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Delirium detection in Intensive Care patients Willemijn van der Kooi Department of Intensive Care Medicine University Medical Center Utrecht, The Netherlands.

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Presentation on theme: "Delirium detection in Intensive Care patients Willemijn van der Kooi Department of Intensive Care Medicine University Medical Center Utrecht, The Netherlands."— Presentation transcript:

1 Delirium detection in Intensive Care patients Willemijn van der Kooi Department of Intensive Care Medicine University Medical Center Utrecht, The Netherlands

2 Orion Pharma: contributed to printing costs of my thesis NPK design: contributed to printing costs of my thesis Disclosures

3 Delirium prevalence: 50%-80% for ICU patients 10-15% for cardiac surgery patients ICU delirium is associated with: Long term cognitive impairment Increased hospital and ICU length of stay Increased mortality Introduction * Actor

4 Delirium often (71%) missed by ICU physicians 1 questionnaires developed for screening Daily practice Sensitivity of questionnaire with best performance (Cam-ICU): – 47% in ICU patients 2 – 28% in post-operative patients 3 Cognitive screening may not fit well in the culture of the ICU Introduction 1 Van Eijk et al. Crit Care Med 2009;37: Van Eijk et al. Am J Respir Crit Care Med 2011;184: Neufeld et al. Br J Anaesth 2013;111:612-8

5 New approach: delirium detection using physiological alterations Introduction Ultimate goal: 2 sensors coupled to a monitor Monitor shows on a scale the chance of having delirium

6 Three physiological parameters studied: Temperature variability Eye movements Brain activity (EEG) Future perspective Content

7 Temperature variability during delirium in ICU patients Van der kooi et al. PLoS One. 2013; 8:e78923

8 Delirium: manifestation of encephalopathy In delirium tremens, Wernicke encephalopathy and schizophrenia: temperature regulation is disturbed Does delirium affect thermoregulation? Introduction

9 To investigate whether: ICU delirium is related to absolute body temperature ICU delirium is related to temperature variability Aim of the study

10 Subjects from 3 previous delirium studies Daily delirium assessments by research- nurse/physician Temperature: measured per minute 24/7 Methods

11 Inclusion: Patients with delirious + non-delirious days during ICU admission of >24 hrs Exclusion criteria: Disturbed body temperature regulation (treatment/diagnoses) Neurological/neurosurgical disease Days with sepsis, coma or death were excluded from analysis *All patients received paracetamol 1000 mg 4 times daily Methods

12 Coma No DeliriumDelirium

13 Linear Mixed models: Univariable (unadjusted) Multivariable (adjusted for confounders RASS and SOFA) Outcome: body temperature [°C] temperature variability (absolute second derivative) [°C/min 2 ] Methods

14 Results

15 Patient characteristics Age: mean (SD)68 (14) Gender: number of males (%)15 (63%) Admission type: number (%) -internal medicine3 (12%) -surgery12 (50%) -cardiothoracic surgery9 (38%) Delirium type: number (%) -Hypoactive6 (25%) -Hyperactive0 (0%) -Mixed type18 (75%) Number of analyzed days: median (IQR) -Delirium2.0 (1.0) -Non-delirium1.0 (1.8)

16 Body Temperature: Results ModelVariableEffect estimate95% Confidence intervalp-value Unadjusted Delirium [yes] ; Adjusted Delirium [yes] ; Rass ; Sofa ;

17 Temperature Variability: Results ModelVariableEffect estimate95% Confidence intervalp-value Unadjusted Delirium [yes] ; 0.008<0.001 Adjusted Delirium [yes] ; 0.008<0.001 Rass ; Sofa ;

18 Strengths: Delirium diagnoses prospectively Within subjects comparisons Easy method temperature variability Limitations Possible effect of medication Natural circadian rhythm bias Discussion

19 Temperature variability: increased during delirium in ICU patients encephalopathy that underlies delirium Future studies: Monitoring temperature variability in total ICU population Combine with EEG for objective tool to detect delirium Discussion

20 Delirium detection based on monitoring of blinks and eye movements Van der kooi et al. Am J Geriatr Psychiatry. 2014

21 Delirium associated with change in motor level activity Actigraphy not practical Eye movements less affected by muscle weakness, restraints, pain Introduction

22 Goal Determine whether eye blinks and eye movements differ in patients with delirium compared to patients without delirium.

23 Methods Population: post-cardiac surgery patients Reference: psychiatrist, geriatrist, neurologist using DSM 4 criteria

24 Methods Standard 21 electrode EEG recording (30 minutes) with periods of eyes open and closed First artifact free minute selected with eyes closed and open

25 Methods: Eye movements Eye movements compared between delirium and non-delirium Number (per min) and duration (sec) of: Blinks Vertical eye movements Horizontal eye movements

26 Results: study population Delirious patients (n=28) Non-delirious patients (n=28) p-value Age, mean (SD)76 (5.6)74 (8.6)0.16 Gender: male, n (%)16 (57%) 1 Apache IV score, median (IQR)58 (45-65)43 (35-51)<0.01 Charlson comorbidity index, median (IQR) 2 (1-3)1 (0-1)0.02 Haloperidol use past 24 hours n (%)17 (61%)2 (7%)<0.01 Postsurgical day of EEG, median (IQR) 3 (2-5)3 (2-4)0.78

27 Results: eye movements Variable Delirium Median (IQR) Non-delirium Median (IQR) p-value Number of Vertical eye movements (min -1 )1 (0-13)15 (2-54)0.01 Number of Blinks (min -1 )12 (5-18)18 (8-25)0.02 Duration of Blinks (s)0.50 ( )0.34 ( )<0.01 Eyes Open

28 Results: eye movements Variable Delirium Median (IQR) Non-delirium Median (IQR) p-value Duration of Horizontal eye movements (s)0.41 ( )0.08 ( )<0.01 Eyes Closed

29 Results: Eye movements haloperidol EyesVariable Delirium with haloperidol Median (IQR) Delirium without haloperidol Median (IQR) p-value Open Number of vertical eye movements 2 (0-17)0 (0-17)0.69 Open Number of blinks 12 (4-19)12 (6-17)0.87 OpenDuration of blinks (s)0.49 ( )0.52 ( )0.81 ClosedDuration of horizontal of eye movements (s) 0.59 ( )0.27 ( )0.19

30 Conclusion Especially blinks are affected in delirious patients Strengths: non-invasive Only 1 minute of data necessary Limitations: 22 electrodes needed for eye movement measurement, except for blinks Difference in Apache and Charlson Comorbidity score Future studies: Detection of eye movements in general population of ICU patients Determining whether eye movements can detect delirium at early stage

31 Delirium detection using EEG: what and how to measure? Van der kooi et al. Chest. 2014

32 Delirium characterized by EEG abnormalities EEG not practical Introduction Without DeliriumWith Delirium

33 Goal Determine the electrode derivation and EEG characteristic that have the best capability of discriminating delirium from non-delirium

34 Methods Standard 21 electrode EEG recording (30 minutes) with periods of eyes open and closed First artifact free minute selected with eyes closed

35 Methods: EEG Eyes closed= 210 different derivations

36 Methods: EEG For every derivation 6 parameters: 1 Relative delta power (0.5-4 Hz), Relative theta power (4-8 Hz),Relative alpha power (8-13 Hz), Relative beta power (13-20 Hz), Peak frequency, Slow-fast ratio 1 van der Kooi, et al. J Neuropsychiatry Clin Neurosci 2012; 24: Ruwe EEG δ 0-4 Hz θ 4-8 Hz α 8-13 Hz β Hz

37 Methods: EEG 210 derivations x 6 parameters = 1260 combinations All 1260 combinations Compared between delirium and non-delirium (Mann-whitney U) P-values ranked smallest p-value is optimal combination (Bonferoni correction ) 1 van der Kooi, et al. J Neuropsychiatry Clin Neurosci 2012; 24:

38 Results: EEG Eyes closed Rankp-value*DeriviationParameter 11.8e-12F8-PzRelative δ 23.7e-12F8-P3Relative δ 31.1e-11F8-O2Relative δ 41.5e-11Fp2-O1Relative δ 51.7e-11F8-F4Relative δ 62.2e-11F8-O1Relative δ 72.4e-11F8-CzRelative δ 82.4e-11F8-C3Relative δ 92.9e-11Fp2-PzRelative δ 103.0e-11Cz-O1Relative δ *p< 4.0*10 -5 is significant

39 Results: EEG Most optimal electrode locations, based on first 4 rankings.

40 Conclusion EEG easily detects delirium from non-delirium using 2 electrodes in frontal-parietal derivation and relative delta power Strengths: new approach, non-invasive, only 2 electrodes and 1 minute data necessary Future studies: Validation study in unselected population of postoperative- and critically ill patients Determine whether it recognizes delirium at an early stage

41 Future Directions

42 Overall Conclusion EEG most promising method for delirium detection. Project started: Development of delirium monitor

43 Product development Product and algorithm

44 Validation study Goal: To determine sensitivity, specificity and predictive values of the delirium monitor when compared to reference standard (specialized geriatric nurse) in elderly postoperative patients (n=154).

45 Usability study Practical? Easy to Use? Opinion of nurses of different medical departments

46

47 Extra slides

48 Results: EEG eyes open Ogen Open Rangp-waarde*AfleidingParameter 12.0e-07P7-P4Relative alpha 24.2e-07P3-P4Relative alpha 31.6e-06P7-O1Relative delta 43.2e-06P7-O1Relative alpha 53.5e-06P3-P4Slow Fast ratio 64.0e-06P4-O1Relative alpha 76.1e-06P7-P8Relative alpha 87.9e-06P7-P4Slow Fast ratio 99.4e-06P3-P8Relative alpha 101.1e-05P7-O2Relative alpha *p< 5.6*10 -4 is significant Delirium met/zonder haloperidol geen verschil (p=0.37)

49 Results: Eye movements eyes open EyesVariable Delirium Median (IQR) Non-delirium Median (IQR) p-value AUC (95% CI) Ope n Number of eye movements Horizontal 6 (0-51) n=23 26 (0-55) n= ( ) Vertical 1 (0-13) n=23 15 (2-54) n= ( ) Blinks 12 (5-18) n=23 18 (8-25) n= ( ) Ope n Duration of eye movements (s) Horizontal 0.24 ( ) n= ( ) n= ( ) Vertical 0.14 ( ) n= ( ) n= ( ) Blinks0.50 ( ) n= ( ) n=27 < ( )

50 Results: Eye movements eyes closed EyesVariable Delirium Median (IQR) Non-delirium Median (IQR) p-value AUC (95% CI) ClosedNumber of eye movements Horizontal 0 (0-42) n=27 0 (0-51) n= ( ) Vertical 5 (0-47) n=27 10 (0-52) n= ( ) Closed Duration of eye movements (s) Horizontal 0.41 ( ) n= ( ) n=13 < ( ) Vertical0.15 ( ) n= ( ) n= ( )

51 Results: Eye movements haloperidol EyesVariable Delirium with haloperidol Median (IQR) Delirium without haloperidol Median (IQR) p-value Number of eye movements Open Vertical 2 (0-17) n=14 0 (0-17) n= Open Blinks 12 (4-19) n=14 12 (6-17) n= Duration of eye movements (s) OpenBlinks 0.49 ( ) n= ( ) n= ClosedHorizontal0.59 ( ) n= ( ) n=6 0.19

52 Stap1Van onderzoek naar klinische prakti Ontwikkeling van delirium monitor – Product – Algoritme Validatie studie Gebruiksvriendelijkheids- studie

53 Validatie studie Doel: Het bepalen van de sensitiviteit, specificiteit en voorspellende waarden van de delirium monitor in vergelijking met de referentie standaard in oudere postoperatieve patiënten (n=154).

54 Validatie studie Inclusie: ≥ 70 jaar Opname voor grote operatie (min. 2 opname dagen ZH na operatie) Preoperatieve verhoogde kwetsbaarheid en/of verhoogd risico op delirium Exclusie: Geen communicatie mogelijk Neurologische chirurgische ingreep Eerdere deelname studie Patient in isolatie vanwege resistente bacterie

55 Validatie studie - Studie verloop OperatieT0T1T2T3 = Delirium monitor = Referentie standaard = POS Geriatrische screening

56 Validatie studie Delirium monitor 4 elektrodes 5 minuten EEG meting OD Relatieve δ power Referentie standaardonderzoeker/vpk DRS-R-98 Ernst van delirium VAS(0-10)Kans dat patiënt delirant is ClassificatieDeliriant/Mogelijk delirant/Niet delirant (Op basis van DSM-V criteria)

57 Validatie studie - Analyses 1 e artefact vrije minute  relatieve δ power ROC curve relatieve δ power vs. classificatie van referentie standaard

58 Validatie studie - Secundaire doelen 1) Schaal voor ernst van delirium (relatieve δ vs. DRS- R-98) 2) Vroegtijdig herkennen van delirium? OperatieT0T1T2T3 = Delirium monitor = Referentie standaard = Geriatrische screening

59 Stap2Van onderzoek naar klinische praktijk Gebruiksvriendelijkheidsonderzoek – Handig product? – Ervaring verpleegkundige

60 Stap3Van onderzoek naar klinische praktijk Delirium monitor bredere doelgroep – Dementie – Neurotrauma – IC:Effect sedatie op EEG

61 Samenvatting 1)EEG in delirium studie = het idee – Relatieve δ power – Frontaal- Pariëtaal 2) Ontwikkeling prototype 3) Validatiestudie 4) Gebruiksvriendelijkheidsstudie 5) Hoe krijgen we het naar de IC

62 Delirium monitor project UMCU - IC Arjen Slooter Willemijn van der Kooi Tianne Numan Annemieke Hoekman Pontes Medical Rutger van Merkerk NPK design Tessa Souhoka Marlies van Dullemen Jos Oberdorf Medische Techniek Leonard van Schelven Rene van de Vosse Bert Westra Maurice Konings Geriatrie Marielle Emmelot-Vonk Jolanda Peijster- de Waal Marcel Weterman KNF Geert-Jan Huiskamp Frans Leijten


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