improving sedation-analgesia quality using novel …...improving sedation-analgesia quality using...
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Improving sedation-analgesia quality using novel technology:
A technology development journey
Tim WalshProfessor of Critical Care, Edinburgh University
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Declarations and Funding
Funding• Chief Scientists Office, Scotland
• Unrestricted funding GE Healthcare
Personal• No personal financial benefit/income; no shares
• Consultancy and collaborative work with GE Healthcare to Edinburgh University
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• Unnecessary deep sedation associated with adverse patient outcomes
Jackson DL et al. Critical care 2010;14:R59.
• Early deep sedation (first 48 hours) associated with higher ICU mortality
Shehabi Y et al. Am J Respir Crit Care Med 2012;186:724-731.
• Agitation increases nursing workload, anxiety, and the risk of adverse events
Everingham K et al. J Clin Nursing;23:694-703.
• Pain is prevalent in ICU patients and frequently recalled by ICU survivors
Chanques G et al. Anesthesiology 2007;107:858-60.
Background
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Implications of minimising sedation
Tolerance of intubation and invasive ventilation• Analgesia• Antinociception• Airway reflexes
Minimising risk of delirium
Managing Pain/discomfort
Managing agitation
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• Need for integrated approach• Consider Pain, Agitation, and Delirium• Need for monitoring/tracking tools to drive quality
improvement
• Current technologies (most studied Bispectral Index; BIS) not recommended except:• during neuromuscular paralysis• therapeutic deep sedation
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Ely EW JAMA 2003; 289: 2183
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Ely EW JAMA 2003; 289: 2183
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Ely EW JAMA 2003; 289: 2183
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Relation between BIS and RASS scoresEly EW et al 2003; 289; 2983
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Comparison of two bispectral index algorithms in monitoring sedation in postoperative intensive care patients
Tonner, Peter H et al CCM 2005; 33: 580
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Vivien B et al.: Anesthesiology 2003: 99: 9-17
BIS: importance of facial EMG
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Log EMG power across different clinical sedation levels
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Cohort of patients regaining consciousness post routine cardiac surgery
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Potential importance of encephalopathy
Pk for 1-4 versus 5-6:“Low risk” encephalopathy 0.90 (0.02)“High risk” encephalopathy 0.70 (0.04)
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The “traffic light” concept• Familiar warning colours to alert clinical staff to
absolute values and trends• Red (RASS -5) “warning”
“stop”“danger”“be alert” …etc
• Amber “intermediate state”
• Green (RASS ≥ -3) “continue”
“Go”“OK” …etc
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Derivation of “best cut-off values” to discriminate “higher” from “lower” probability of over-sedation
In absence of likely encephalopathy:Cut-off RI 35: Sensitivity 90%
Specificity 79%
RED: ≤ 20AMBER: 20-40GREEN ≥40
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Responsiveness colour in relation to RASS score
AlgorithmLapinlampi TP, Viertio-Oja HE, Helin M, et al. Canadian J Neurol Sciences 2014, 41(5):611-619
Validation and “Traffic light cut-offs”Walsh TS, Everingham K, Frame F, et al. J Crit Care 2014, 29(5):886.e881-887
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Reasons for an “unresponsive “ patient based on fEMG activity (Red/Amber)
• Muscle paralysis• Normal sleep• Illness associated coma
– Liver failure– Hypoxic brain injury– Traumatic brain injury– Severe metabolic encephalopathy
• Drug-induced coma– Excessive dosing of sedative drugs– Accumulation of sedative drugs
• Decreased levels of patient stimulation
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Excessive sedation
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• Reduction in time with “Red” Responsiveness Index
• Reduction in time to extubation
• Increase in extubationsduring 48 hrs intervention period
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Sedation Quality Assessment Tool (SQAT)
Denominator data
Pain behaviours: facial expression; limb relaxation; ventilator synchrony
Sedation state: agitation; calm/cooperative; unresponsive
Clinical status justifying deep sedation: advanced ventilation; therapeutic cooling; brain injury
Completed for every 12 hours (nursing shift)“DESIST care period” (unit of quality)
Domains
Crit Care Med 2016doi: 10.1097/CCM.0000000000001463
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Primary outcomeProportion of DESIST care periods with optimum sedationCare period without agitation, excessive sedation, poor limb relaxation, or poor ventilator synchronisation
Secondary outcomes A Primary outcome sedation quality componentsProportion of all DESIST care periods with: 1. agitation2. excessive sedation3. poor relaxation4. poor ventilator synchronisation
B Patient-level sedation outcomesNumber of DESIST care periods per mechanically ventilated patient with:1. optimum sedation 2. agitation 3. excessive sedation 4. poor relaxation 5. poor ventilator synchronisation
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Study Design: modified cluster randomised trialSetting: 8 ICUs in Scotland
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Sample size• 1600 patients (800 per study period; target 100 per site per
period)
• Modelled with various ICC values
• Assumed 70% optimum sedation rate pre-intervention, detecting 25% improvement at patient level (80% power; P = 0.05)
Analysis• multilevel generalised linear regression mixed model
• 3 levels– ICU
– Patient
– DESIST care period
• Adjustment for ICU; time period (pre-intervention or post-implementation); ICU by time period interaction; age, sex and APACHE II score
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• Monitoring supplied to all ICUs (sufficient for all ventilated patients)
• Training of staff and subsequent support available
• Staff encouraged to use “red” RI as trigger to explore potential deep sedation (prompts on screen)
• No formal protocol linking RI number to sedative drug use
DESIST Responsiveness monitoring
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DESIST Consort Diagram (Study totals)
Total number of Screened Patients
n = 9427
Excluded patients = 340
Patient died 244
Age <16 years 71
For Palliative care 25
Eligible patients n = 3127
Inclusion Criteria not met = 5960
Patient not receiving mechanical ventilation via ET tube or tracheostomy 3877
Patient has received mechanical ventilation but has been discontinued at the time of screening 1132
Extubation anticipated in the next 4 hours at time of screening 678
Patient in whom the decision to withdraw treatment has been made at time of screening 194
Patient already enrolled in the study in current hospital admission 79
Unconsented patients n = 1490
Reasons for not obtaining consent:
No one available to give consent 270
Lack of research staff 133
Not approached 243
Clinician refusal 109
Consent not obtained within 48 hours of admission 380
Other 355
Includes: Refusals Transferred out of ICU/hospital prior to consent Patients with a primary neurological diagnosis Family distress/inappropriate to approach NOK had cognitive issues
Randomised 296
Consented patients n = 1637
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Primary outcome and sedation quality outcomes at the DESIST care period level by intervention
Odds Ratio (95% CI)
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Process evaluation• DESIST Responsiveness monitoring
– time between intubation and starting monitoring median 21 hours (IQR: 11, 34)
– median duration of monitoring was 66 hours (27, 139). – First RI recorded was: red 59% (range 50-66% across ICUs),
amber 12% (range 4-17%), and green 28% (range 25-38%).– Median time to first recording green RI 9 hours (4, 23).– RI value red for 35% of monitoring time (range 23-48% across
ICUs)
• Qualitative data– Perceived by many as user friendly and a useful bedside prompt
to all staff to review sedation management. – Mixed views– Some staff did not understand the concept and questioned its
utility and validity. – Some found its presence at the bedside intrusive.
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Conclusions
• Continuous Responsiveness Index monitoring is a promising novel technology to assist decision-making during ICU sedation-analgesia
• RI has been specifically developed to detect deeper sedation states and encourage sedation review and reduction
• Future trials should test its effects on other important outcomes such as duration of ventilation and assess cost-effectiveness.
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ROYAL INFIRMARY EDINBURGH
Prof Timothy Walsh (CI)
Dr Alasdair Hay (PI)
Dr Claire Kydonaki
Fiona Pollock
Louise Boardman
Corrienne McCulloch
Heidi Dawson
David Hope
Dr Kallirroi Kefala
Dr Michael Gillies
Louise Bell
Deborah Rodgers
Sue Wright
Dr Kirsty Everingham
DUMFRIES AND GALLOWAY ROYAL INFIRMARY
Dr John Rutherford (PI)
Dr Dewi Williams
Catherine Jardine
GLASGOW ROYAL INFIRMARY
Dr Tara Quasim (PI)
Dr Alex Puxty
Steven Henderson
Naomi Hickey
Elizabeth Lennon
Jane Ireland
Natalie Dickinson
Marie Callaghan
Dominic Rimmer
VICTORIA INFIRMARY, GLASGOW
Dr Alan Davidson (PI)
Katherine McGuigan
Anissa Benchiheub
Laura Rooney
FORTH VALLEY HOSPITAL
Dr Jonathan Richards (PI)
Janice Grant
Pamela Scott
Marianne Mallice
VICTORIA HOSPITAL, KIRKCALDY
Dr Marcia McDougall (PI)
Claire McGinn
Sarah Gray
Keith Boath
Louise Doig
Lesley Berry
Edward Greenwood
Elish Daglish
Carolyne Bullions
Elaine Black
Donna Beattie
Elaine Paton
Alison Connelly
Nancy Hudson
Neville Tomkins
Julia Cook
Terry Hughes
Lynne Cairns
Jennifer Rowe
Ben Slater
Susan Russell
Bob Savage
Gavin Simpson
Ben Shippy
NINEWELLS HOSPITAL, DUNDEE
Dr Stephen Cole (PI)
Louise Cabrelli
Jackie Duffy
Pauline Amory
MONKLANDS HOSPITAL
Dr James Ruddy (PI)
Margaret Harkins
Elizabeth Reaney
Lyndsey Kearney
Angela Hamill
Isobel Paterson
EDINBURGH CLINICAL TRIALS UNIT
Jean Antonelli (Trial Manager)
Ronald Harkess
Samantha Thomas
STATISTICAL TEAM (ECTU)
Dr Christopher Weir
Robert Lee
Jacqueline Stephens
GE HEALTHCARE
Petra Peltola
Kimmo Uutela
Lasse Kamppari
Mika Sarkela
LEARNPRO (Education Module)
Christine Blaydon
Shaun McWhinnie
Edinburgh Health Services Research Unit
Dr Janet Hanley