Literature DB >> 25390793

Predicting suicides after psychiatric hospitalization in US Army soldiers: the Army Study To Assess Risk and rEsilience in Servicemembers (Army STARRS).

Ronald C Kessler1, Christopher H Warner2, Christopher Ivany3, Maria V Petukhova1, Sherri Rose1, Evelyn J Bromet4, Millard Brown3, Tianxi Cai5, Lisa J Colpe6, Kenneth L Cox7, Carol S Fullerton8, Stephen E Gilman9, Michael J Gruber1, Steven G Heeringa10, Lisa Lewandowski-Romps10, Junlong Li5, Amy M Millikan-Bell7, James A Naifeh8, Matthew K Nock11, Anthony J Rosellini1, Nancy A Sampson1, Michael Schoenbaum6, Murray B Stein12, Simon Wessely13, Alan M Zaslavsky1, Robert J Ursano8.   

Abstract

IMPORTANCE: The US Army experienced a sharp increase in soldier suicides beginning in 2004. Administrative data reveal that among those at highest risk are soldiers in the 12 months after inpatient treatment of a psychiatric disorder.
OBJECTIVE: To develop an actuarial risk algorithm predicting suicide in the 12 months after US Army soldier inpatient treatment of a psychiatric disorder to target expanded posthospitalization care. DESIGN, SETTING, AND PARTICIPANTS: There were 53,769 hospitalizations of active duty soldiers from January 1, 2004, through December 31, 2009, with International Classification of Diseases, Ninth Revision, Clinical Modification psychiatric admission diagnoses. Administrative data available before hospital discharge abstracted from a wide range of data systems (sociodemographic, US Army career, criminal justice, and medical or pharmacy) were used to predict suicides in the subsequent 12 months using machine learning methods (regression trees and penalized regressions) designed to evaluate cross-validated linear, nonlinear, and interactive predictive associations. MAIN OUTCOMES AND MEASURES: Suicides of soldiers hospitalized with psychiatric disorders in the 12 months after hospital discharge.
RESULTS: Sixty-eight soldiers died by suicide within 12 months of hospital discharge (12.0% of all US Army suicides), equivalent to 263.9 suicides per 100,000 person-years compared with 18.5 suicides per 100,000 person-years in the total US Army. The strongest predictors included sociodemographics (male sex [odds ratio (OR), 7.9; 95% CI, 1.9-32.6] and late age of enlistment [OR, 1.9; 95% CI, 1.0-3.5]), criminal offenses (verbal violence [OR, 2.2; 95% CI, 1.2-4.0] and weapons possession [OR, 5.6; 95% CI, 1.7-18.3]), prior suicidality [OR, 2.9; 95% CI, 1.7-4.9], aspects of prior psychiatric inpatient and outpatient treatment (eg, number of antidepressant prescriptions filled in the past 12 months [OR, 1.3; 95% CI, 1.1-1.7]), and disorders diagnosed during the focal hospitalizations (eg, nonaffective psychosis [OR, 2.9; 95% CI, 1.2-7.0]). A total of 52.9% of posthospitalization suicides occurred after the 5% of hospitalizations with highest predicted suicide risk (3824.1 suicides per 100,000 person-years). These highest-risk hospitalizations also accounted for significantly elevated proportions of several other adverse posthospitalization outcomes (unintentional injury deaths, suicide attempts, and subsequent hospitalizations). CONCLUSIONS AND RELEVANCE: The high concentration of risk of suicide and other adverse outcomes might justify targeting expanded posthospitalization interventions to soldiers classified as having highest posthospitalization suicide risk, although final determination requires careful consideration of intervention costs, comparative effectiveness, and possible adverse effects.

Entities:  

Mesh:

Year:  2015        PMID: 25390793      PMCID: PMC4286426          DOI: 10.1001/jamapsychiatry.2014.1754

Source DB:  PubMed          Journal:  JAMA Psychiatry        ISSN: 2168-622X            Impact factor:   21.596


  34 in total

1.  Suicide incidence and risk factors in an active duty US military population.

Authors:  Jeffrey Hyman; Robert Ireland; Lucinda Frost; Linda Cottrell
Journal:  Am J Public Health       Date:  2012-01-25       Impact factor: 9.308

2.  Deaths by suicide while on active duty, active and reserve components, U.S. Armed Forces, 1998-2011.

Authors: 
Journal:  MSMR       Date:  2012-06

Review 3.  Clinical versus actuarial judgment.

Authors:  R M Dawes; D Faust; P E Meehl
Journal:  Science       Date:  1989-03-31       Impact factor: 47.728

4.  Focusing suicide prevention on periods of high risk.

Authors:  Mark Olfson; Steven C Marcus; Jeffrey A Bridge
Journal:  JAMA       Date:  2014-03-19       Impact factor: 56.272

5.  A probabilistic system for identifying suicide attemptors.

Authors:  D H Gustafson; J H Greist; F F Stauss; H Erdman; T Laughren
Journal:  Comput Biomed Res       Date:  1977-04

6.  The Army study to assess risk and resilience in servicemembers (Army STARRS).

Authors:  Robert J Ursano; Lisa J Colpe; Steven G Heeringa; Ronald C Kessler; Michael Schoenbaum; Murray B Stein
Journal:  Psychiatry       Date:  2014       Impact factor: 2.458

7.  Measuring the suicidal mind: implicit cognition predicts suicidal behavior.

Authors:  Matthew K Nock; Jennifer M Park; Christine T Finn; Tara L Deliberto; Halina J Dour; Mahzarin R Banaji
Journal:  Psychol Sci       Date:  2010-03-09

8.  Suicide within two weeks of discharge from psychiatric inpatient care: a case-control study.

Authors:  Harriet Bickley; Isabelle M Hunt; Kirsten Windfuhr; Jenny Shaw; Louis Appleby; Navneet Kapur
Journal:  Psychiatr Serv       Date:  2013-07-01       Impact factor: 3.084

9.  Regularization Paths for Generalized Linear Models via Coordinate Descent.

Authors:  Jerome Friedman; Trevor Hastie; Rob Tibshirani
Journal:  J Stat Softw       Date:  2010       Impact factor: 6.440

Review 10.  Review of predictors of suicide within 1 year of discharge from a psychiatric hospital.

Authors:  Talia Troister; Paul S Links; John Cutcliffe
Journal:  Curr Psychiatry Rep       Date:  2008-02       Impact factor: 8.081

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  129 in total

Review 1.  Self-injurious thoughts and behaviors as risk factors for future suicide ideation, attempts, and death: a meta-analysis of longitudinal studies.

Authors:  J D Ribeiro; J C Franklin; K R Fox; K H Bentley; E M Kleiman; B P Chang; M K Nock
Journal:  Psychol Med       Date:  2015-09-15       Impact factor: 7.723

2.  Association Between Social Integration and Suicide Among Women in the United States.

Authors:  Alexander C Tsai; Michel Lucas; Ichiro Kawachi
Journal:  JAMA Psychiatry       Date:  2015-10       Impact factor: 21.596

3.  Suicide mortality among male veterans discharged from Veterans Health Administration acute psychiatric units from 2005 to 2010.

Authors:  Peter C Britton; Kipling M Bohnert; Mark A Ilgen; Cathleen Kane; Brady Stephens; Wilfred R Pigeon
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2017-04-11       Impact factor: 4.328

4.  Magnetic resonance imaging texture predicts progression to dementia due to Alzheimer disease earlier than hippocampal volume

Authors:  Subin Lee; Hyunna Lee; Ki Woong Kim
Journal:  J Psychiatry Neurosci       Date:  2020-01-01       Impact factor: 6.186

5.  Developing a Risk Model to Target High-risk Preventive Interventions for Sexual Assault Victimization among Female U.S. Army Soldiers.

Authors:  Amy E Street; Anthony J Rosellini; Robert J Ursano; Steven G Heeringa; Eric D Hill; John Monahan; James A Naifeh; Maria V Petukhova; Ben Y Reis; Nancy A Sampson; Paul D Bliese; Murray B Stein; Alan M Zaslavsky; Ronald C Kessler
Journal:  Clin Psychol Sci       Date:  2016-07-29

6.  Predicting Suicide Attempts and Suicide Deaths Following Outpatient Visits Using Electronic Health Records.

Authors:  Gregory E Simon; Eric Johnson; Jean M Lawrence; Rebecca C Rossom; Brian Ahmedani; Frances L Lynch; Arne Beck; Beth Waitzfelder; Rebecca Ziebell; Robert B Penfold; Susan M Shortreed
Journal:  Am J Psychiatry       Date:  2018-05-24       Impact factor: 18.112

7.  Psychiatric Risk Assessment from the Clinician's Perspective: Lessons for the Future.

Authors:  Alex S Cohen; Taylor Fedechko; Elana K Schwartz; Thanh P Le; Peter W Foltz; Jared Bernstein; Jian Cheng; Elizabeth Rosenfeld; Brita Elvevåg
Journal:  Community Ment Health J       Date:  2019-06-01

8.  Efficient Exploration of Many Variables and Interactions Using Regularized Regression.

Authors:  Tyson S Barrett; Ginger Lockhart
Journal:  Prev Sci       Date:  2019-05

Review 9.  Digital Suicide Prevention: Can Technology Become a Game-changer?

Authors:  Arshya Vahabzadeh; Ned Sahin; Amir Kalali
Journal:  Innov Clin Neurosci       Date:  2016-06-01

Review 10.  Suicide Rates After Discharge From Psychiatric Facilities: A Systematic Review and Meta-analysis.

Authors:  Daniel Thomas Chung; Christopher James Ryan; Dusan Hadzi-Pavlovic; Swaran Preet Singh; Clive Stanton; Matthew Michael Large
Journal:  JAMA Psychiatry       Date:  2017-07-01       Impact factor: 21.596

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