Literature DB >> 25257065

Determinants of completed railway suicides by psychiatric in-patients: case-control study.

Karoline Lukaschek1, Jens Baumert1, Marion Krawitz1, Natalia Erazo1, Hans Förstl1, Karl-Heinz Ladwig1.   

Abstract

BACKGROUND: Suicide prediction during psychiatric in-patient treatment remains an unresolved challenge. AIMS: To identify determinants of railway suicides in individuals receiving in-patient psychiatric treatment.
METHOD: The study population was drawn from patients admitted to six psychiatric hospitals in Germany during a 10-year period (1997-2006). Data from 101 railway suicide cases were compared with a control group of 101 discharged patients matched for age, gender and diagnosis.
RESULTS: Predictors of suicide were change of therapist (OR = 22.86, P = 0.004), suicidal ideation (OR = 7.92, P<0.001), negative or unchanged therapeutic course (OR = 7.73, P<0.001), need of polypharmaceutical treatment (OR = 2.81, P = 0.04) and unemployment (OR = 2.72, P = 0.04). Neither restlessness nor impulsivity predicted in-patient suicide.
CONCLUSIONS: Suicidal ideation, unfavourable clinical course and the use of multiple psychotropic substances (reflecting the severity of illness) were strong determinants of railway suicides. The most salient finding was the vital impact of a change of therapist. These findings deserve integration into the clinical management of patients with serious mental disease. Royal College of Psychiatrists.

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Year:  2014        PMID: 25257065     DOI: 10.1192/bjp.bp.113.139352

Source DB:  PubMed          Journal:  Br J Psychiatry        ISSN: 0007-1250            Impact factor:   9.319


  7 in total

1.  Suicidal ideation and subsequent completed suicide in both psychiatric and non-psychiatric populations: a meta-analysis.

Authors:  A A M Hubers; S Moaddine; S H M Peersmann; T Stijnen; E van Duijn; R C van der Mast; O M Dekkers; E J Giltay
Journal:  Epidemiol Psychiatr Sci       Date:  2016-12-19       Impact factor: 6.892

2.  Gender Differences in Machine Learning Models of Trauma and Suicidal Ideation in Veterans of the Iraq and Afghanistan Wars.

Authors:  Jaimie L Gradus; Matthew W King; Isaac Galatzer-Levy; Amy E Street
Journal:  J Trauma Stress       Date:  2017-07-25

3.  Suicide risk after psychiatric discharge: study protocol of a naturalistic, long-term, prospective observational study.

Authors:  Tim J Krause; Jasmin Schneider; Annette Lederer; Magdalena Sauer; Cathrin Sauer; Burkhard Jabs; Elmar Etzersdorfer; Axel Genz; Michael Bauer; Susann Richter; Dan Rujescu; Ute Lewitzka
Journal:  Pilot Feasibility Stud       Date:  2020-09-30

4.  Demographics as predictors of suicidal thoughts and behaviors: A meta-analysis.

Authors:  Xieyining Huang; Jessica D Ribeiro; Katherine M Musacchio; Joseph C Franklin
Journal:  PLoS One       Date:  2017-07-10       Impact factor: 3.240

5.  Meta-analysis of the strength of exploratory suicide prediction models; from clinicians to computers.

Authors:  Michelle Corke; Katherine Mullin; Helena Angel-Scott; Shelley Xia; Matthew Large
Journal:  BJPsych Open       Date:  2021-01-07

6.  Clinical Characteristics Associated with Suicide Attempts in Clinical Settings: A Comparison of Suicidal and Non-Suicidal Depressed Inpatients.

Authors:  Carla Gramaglia; Alessandro Feggi; Paola Bergamasco; Fabrizio Bert; Eleonora Gattoni; Debora Marangon; Roberta Siliquini; Eugenio Torre; Patrizia Zeppegno
Journal:  Front Psychiatry       Date:  2016-06-20       Impact factor: 4.157

7.  Association between suicidal ideation and suicide: meta-analyses of odds ratios, sensitivity, specificity and positive predictive value.

Authors:  Catherine M McHugh; Amy Corderoy; Christopher James Ryan; Ian B Hickie; Matthew Michael Large
Journal:  BJPsych Open       Date:  2019-03
  7 in total

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