TY - JOUR PY - 2023// TI - Risk of death by suicide following self-harm presentations to healthcare: development and validation of a multivariable clinical prediction rule (OxSATS) JO - BMJ mental health A1 - Fazel, Seena A1 - Vazquez-Montes, Maria D. L. A. A1 - Molero, Yasmina A1 - Runeson, Bo A1 - D'Onofrio, Brian M. A1 - Larsson, Henrik A1 - Lichtenstein, Paul A1 - Walker, Jane A1 - Sharpe, Michael A1 - Fanshawe, Thomas R. SP - e300673 EP - e300673 VL - 26 IS - 1 N2 - BACKGROUND: Assessment of suicide risk in individuals who have self-harmed is common in emergency departments, but is often based on tools developed for other purposes.

OBJECTIVE: We developed and validated a predictive model for suicide following self-harm.

METHODS: We used data from Swedish population-based registers. A cohort of 53 172 individuals aged 10+ years, with healthcare episodes of self-harm, was split into development (37 523 individuals, of whom 391 died from suicide within 12 months) and validation (15 649 individuals, 178 suicides within 12 months) samples. We fitted a multivariable accelerated failure time model for the association between risk factors and time to suicide. The final model contains 11 factors: age, sex, and variables related to substance misuse, mental health and treatment, and history of self-harm. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis guidelines were followed for the design and reporting of this work.

FINDINGS: An 11-item risk model to predict suicide was developed using sociodemographic and clinical risk factors, and showed good discrimination (c-index 0.77, 95% CI 0.75 to 0.78) and calibration in external validation. For risk of suicide within 12 months, using a 1% cut-off, sensitivity was 82% (75% to 87%) and specificity was 54% (53% to 55%). A web-based risk calculator is available (Oxford Suicide Assessment Tool for Self-harm or OxSATS).

CONCLUSIONS: OxSATS accurately predicts 12-month risk of suicide. Further validations and linkage to effective interventions are required to examine clinical utility. CLINICAL IMPLICATIONS: Using a clinical prediction score may assist clinical decision-making and resource allocation.

Language: en

LA - en SN - 2755-9734 UR - http://dx.doi.org/10.1136/bmjment-2023-300673 ID - ref1 ER -