Intensive longitudinal assessment following index trauma to predict development of PTSD using machine learning

Adam Horwitz¹, Kaitlyn McCarthy², Stacey L House³, Francesca L Beaudoin⁴, Xinming An⁵, Thomas C Neylan⁶, Gari D Clifford⁷, Sarah D Linnstaedt⁵, Laura T Germine⁸, Scott L Rauch⁹, John P Haran¹⁰, Alan B Storrow¹¹, Christopher Lewandowski¹², Paul I Musey Jr¹³, Phyllis L Hendry¹⁴, Sophia Sheikh¹⁴, Christopher W Jones¹⁵, Brittany E Punches¹⁶, Robert A Swor¹⁷, Lauren A Hudak¹⁸, Jose L Pascual¹⁹, Mark J Seamon²⁰, Erica Harris²¹, Claire Pearson²², David A Peak²³, Robert M Domeier²⁴, Niels K Rathlev²⁵, Paulina Sergot²⁶, Leon D Sanchez²⁷, Steven E Bruce²⁸, Jutta Joormann²⁹, Steven E Harte³⁰, Karestan C Koenen³¹, Samuel A McLean³², Srijan Sen²

Affiliations

¹ Department of Psychiatry, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: ahor@umich.edu.
² Department of Psychiatry, University of Michigan, Ann Arbor, MI 48109, USA.
³ Department of Emergency Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA.
⁴ Department of Epidemiology, Brown University, Providence, RI 02930, USA; Department of Emergency Medicine, Brown University, Providence, RI 02930, USA.
⁵ Institute for Trauma Recovery, Department of Anesthesiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27559, USA.
⁶ Departments of Psychiatry and Neurology, University of California San Francisco, San Francisco, CA 94143, USA.
⁷ Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA 30332, USA; Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.
⁸ Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA 02478, USA; The Many Brains Project, Belmont, MA 02478, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA.
⁹ Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA 02478, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA; Department of Psychiatry, McLean Hospital, Belmont, MA 02478, USA.
¹⁰ Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, MA 01655, USA.
¹¹ Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA.
¹² Department of Emergency Medicine, Henry Ford Health System, Detroit, MI 48202, USA.
¹³ Department of Emergency Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
¹⁴ Department of Emergency Medicine, University of Florida College of Medicine -Jacksonville, Jacksonville, FL 32209, USA.
¹⁵ Department of Emergency Medicine, Cooper Medical School of Rowan University, Camden, NJ 08103, USA.
¹⁶ Department of Emergency Medicine, Ohio State University College of Medicine, Columbus, OH 43210, USA; Ohio State University College of Nursing, Columbus, OH 43210, USA.
¹⁷ Department of Emergency Medicine, Oakland University William Beaumont School of Medicine, Rochester, MI 48309, USA.
¹⁸ Department of Emergency Medicine, Emory University School of Medicine, Atlanta, GA 30329, USA.
¹⁹ Department of Surgery, Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA 19104, USA; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
²⁰ Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Surgery, Division of Traumatology, Surgical Critical Care and Emergency Surgery, University of Pennsylvania, Philadelphia, PA 19104, USA.
²¹ Department of Emergency Medicine, Einstein Medical Center, Philadelphia, PA 19107, USA.
²² Department of Emergency Medicine, Wayne State University, Ascension St. John Hospital, Detroit, MI 48202, USA.
²³ Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA 02114, USA.
²⁴ Department of Emergency Medicine, Trinity Health-Ann Arbor, Ypsilanti, MI 48197, USA.
²⁵ Department of Emergency Medicine, University of Massachusetts Medical School-Baystate, Springfield, MA 01107, USA.
²⁶ Department of Emergency Medicine, McGovern Medical School at UTHealth, Houston, TX 77030, USA.
²⁷ Department of Emergency Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Emergency Medicine, Harvard Medical School, Boston, MA 02115, USA.
²⁸ Department of Psychological Sciences, University of Missouri - St. Louis, St. Louis, MO 63121, USA.
²⁹ Department of Psychology, Yale University, New Haven, CT 06510, USA.
³⁰ Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA; Department of Internal Medicine-Rheumatology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
³¹ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA.
³² Department of Emergency Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27559, USA; Institute for Trauma Recovery, Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27559, USA.

PMID: 38723405
PMCID: PMC11215748
DOI: 10.1016/j.janxdis.2024.102876

Intensive longitudinal assessment following index trauma to predict development of PTSD using machine learning

Adam Horwitz et al. J Anxiety Disord. 2024 Jun.

. 2024 Jun:104:102876.

doi: 10.1016/j.janxdis.2024.102876. Epub 2024 May 5.

Authors

Affiliations

¹ Department of Psychiatry, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: ahor@umich.edu.
² Department of Psychiatry, University of Michigan, Ann Arbor, MI 48109, USA.
³ Department of Emergency Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA.
⁴ Department of Epidemiology, Brown University, Providence, RI 02930, USA; Department of Emergency Medicine, Brown University, Providence, RI 02930, USA.
⁵ Institute for Trauma Recovery, Department of Anesthesiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27559, USA.
⁶ Departments of Psychiatry and Neurology, University of California San Francisco, San Francisco, CA 94143, USA.
⁷ Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA 30332, USA; Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.
⁸ Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA 02478, USA; The Many Brains Project, Belmont, MA 02478, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA.
⁹ Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA 02478, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA; Department of Psychiatry, McLean Hospital, Belmont, MA 02478, USA.
¹⁰ Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, MA 01655, USA.
¹¹ Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA.
¹² Department of Emergency Medicine, Henry Ford Health System, Detroit, MI 48202, USA.
¹³ Department of Emergency Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
¹⁴ Department of Emergency Medicine, University of Florida College of Medicine -Jacksonville, Jacksonville, FL 32209, USA.
¹⁵ Department of Emergency Medicine, Cooper Medical School of Rowan University, Camden, NJ 08103, USA.
¹⁶ Department of Emergency Medicine, Ohio State University College of Medicine, Columbus, OH 43210, USA; Ohio State University College of Nursing, Columbus, OH 43210, USA.
¹⁷ Department of Emergency Medicine, Oakland University William Beaumont School of Medicine, Rochester, MI 48309, USA.
¹⁸ Department of Emergency Medicine, Emory University School of Medicine, Atlanta, GA 30329, USA.
¹⁹ Department of Surgery, Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA 19104, USA; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
²⁰ Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Surgery, Division of Traumatology, Surgical Critical Care and Emergency Surgery, University of Pennsylvania, Philadelphia, PA 19104, USA.
²¹ Department of Emergency Medicine, Einstein Medical Center, Philadelphia, PA 19107, USA.
²² Department of Emergency Medicine, Wayne State University, Ascension St. John Hospital, Detroit, MI 48202, USA.
²³ Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA 02114, USA.
²⁴ Department of Emergency Medicine, Trinity Health-Ann Arbor, Ypsilanti, MI 48197, USA.
²⁵ Department of Emergency Medicine, University of Massachusetts Medical School-Baystate, Springfield, MA 01107, USA.
²⁶ Department of Emergency Medicine, McGovern Medical School at UTHealth, Houston, TX 77030, USA.
²⁷ Department of Emergency Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Emergency Medicine, Harvard Medical School, Boston, MA 02115, USA.
²⁸ Department of Psychological Sciences, University of Missouri - St. Louis, St. Louis, MO 63121, USA.
²⁹ Department of Psychology, Yale University, New Haven, CT 06510, USA.
³⁰ Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA; Department of Internal Medicine-Rheumatology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
³¹ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA.
³² Department of Emergency Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27559, USA; Institute for Trauma Recovery, Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27559, USA.

PMID: 38723405
PMCID: PMC11215748
DOI: 10.1016/j.janxdis.2024.102876

Abstract

There are significant challenges to identifying which individuals require intervention following exposure to trauma, and a need for strategies to identify and provide individuals at risk for developing PTSD with timely interventions. The present study seeks to identify a minimal set of trauma-related symptoms, assessed during the weeks following traumatic exposure, that can accurately predict PTSD. Participants were 2185 adults (Mean age=36.4 years; 64% women; 50% Black) presenting for emergency care following traumatic exposure. Participants received a 'flash survey' with 6-8 varying symptoms (from a pool of 26 trauma symptoms) several times per week for eight weeks following the trauma exposure (each symptom assessed ∼6 times). Features (mean, sd, last, worst, peak-end scores) from the repeatedly assessed symptoms were included as candidate variables in a CART machine learning analysis to develop a pragmatic predictive algorithm. PTSD (PCL-5 ≥38) was present for 669 (31%) participants at the 8-week follow-up. A classification tree with three splits, based on mean scores of nervousness, rehashing, and fatigue, predicted PTSD with an Area Under the Curve of 0.836. Findings suggest feasibility for a 3-item assessment protocol, delivered once per week, following traumatic exposure to assess and potentially facilitate follow-up care for those at risk.

Keywords: Emergency services; Machine learning; Mobile assessment; Posttraumatic stress disorder; Trauma.

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Conflict of interest statement

Declaration of Competing Interest Dr. Neylan has received research support from NIH, VA, and Rainwater Charitable Foundation, and consulting income from Jazz Pharmaceuticals. In the last three years Dr. Clifford has received research funding from the NSF, NIH and LifeBell AI, and unrestricted donations from AliveCor Inc, Amazon Research, the Center for Discovery, the Gates Foundation, Google, the Gordon and Betty Moore Foundation, MathWorks, Microsoft Research, Nextsense Inc, One Mind Foundation, and the Rett Research Foundation. Dr. Clifford has financial interest in AliveCor Inc and Nextsense Inc. He also is the CTO of MindChild Medical with significant stock. These relationships are unconnected to the current work. Dr. Germine receives funding from the National Institute of Mental Health (R01 MH121617) and is on the board of the Many Brains Project. Her family also has equity in Intelerad Medical Systems, Inc. Dr. Rauch reported serving as secretary of the Society of Biological Psychiatry; serving as a board member of Community Psychiatry and Mindpath Health; serving as a board member of National Association of Behavioral Healthcare; serving as secretary and a board member for the Anxiety and Depression Association of America; serving as a board member of the National Network of Depression Centers; receiving royalties from Oxford University Press, American Psychiatric Publishing Inc, and Springer Publishing; and receiving personal fees from the Society of Biological Psychiatry, Community Psychiatry and Mindpath Health, and National Association of Behavioral Healthcare outside the submitted work. Dr. Jones has no competing interests related to this work, though he has been an investigator on studies funded by AstraZeneca, Vapotherm, Abbott, and Ophirex. Dr. Joormann receives consulting payments from Janssen Pharmaceuticals. Dr. Harte has no competing interest related to this work, though in the last three years he has received research funding from Aptinyx and Arbor Medical Innovations, and consulting payments from Aptinyx. Dr. Koenen’s research has been supported by the Robert Wood Johnson Foundation, the Kaiser Family Foundation, the Harvard Center on the Developing Child, Stanley Center for Psychiatric Research at the Broad Institute of MIT and Harvard, the National Institutes of Health, One Mind, Anonymous Philanthropy, LLC, and Cohen Veterans Bioscience. She has been a paid consultant for the US Department of Justice and Covington Burling, LLP over the last three years. She has been a paid external reviewer for the Chan Zuckerberg Foundation, the University of Cape Town, and Capita Ireland. She has had paid speaking engagements in the last three years with the American Psychological Association, European Central Bank. Sigmund Freud University – Milan, Cambridge Health Alliance, and Coverys. She receives royalties from Guilford Press and Oxford University Press. Dr. McLean has served as a consultant for Walter Reed Army Institute for Research, Arbor Medical Innovations, and BioXcel Therapeutics, Inc.

Figures

**Figure 1**
CART Classification Algorithm for Probable PTSD Note. PTSD was defined as PCL-5 score ≥ 38. Nervous_mean = aggregated mean score from intermittent flash surveys over 8 weeks (0–4 range) of “feeling very nervous, worried, or anxious.” Rehash_mean = aggregated mean score from intermittent flash surveys over 8 weeks (0–4 range) of “finding yourself ‘re-hashing’ the circumstances related to the event.” Fatigue_mean = aggregated mean score from intermittent flash surveys over 8 weeks (0–10 range) of “having problems with fatigue.”

**Figure 2**
Variable Importance Features from Classification Trees

**Figure 3**
Receiver Operating Characteristic (ROC) Curve Using Derived Algorithm with Testing Data Note. The three coordinates (0.25, 0.50, 0.75) correspond to predicted probability thresholds of having PTSD, as determined by the algorithm in Figure 1 (i.e., someone with ‘nervous_mean’ above 2.08, a ‘rehash_mean’ score below 2.55, and a ‘fatigue_mean’ below 7.08 would have a 0.32 predicted probability of PTSD; someone with a ‘nervous_mean’ below 2.08 would have a 0.09 predicted probability). The parenthesized specificity and sensitivity metrics are derived when individuals with the specified probability (or higher) are predicted to have PTSD.

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Intensive longitudinal assessment following index trauma to predict development of PTSD using machine learning

Affiliations

Intensive longitudinal assessment following index trauma to predict development of PTSD using machine learning

Authors

Affiliations

Abstract

Conflict of interest statement

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References

MeSH terms

Grants and funding

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Medical