Sex‐Specific Risk Profiles for Suicide Among Persons with Substance Use Disorders in Denmark.
Background and Aims: Persons with substance use disorders (SUDs) are at elevated risk of suicide death. We identified novel risk factors and interactions that predict suicide among men and women with SUD using machine learning. Design Case–cohort study. Setting: Denmark. Participants: The sample was...
| Publicado en: | Addiction Vol. 116; no. 10; pp. 2882 - 2893 |
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| Autores principales: | , , , , , , , , , |
| Formato: | algorithm research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Oct2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=152291187&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 152291187 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09652140 AIO jtl: Addiction issn: 09652140 maglogo: Y pubinfo: dt: Oct2021 vid: 116 iid: 10 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 152291187 149165681 152291187 152291187 10.1111/add.15455 152291187 ppf: 2882 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Sex‐Specific Risk Profiles for Suicide Among Persons with Substance Use Disorders in Denmark. aug: au: Adams, Rachel Sayko Jiang, Tammy Rosellini, Anthony J. Horváth‐Puhó, Erzsébet Street, Amy E. Keyes, Katherine M. Cerdá, Magdalena Lash, Timothy L. Sørensen, Henrik Toft Gradus, Jaimie L. affil: Institute for Behavioral Health, Heller School for Social Policy and Management, Brandeis University, Waltham MA,, USA sug: subj: Sex Factors Suicidal Ideation Risk Factors Substance Use Disorders Denmark Suicidal Ideation Diagnosis Denmark Machine Learning Suicide Death Prospective Studies Comparative Studies Random Sample Mental Health Social Behavior Health Status Surgery, Operative Poisoning Diagnosis Antidepressive Agents Time Factors Clinical Assessment Tools Independent Variable Decision Trees Classification Human Male Female Adult Random Forest Variable Adjustment Disorders Substance Use Disorders Suicide, Attempted Psychosocial Factors Stress, Psychological Comorbidity Mental Disorders Clinical Indicators Descriptive Statistics Data Analysis Software Aged Middle Age Aged, 80 and Over Adult: 19-44 years Aged: 65+ years Middle Aged: 45-64 years Aged, 80 & over Male Female ab: Background and Aims: Persons with substance use disorders (SUDs) are at elevated risk of suicide death. We identified novel risk factors and interactions that predict suicide among men and women with SUD using machine learning. Design Case–cohort study. Setting: Denmark. Participants: The sample was restricted to persons with their first SUD diagnosis during 1995 to 2015. Cases were persons who died by suicide in Denmark during 1995 to 2015 (n = 2774) and the comparison subcohort was a 5% random sample of individuals in Denmark on 1 January 1995 (n = 13 179). Measurements Suicide death was recorded in the Danish Cause of Death Registry. Predictors included social and demographic information, mental and physical health diagnoses, surgeries, medications, and poisonings. Findings Persons among the highest risk for suicide, as identified by the classification trees, were men prescribed antidepressants in the 4 years before suicide and had a poisoning diagnosis in the 4 years before suicide; and women who were 30+ years old and had a poisoning diagnosis 4 years before and 12 months before suicide. Among men with SUD, the random forest identified five variables that were most important in predicting suicide; reaction to severe stress and adjustment disorders, drugs used to treat addictive disorders, age 30+ years, antidepressant use, and poisoning in the 4 prior years. Among women with SUD, the random forest found that the most important predictors of suicide were prior poisonings and reaction to severe stress and adjustment disorders. Individuals in the top 5% of predicted risk accounted for 15% of all suicide deaths among men and 24% of all suicides among women. Conclusions: In Denmark, prior poisoning and comorbid psychiatric disorders may be among the most important indicators of suicide risk among persons with substance use disorders, particularly among women. pubtype: Academic Journal doctype: algorithm research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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