Risk Factors for Reattempt and Suicide ...
Document type :
Article dans une revue scientifique: Article original
DOI :
PMID :
Permalink :
Title :
Risk Factors for Reattempt and Suicide Within 6 Months After an Attempt in the French ALGOS Cohort: A Survival Tree Analysis.
Author(s) :
Demesmaeker, A. [Auteur]
Lille Neurosciences & Cognition - U 1172 [LilNCog]
Chazard, Emmanuel [Auteur]
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Vaiva, Guillaume [Auteur]
Lille Neurosciences & Cognition (LilNCog) - U 1172
Amad, Ali [Auteur]
Lille Neurosciences & Cognition - U 1172 [LilNCog]
Lille Neurosciences & Cognition - U 1172 [LilNCog]
Chazard, Emmanuel [Auteur]
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Vaiva, Guillaume [Auteur]
Lille Neurosciences & Cognition (LilNCog) - U 1172
Amad, Ali [Auteur]
Lille Neurosciences & Cognition - U 1172 [LilNCog]
Journal title :
Journal of Clinical Psychiatry
Abbreviated title :
J Clin Psychiatry
Volume number :
82
Pages :
p. 1-9
Publication date :
2021-02
ISSN :
1555-2101
HAL domain(s) :
Sciences du Vivant [q-bio]
English abstract : [en]
Objective: Understanding the cumulative effect of several risk factors involved in suicidal behavior is crucial for the development of effective prevention plans. The objective of this study is to provide clinicians with ...
Show more >Objective: Understanding the cumulative effect of several risk factors involved in suicidal behavior is crucial for the development of effective prevention plans. The objective of this study is to provide clinicians with a simple predictive model of the risk of suicide attempts and suicide within 6 months after suicide attempt. Methods: A prospective observational cohort of 972 subjects, included from January 26, 2010, to February 28, 2013, was used to perform a survival tree analysis with all sociodemographic and clinical variables available at inclusion. The results of the decision tree were then used to define a simple predictive algorithm for clinicians. Results: The results of survival tree analysis highlighted 3 subgroups of patients with an increased risk of suicide attempt or death by suicide within 6 months after suicide attempt: patients with alcohol use disorder and a previous suicide attempt with acute alcohol use (risk ratio [RR] = 2.92; 95% CI, 2.08 to 4.10), patients with anxiety disorders (RR = 0.98; 95% CI, 0.69 to 1.39), and patients with a history of more than 2 suicide attempts in the past 3 years (RR = 2.11; 95% CI, 1.25 to 3.54). The good prognosis group comprised all other patients. Conclusions: By using a data-driven method, this study identified 4 clinical factors interacting together to reduce or increase the risk of recidivism. These combinations of risk factors allow for a better evaluation of a subject’s suicide risk in clinical practice.Show less >
Show more >Objective: Understanding the cumulative effect of several risk factors involved in suicidal behavior is crucial for the development of effective prevention plans. The objective of this study is to provide clinicians with a simple predictive model of the risk of suicide attempts and suicide within 6 months after suicide attempt. Methods: A prospective observational cohort of 972 subjects, included from January 26, 2010, to February 28, 2013, was used to perform a survival tree analysis with all sociodemographic and clinical variables available at inclusion. The results of the decision tree were then used to define a simple predictive algorithm for clinicians. Results: The results of survival tree analysis highlighted 3 subgroups of patients with an increased risk of suicide attempt or death by suicide within 6 months after suicide attempt: patients with alcohol use disorder and a previous suicide attempt with acute alcohol use (risk ratio [RR] = 2.92; 95% CI, 2.08 to 4.10), patients with anxiety disorders (RR = 0.98; 95% CI, 0.69 to 1.39), and patients with a history of more than 2 suicide attempts in the past 3 years (RR = 2.11; 95% CI, 1.25 to 3.54). The good prognosis group comprised all other patients. Conclusions: By using a data-driven method, this study identified 4 clinical factors interacting together to reduce or increase the risk of recidivism. These combinations of risk factors allow for a better evaluation of a subject’s suicide risk in clinical practice.Show less >
Language :
Anglais
Audience :
Internationale
Popular science :
Non
Administrative institution(s) :
Université de Lille
CHU Lille
CHU Lille
Collections :
Submission date :
2023-11-15T06:37:47Z
2024-01-11T14:33:40Z
2024-02-27T14:49:35Z
2024-01-11T14:33:40Z
2024-02-27T14:49:35Z