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Predicting suicides after psychiatric hospitalization in US Army soldiers: the Army Study To Assess Risk and rEsilience in Servicemembers (Army STARRS).
Kessler, Ronald C; Warner, Christopher H; Ivany, Christopher; Petukhova, Maria V; Rose, Sherri; Bromet, Evelyn J; Brown, Millard; Cai, Tianxi; Colpe, Lisa J; Cox, Kenneth L; Fullerton, Carol S; Gilman, Stephen E; Gruber, Michael J; Heeringa, Steven G; Lewandowski-Romps, Lisa; Li, Junlong; Millikan-Bell, Amy M; Naifeh, James A; Nock, Matthew K; Rosellini, Anthony J; Sampson, Nancy A; Schoenbaum, Michael; Stein, Murray B; Wessely, Simon; Zaslavsky, Alan M; Ursano, Robert J.
Afiliação
  • Kessler RC; Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
  • Warner CH; Department of Behavioral Medicine, Blanchfield Army Community Hospital, Fort Campbell, Kentucky.
  • Ivany C; US Army Office of the Surgeon General, Falls Church, Virginia.
  • Petukhova MV; Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
  • Rose S; Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
  • Bromet EJ; Department of Psychiatry, Stony Brook University School of Medicine, Stony Brook, New York.
  • Brown M; US Army Office of the Surgeon General, Falls Church, Virginia.
  • Cai T; Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts.
  • Colpe LJ; National Institute of Mental Health, Bethesda, Maryland.
  • Cox KL; US Army Public Health Command, Aberdeen Proving Ground, Maryland.
  • Fullerton CS; Center for the Study of Traumatic Stress, Department of Psychiatry, Uniformed Services University of the Health Sciences, Bethesda, Maryland.
  • Gilman SE; Department of Social and Behavioral Sciences, Harvard School of Public Health, Boston, Massachusetts10Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts.
  • Gruber MJ; Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
  • Heeringa SG; Institute for Social Research, University of Michigan, Ann Arbor.
  • Lewandowski-Romps L; Institute for Social Research, University of Michigan, Ann Arbor.
  • Li J; Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts.
  • Millikan-Bell AM; US Army Public Health Command, Aberdeen Proving Ground, Maryland.
  • Naifeh JA; Center for the Study of Traumatic Stress, Department of Psychiatry, Uniformed Services University of the Health Sciences, Bethesda, Maryland.
  • Nock MK; Department of Psychology, Harvard University, Cambridge, Massachusetts.
  • Rosellini AJ; Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
  • Sampson NA; Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
  • Schoenbaum M; National Institute of Mental Health, Bethesda, Maryland.
  • Stein MB; Department of Psychiatry, University of California, San Diego, La Jolla14Deapartment of Family and Preventive Medicine, University of California, San Diego, La Jolla15Veterans Affairs San Diego Healthcare System, San Diego, California.
  • Wessely S; King's Centre for Military Health Research, King's College London, London, United Kingdom.
  • Zaslavsky AM; Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
  • Ursano RJ; Center for the Study of Traumatic Stress, Department of Psychiatry, Uniformed Services University of the Health Sciences, Bethesda, Maryland.
JAMA Psychiatry ; 72(1): 49-57, 2015 Jan.
Article em En | MEDLINE | ID: mdl-25390793
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Psicopatologia / Suicídio / Medição de Risco / Prevenção do Suicídio / Transtornos Mentais Tipo de estudo: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male País como assunto: America do norte Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Psicopatologia / Suicídio / Medição de Risco / Prevenção do Suicídio / Transtornos Mentais Tipo de estudo: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male País como assunto: America do norte Idioma: En Ano de publicação: 2015 Tipo de documento: Article