sedation Scale (RASS). JAMA. 2003. June 11;289(22):2983–91. 10.1001/jama.289.22.2983
    1. Shehabi Y, Bellomo R, Reade MC, Bailey M, Bass F, Howe B, et al. Early intensive care sedation predicts long-term mortality in ventilated critically ill patients. Am J Respir Crit Care Med. 2012. October 15;186(8):724–31. 10.1164/rccm.201203-0522OC
    1. Grap MJ, Munro CL, Wetzel PA, Best AM, Ketchum JM, Hamilton VA, et al. Sedation in adults receiving mechanical ventilation: physiological and comfort outcomes. Am J Crit Care. 2012. May;21(3):e53–63. 10.4037/ajcc2012301
    1. Shehabi Y, Chan L, Kadiman S, Alias A, Ismail WN, Tan MATI, et al. Sedation depth and long-term mortality in mechanically ventilated critically ill adults: a prospective longitudinal multicentre cohort study. Intensive Care Med. 2013. May;39(5):910–8. 10.1007/s00134-013-2830-2
    1. Elliott D, Aitken LM, Bucknall TK, Seppelt IM, Webb SAR, Weisbrodt L, et al. Patient comfort in the intensive care unit: a multicentre, binational point prevalence study of analgesia, sedation and delirium management. Crit Care Resusc. 2013. September;15(3):213–9.
    1. Nydahl P, Ruhl AP, Bartoszek G, Dubb R, Filipovic S, Flohr H-J, et al. Early mobilization of mechanically ventilated patients: a 1-day point-prevalence study in Germany. Crit Care Med. 2014. May;42(5):1178–86. 10.1097/CCM.0000000000000149
    1. Balzer F, Weiß B, Kumpf O, Treskatsch S, Spies C, Wernecke K-D, et al. Early deep sedation is associated with decreased in-hospital and two-year follow-up survival. Crit Care. 2015;19:197 10.1186/s13054-015-0929-2
    1. Ely EW, Shintani A, Truman B, Speroff T, Gordon SM, Harrell FE Jr, et al. Delirium as a predictor of mortality in mechanically ventilated patients in the intensive care unit. JAMA. 2004. April 14;291(14):1753–62. 10.1001/jama.291.14.1753
    1. Pandharipande PP, Pun BT, Herr DL, Maze M, Girard TD, Miller RR, et al. Effect of sedation with dexmedetomidine vs lorazepam on acute brain dysfunction in mechanically ventilated patients: the MENDS randomized controlled trial. JAMA. 2007. December 12;298(22):2644–53. 10.1001/jama.298.22.2644
    1. Reade MC, Finfer S. Sedation and Delirium in the Intensive Care Unit. N Engl J Med. 2014;370(5):444–54. 10.1056/NEJMra1208705
    1. Treggiari MM, Romand J-A, Yanez ND, Deem SA, Goldberg J, Hudson L, et al. Randomized trial of light versus deep sedation on mental health after critical illness. Crit Care Med. 2009. September;37(9):2527–34. 10.1097/CCM.0b013e3181a5689f
    1. Sharshar T, Porcher R, Siami S, Rohaut B, Bailly-Salin J, Hopkinson NS, et al. Brainstem responses can predict death and delirium in sedated patients in intensive care unit. Crit Care Med. 2011. August;39(8):1960–7. 10.1097/CCM.0b013e31821b843b
    1. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for reporting observational studies. Int J Surg. 2014. December;12(12):1495–9. 10.1016/j.ijsu.2014.07.013
    1. Wijdicks EFM, Bamlet WR, Maramattom BV, Manno EM, McClelland RL. Validation of a new coma scale: The FOUR score. Ann Neurol. 2005. October;58(4):585–93. 10.1002/ana.20611
    1. van den Boogaard M, Pickkers P, Slooter AJC, Kuiper MA, Spronk PE, van der Voort PHJ, et al. Development and validation of PRE-DELIRIC (PREdiction of DELIRium in ICu patients) delirium prediction model for intensive care patients: observational multicentre study. BMJ. 2012;344:e420 10.1136/bmj.e420
    1. van den Boogaard M, Schoonhoven L, Maseda E, Plowright C, Jones C, Luetz A, et al. Recalibration of the delirium prediction model for ICU patients (PRE-DELIRIC): a multinational observational study. Intensive Care Med. 2014. March;40(3):361–9. 10.1007/s00134-013-3202-7
    1. Le Gall JR, Neumann A, Hemery F, Bleriot JP, Fulgencio JP, Garrigues B, et al. Mortality prediction using SAPS II: an update for French intensive care units. Crit Care. 2005;9(6):R645–652. 10.1186/cc3821
    1. Vincent JL, Moreno R, Takala J, Willatts S, De Mendonça A, Bruining H, et al. 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. July;22(7):707–10.
    1. Ely EW, Inouye SK, Bernard GR, Gordon S, Francis J, May L, et al. Delirium in mechanically ventilated patients: validity and reliability of the confusion assessment method for the intensive care unit (CAM-ICU). JAMA. 2001. December 5;286(21):2703–10.
    1. Lazarsfeld PF, Henry NW. Latent Structure Analysis Houghton Mifflin; Boston: Auflage; 1968.
    1. Collins LM, Lanza ST. Latent class and latent transition analysis: With applications in the social, behavioral, and health sciences. Vol. 718 John Wiley & Sons; 2013.
    1. Le Cessie S, Van Houwelingen JC. A goodness-of-fit test for binary regression models, based on smoothing methods. Biometrics. 1991;1267–1282.
    1. Harrell FE, Lee KL, Mark DB. Tutorial in biostatistics multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15:361–387. 10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>;2-4
    1. Harrell FE, Califf RM, Pryor DB, Lee KL, Rosati RA. Evaluating the yield of medical tests. JAMA. 1982;247(18):2543–2546.
    1. R Development Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing; [Internet]. 2012;
    1. Linzer DA, Lewis JB, others. poLCA: An R package for polytomous variable latent class analysis. J Stat Softw. 2011;42(10):1–29.
    1. Annane D, Trabold F, Sharshar T, Jarrin I, Blanc AS, Raphael JC, et al. Inappropriate sympathetic activation at onset of septic shock: a spectral analysis approach. Am J Respir Crit Care Med. 1999. August;160(2):458–65. 10.1164/ajrccm.160.2.9810073
    1. Boisseau N, Madany M, Staccini P, Armando G, Martin F, Grimaud D, et al. Comparison of the effects of sevoflurane and propofol on cortical somatosensory evoked potentials. Br J Anaesth. 2002. June;88(6):785–9.
    1. Liu EHC, Wong HK, Chia CP, Lim HJ, Chen ZY, Lee TL. Effects of isoflurane and propofol on cortical somatosensory evoked potentials during comparable depth of anaesthesia as guided by bispectral index. Br J Anaesth. 2005. February;94(2):193–7. 10.1093/bja/aei003
    1. Dantzer R, O’Connor JC, Freund GG, Johnson RW, Kelley KW. From inflammation to sickness and depression: when the immune system subjugates the brain. Nat Rev Neurosci. 2008. January;9(1):46–56. 10.1038/nrn2297
    1. Sharshar T, Gray F, Poron F, Raphaël JC, Gajdos P, Annane D. Multifocal necrotizing leukoencephalopathy in septic shock. Crit Care Med. 2002. October;30(10):2371–5. 10.1097/01.CCM.0000029189.65178.C5
    1. Sharshar T, Gray F, Lorin de la Grandmaison G, Hopkinson NS, Ross E, Dorandeu A, et al. Apoptosis of neurons in cardiovascular autonomic centres triggered by inducible nitric oxide synthase after death from septic shock. Lancet. 2003. November 29;362(9398):1799–805.
    1. Sharshar T, Annane D, de la Grandmaison GL, Brouland JP, Hopkinson NS, Françoise G. The neuropathology of septic shock. Brain Pathol. 2004. January;14(1):21–33.
    1. The SRLF Trial Group. Sedation in French intensive care units: a survey of clinical practice. Ann Intensive Care. 2013;3(1):24.
    1. Sauder P, Andreoletti M, Cambonie G, Capellier G, Feissel M, Gall O, et al. Sédation-analgésie en réanimation (nouveau-né exclu). Ann Fr Anesth Reanim. 2008;27:541–551.
    1. Rotheray KR, Cheung PSY, Cheung CSK, Wai AKC, Chan DYS, Rainer TH, et al. What is the relationship between the Glasgow coma scale and airway protective reflexes in the Chinese population? Resuscitation. 2012. January;83(1):86–9. 10.1016/j.resuscitation.2011.07.017
    1. Wurpts IC, Geiser C. Is adding more indicators to a latent class analysis beneficial or detrimental? Results of a Monte-Carlo study. Front Psychol. 2014;5:920 10.3389/fpsyg.2014.00920

Source: PubMed

3
S'abonner