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The Prediction of Suicide: Sensitivity, Specificity, and Predictive Value of a Multivariate Model Applied to Suicide Among 1906 Patients With Affective Disorders
Abstract
Stepwise multiple logistic regression was utilized in an attempt to develop a statistical model that would predict suicide in a group of 1906 Iowans with affective disorders admitted to a tertiary care hospital. The risk factors identified by this approach included the number of prior suicide attempts, suicidal ideation on admission, bipolar affective disorder (manic or mixed type), gender, outcome at discharge, and unipolar depressive disorder in individuals with a family history of mania. However, the model failed to identify any of the patients who committed suicide. The results appear to support the contention that, based on present knowledge, it is not possible to predict suicide, even among a high-risk group of inpatients.
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“Goldstein (1991)[10] Patients admitted with affective disorders to University of Iowa Psychiatric Hospital 1,901 patients, 46 suicides 84 21 clinical variables with final score of 6 significant predictors on logistic regression Exploratory.”
BackgroundA risk index for 12-month suicide attempts in the National Comorbidity Survey Replication (NCS-R)
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Metadata
- Authors
- Goldstein, R. B.
- Venue
- Archives of General Psychiatry
- Publisher
- American Medical Association (AMA)
- Published
- 1991-05-01
- Volume
- 48
- Issue
- 5
- Pages
- 418
- ISSN
- 0003-990X (ISSN-L)
- OpenAlex
- W2074042904
- Cited by
- 402
- References
- 1
- FWCI
- 14.96
- Type
- journal article
- Language
- en
- Open access
- closed
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