Jason Shahin MD Msc FRCPC Assistant Professor McGill University Department of Critical Care

DCD overview

Withdrawal of care in the ICU

Time to death- models and important variables

Future research

•1st cadaveric transplants •Poor outcomes

•Concept of brain death emerges •Legislation adopted approving neurological definition of death •Field of transplantation is opened up

•Due to success organ need outstrips supply

•DCD re-examined

Criteria used to determine death

Time period required to confirm “irreversible death”

Autoresuscitation

Ethical considerations “violation of the dead donor rule”

Time to death prediction- warm ischemia

Resource use

60-120 minutes

“Orchestration of technology”

“Socially negotiated”

“Nuanced for each patient”

“Some people walk in and yank the endotracheal tube and

others will say “let’s stop the drugs, let’s stop the oxygen.” I

have trouble yanking out the endotracheal tube probably

because I think that it increases the chances that the patient

is going to die actively trying to breathe against an

obstructed airway. I don’t think that’s a nice way to die. I find

it a little tougher to do that than to say, “I think if we turn off

the drug he’s not going to last very long.” For me, personally,

it’s a lot easier to turn off the drug. I guess it relates to how I

see the patient’s comfort. “[interview with intensivist]

Are there variables and or models/clinical

decision rules that exist that can accurately

predict the time it will take a patient to die

after withdrawal of life sustaining therapy ?

Systematic review of the literature

1. Jason Shahin 2. Laveena Munshi

In patients who have a withdrawal of life sustaining therapy what are the risk factors/ risk prediction models/clinical decision tools that are associated with and/or predict time to death.

In the potential organ donor who has a

withdrawal of life sustaining therapy what are the risk factors/ risk prediction models/clinical decision tools that are associated with and/or predict time to death? (Class III DCD)

Participants Study type Outcome

Pediatric and adults RCT Time to death from WLST

Withdrawal of life sustaining therapy (mechanical ventilation and or hemodynamic support)

Observational studies

WLST occuring in a critical care unit

Single centre or multicentre

No case series

Collaborated with a University librarian

trained in systematic review searches

MEDLINE, EMBASE and Central

No year of publication limit

Limits: English, humans

Most variables focus on pre withdrawal physiology and clinical signs (neuro, cardiac, resp, treatment plan)

Most widely used models (University of Wisconsin) developed using small sample sizes and require a ventilator cessation trial

Other models exist but have not been externally validated yet

The Brevia model may not be generalisable

Physician assessment may be as good as any model??

www.ddepict.com

Sonny Dhanani Principal investigator- Critical Care, Children’s Hospital of Eastern Ontario, University of Ottawa-Principal investigator

Laura Hornby Clinical Research Project Manager, Montreal Children’s Hospital Research Institute

Katherine Smith Central coordinator, Loeb Research Chair in organ and tissue donation, University of Ottawa

Sam Shemie Senior investigator-Critical Care, Montreal Children's Hospital, Chair Loeb Research Consortium, Faculty of Arts, Univ. of Ottawa

Jason Shahin Lead investigator for complimentary study-time to death prediction tool-Critical Care, McGill University Health Centre

www.ddepict.com

Primary Objective To determine the incidence of

autoresuscitation (as reported by the healthcare team) in critically ill adults and children who die in the ICU, following WLST.

Criteria used to determine death

Time period required to confirm “irreversible death”

Autoresuscitation

Ethical considerations “violation of the dead donor rule”

Time to death prediction- warm ischemia

Resource use

www.ddepict.com

DePPaRT study

Complimentary study 1

Time to death prediction study

Complimentary study 2

Surrogate decision making in DCD

DePPaRT Collaborators/Co-investigators

CANADA

Andrew Baker

Stephen Beed

Jane Chamber-Evans

Jennifer Chandler

Chip Doig

Peter Dodek

Rob Fowler

Jan Friedrich

Teneille Gofton

Vanessa Gruben

AnneMarie Guerguerian

Christophe Herry

George Isac

Greg Knoll

Jim Kutsogiannis

Lauralyn McIntyre

Maureen Meade

Laveena Munshi

Tim Ramsay

Steven Reynolds

Damon Scales

Jason Shahin

Andrew Seely

Janet Squires

Alexis Turgeon

Bryan Young

US

Tom Nakagawa

Paul Shore

UK

Christian Brailsford

Dale Gardiner OTHER Frantisek Duska TRAINEES Alvin Li Loretta Norton Amanda van Beinum TEAM Laura Hornby Katherine Smith Nathan Scales

Primary Objective To develop a new reliable tool to predict time

to death following WLST in critically ill adults eligible for DCD.

Inclusion criteria

Patients who have a WLST in an ICU

Age > 1 month

Subjects will have a minimum of the following bedside monitors in place:

▪ Pulse oximeter plethysmography

▪ Continuous 3-lead electrocardiogram

▪ Invasive arterial blood pressure monitoring

▪ EEG- (a few centres)

Exclusion criteria Declared dead by NDD criteria Functioning pacemaker

GROUP 1: DCD patients had consented to be DCD donors and whose organs were

recovered

GROUP 2: “DCD Eligible” patients consented to DCD but did not proceed to donation or

GROUP 3: “DCD non-Eligible” General ICU patients Any other patients who fulfill study inclusion and

exclusion criteria but who would did not meet criteria to be considered eligible to be DCD donors.

At least 300

Up to 200

DATA COLLECTION

Demographic Comorbidities Physiological Imaging (Ct head) Analgesia and sedatives Withdrawal process Intensivist opinion Time to death

ANALYSIS

Multivariable logistic regression analysis

Parsimonious model building

Step 1-Systematic review, expert opinion

Step 2-Prospective data collection

Step 3

Model development

Step 4 Model

validation

1. More accurate prediction tool will allow health care practitioners to focus efforts on candidates with a high probability of dying within 2 hours

2. Increased confidence in and better implementation of DCD practice

Time to death is one of the major barriers to Further implementation of DCD

Existing data has contributed to understanding of important variables-but may be insufficient

Future research on death determination being carried out at a hospital near you