Ecological momentary assessment (EMA) and machine learning : … · 2019-10-04 · CV=22,4 CV=24,8...

Enrique Baca García

Ecological momentary assessment (EMA)

and machine learning : Digital phenotyping

in suicide behavior

Enriching Populations and

Enhancing Outcomes

in Studies Measuring Suicidality

E. Baca-García

Disclosure of conflict of interest

2

Grants/research support

AFSP

NARSAD

Lilly

Janssen

Servier

Lundbeck

Otsuka

Founder

MeMind

Eb2

E. Baca-García

FACTS & CONTROVERSIES

3

2nd greatest cause of mortality in people 18-35

640.300 potentially productive life years lost EU → 22€ billion in

potential income loss

Preventable but not predictable

Safety vs trauma → hospitalisation (standard of care)

Complexity vs risk stratification → personalisation

Suicidality as exclusion criteria in clinical trials

E. Baca-García

Clinical outcome measures vs Patient reported outcomes measures measures

4

Clinician: “Have you ever thought that you would be better off dead or wish you were dead?”

Patient: “ Have you ever felt that you no have desire to life?”

Wish to live/ Wish to die for patients r=.89 (IC 95% -0,94 -0.81) n=119 (896 observations)

Enrique Baca-García

FROM SMARTCRISIS TO CNS CLINICAL TRIALS

5

DESIGN: EMA1

EXPERIENCE:FEASIBILITY

PATIENT EXPERIENCE

2OUTCOMES:

MBC → PROMs & PREMs

3

REAL TIME ANALYTIC 4

SAFETY5

01

02

03

04

E. Baca-García

RESEARCH DESIGN

6

1

DSG

E. Baca-García

RESEARCH DESIGN

7

1

DSG

E. Baca-García

RESEARCH DESIGN

8

1

DSG

E. Baca-García

RESEARCH DESIGN

9

1

DSG

E. Baca-García

Participative 03

COLLECT DATA AND PATIENT EXPERIENCE

10

Dynamic02

EXPLICIT-ACTIVE

IMPLICIT-PASSIVE Passive01

Interactive04

EMA

1

DSG

BMC Psychiatry in press


SMARTCRISIS: DATA DENSITY

11

1

DSG


OUTCOME

12

Clinical outcome measures

Suicide/Suicide attempt/hospitalisation/ER

Patient reported outcomes measures

Wish to live/ to die

Sleep

Patient reported experience measures

Satisfaction

Movement Passive01

Dynamic02

Dynamic02

Participative 03

2OUT


E. Baca-García13

Patient reported outcomes measures

MONTH 1

Question/day 4

Twice per week *

Once each 4 days **Once each 2 weeks

MONTH 2-3

Question/day 2

Once per week *


MONTH 4-6

Question/day 1-2

Once per week *


Dynamic022

OUT


E. Baca-García14

Feasibility1

Refused to participate

14%

Not installed

No upload

Participating66%

SMART CRISIS (n=189) WHODAS (n=1706)


13%

Not installed

No upload

Participating58%


16%

Not installed

No upload

Participating59%

UCV (n=583)

3

EXP

E. Baca-García15

High retention rate at 2 months (n=100)

ActiveLog Rank (Mantel-Cox) =,411, DF=1, P=0,522

PassiveLog Rank (Mantel-Cox) =8,77 , DF=2, P=0,012

3

EXP


180 days retention (n=199)

16

3

EXP


INTRAINDIVIDUAL VARIABLITY

17

3

EXP

Wish to live Wish to die

CV=24,8CV=22,4

Wish to live/ Wish to die for patients r=.89 (IC 95% -0,94 -0.81) n=119 (896 obs)


SLEEP AS A SURROGATE MARKER

18

3

EXP

Wish to live

Correlation stability

sleep satisfaction

Wish to live


Personalisation: Indian buffet process

19

Feature 0 Feature 1 Feature 2 Feature 3

Profile 1 (1452) xProfile 2 (738) x xProfile 3 (142) x xProfile 4 (93) x x xProfile 5 (3) x x

3

EXP

E. Baca-García20

5Pattern of Movement: Real time

analysis4

RT

0

150

300

450

600Pattern 8 Pattern 7

Pattern 6 Pattern 5

Pattern 4 Pattern 3

Pattern 2 Pattern 1

Median number of patterns per patient =2

JMIR Mhealth Uhealth 2018 | vol. 6 | iss. 12 | e197 | p.1

E. Baca-García

STABILITY

21

Detection based on movement patterns

29/6/2018

Unstable

Pattern change

4/7/2018

EA Suicide Attempt

What's behind it?

5SAFE

JMIR Mhealth Uhealth 2018 | vol. 6 | iss. 12 | e197 | p.1

E. Baca-García22

CONCLUSIONS5

REAL WORLD + PERSONALISED → INTERVENTION

Access to real world with patient acceptability and minimal interference

Massive sampling

Assessing and analysing in real time

Measures variability

Sleep and movement as suicide behaviour markers


Thanks

23

Enrique * Baca-Garcia * Fundacion Jimenez Diaz

Sofian Berrouiguet University Hopital Brest

Juan

Jose

Carballo

Beloso

Hospital Gregorio

Marañon

Santiago Ovejero Fundacion Jimenez Diaz

Raquel Alvarez GarcíaHospital Rey Juan

Carlos

Laura Mata Iturralde Fundacion Jimenez Diaz

LauraMuñoz

LorenzoFundacion Jimenez Diaz

Ezequiel DistasioHospital General de

V llaba

Mari

a

Luis

a

Barrigon Fundacion Jimenez Diaz

David Delgado Universidad Carlos III

Pablo Fernandez Navarro ISCIII

JorgeLopez

CastromanUniversity Montpleir

Hilario Blasco Fontecilla HU Puerta de Hierro

Lucas Giner Universidad Sevilla

Ana Gomez Carrillo University of London

MercedesPerez

RodriguezMount Sinai, NY

Philippe Courtet University Montpelier

Maria Oquendo Columbia University

Ecological momentary assessment (EMA) and machine learning : … · 2019-10-04 · CV=22,4 CV=24,8...

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