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Enriching Populations and Enhancing Outcomes in Studies Measuring Suicidality Ecological momentary assessment (EMA) and machine learning : Digital phenotyping in suicide behavior Enrique Baca Garca Disclosure of conflict of interest


  1. Enriching Populations and Enhancing Outcomes in Studies Measuring Suicidality Ecological momentary assessment (EMA) and machine learning : Digital phenotyping in suicide behavior Enrique Baca García

  2. Disclosure of conflict of interest Grants/research support AFSP NARSAD Lilly Janssen Servier Lundbeck Otsuka Founder MeMind Eb2 E. Baca-García 2

  3. FACTS & CONTROVERSIES nd greatest cause of mortality in people 18-35 2 640.300 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 3

  4. Clinical outcome measures vs Patient reported outcomes measures measures 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) E. Baca-García 4

  5. 02 01 03 FROM SMARTCRISIS TO CNS CLINICAL TRIALS 04 DESIGN: EMA 1 OUTCOMES: 2 MBC → PROMs & PREMs EXPERIENCE: FEASIBILITY 3 PATIENT EXPERIENCE REAL TIME ANALYTIC 4 SAFETY 5 Enrique Baca-García 5

  6. RESEARCH DESIGN 1 DSG E. Baca-García 6

  7. RESEARCH DESIGN 1 DSG E. Baca-García 7

  8. RESEARCH DESIGN 1 DSG E. Baca-García 8

  9. RESEARCH DESIGN 1 DSG E. Baca-García 9

  10. COLLECT DATA AND PATIENT EXPERIENCE 1 DSG EMA IMPLICIT-PASSIVE 01 Passive Dynamic 02 EXPLICIT-ACTIVE Participative 03 04 Interactive E. Baca-García BMC Psychiatry in press 10

  11. SMARTCRISIS: DATA DENSITY 1 DSG Enrique Baca-García 11

  12. OUTCOME 2 OUT Clinical outcome measures Suicide/Suicide attempt/hospitalisation/ER Patient reported outcomes measures Wish to live/ to die Dynamic 02 Sleep Dynamic 02 Patient reported experience measures Satisfaction Participative 03 Movement Passive 01 Enrique Baca-García BMC Psychiatry in press 12

  13. 2 Patient reported outcomes measures Dynamic OUT 02 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 ** Once each 8 days Once each 4 weeks MONTH 4-6 Question/day 1-2 * Once per week ** Once each 8 days Once each 6 weeks E. Baca-García BMC Psychiatry in press 13

  14. Feasibility 3 1 EXP SMART CRISIS (n=189) WHODAS (n=1706) Refused to Refused to participate participate 13% 14% Not installed Not installed Participating 58% No upload Participating No upload 66% Refused to participate 16% UCV (n=583) Not installed Participating 59% No upload E. Baca-García 14

  15. High retention rate at 2 months (n=100) 3 EXP Active Passive Log Rank (Mantel-Cox) =,411, DF=1, P=0,522 Log Rank (Mantel-Cox) =8,77 , DF=2, P=0,012 E. Baca-García 15

  16. 180 days retention (n=199) 3 EXP Enrique Baca-García 16

  17. INTRAINDIVIDUAL VARIABLITY 3 EXP Wish to live Wish to die Wish to live/ Wish to die for patients r=.89 (IC 95% -0,94 -0.81) n=119 (896 obs) CV=24,8 CV=22,4 Enrique Baca-García 17

  18. SLEEP AS A SURROGATE MARKER 3 EXP Wish to live Correlation stability sleep satisfaction Wish to live Enrique Baca-García 18

  19. Personalisation: Indian buffet process 3 EXP Feature 0 Feature 1 Feature 2 Feature 3 Profile 1 (1452) x x x Profile 2 (738) x x Profile 3 (142) x x x Profile 4 (93) x x Profile 5 (3) Enrique Baca-García 19

  20. Pattern of Movement: Real time 4 5 RT analysis Pattern 8 Pattern 7 600 Pattern 6 Pattern 5 Pattern 4 Pattern 3 450 Pattern 2 Pattern 1 300 150 0 Median number of patterns per patient =2 E. Baca-García JMIR Mhealth Uhealth 2018 | vol. 6 | iss. 12 | e197 | p.1 20

  21. Detection based on movement patterns 5 SAFE 29/6/2018 Unstable 4/7/2018 EA Suicide Attempt Pattern change STABILITY What's behind it? E. Baca-García JMIR Mhealth Uhealth 2018 | vol. 6 | iss. 12 | e197 | p.1 21

  22. CONCLUSIONS 5 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 REAL WORLD + PERSONALISED → INTERVENTION E. Baca-García 22

  23. Thanks Enrique * Baca-Garcia * Fundacion Jimenez Diaz Sofian Berrouiguet University Hopital Brest Juan Carballo Hospital Gregorio Jose Beloso Marañon Santiago Ovejero Fundacion Jimenez Diaz Hospital Rey Juan Raquel Alvarez García Carlos Laura Mata Iturralde Fundacion Jimenez Diaz Muñoz Laura Fundacion Jimenez Diaz Lorenzo Hospital General de Ezequiel Distasio V llaba Mari a Barrigon Fundacion Jimenez Diaz Luis a David Delgado Universidad Carlos III Pablo Fernandez Navarro ISCIII Lopez Jorge University Montpleir Castroman Hilario Blasco Fontecilla HU Puerta de Hierro Lucas Giner Universidad Sevilla Ana Gomez Carrillo University of London Perez Mercedes Mount Sinai, NY Rodriguez Philippe Courtet University Montpelier Enrique Baca-García Maria Oquendo Columbia University 23

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