Evidence map›Paper›PMID 37385664›Full record

ArticleBMJ mental health2023

Risk of death by suicide following self-harm presentations to healthcare: development and validation of a multivariable clinical prediction rule (OxSATS).

Seena Fazel, Maria D L A Vazquez-Montes, Yasmina Molero, Bo Runeson, Brian M D'Onofrio, Henrik Larsson, Paul Lichtenstein, Jane Walker, Michael Sharpe, Thomas R Fanshawe

Abstract read
In one paragraph

Article in BMJ mental health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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  9. Evaluating Machine Learning for Predicting Youth Suicidal Behavior Up to 1 Year After Contact With Mental-Health Specialty Care.Clinical psychological science : a journal of the Association for Psychological Science · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Seena FazelPsychiatry, University of Oxford, Oxford, UK seena.fazel@psych.ox.ac.uk.ORCID 0000-0002-5383-5365
Maria D L A Vazquez-MontesNuffield Department of Primary Health Care Sciences, University of Oxford, Oxford, UK.
Yasmina MoleroDepartment of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
Bo RunesonDepartment of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden.
Brian M D'OnofrioDepartment of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
Henrik LarssonDepartment of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
Paul LichtensteinDepartment of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
Jane WalkerPsychological Medicine Research Department of Psychiatry, University of Oxford, Oxford, UK.
Michael SharpePsychological Medicine Research Department of Psychiatry, University of Oxford, Oxford, UK.
Thomas R FanshaweNuffield Department of Primary Health Care Sciences, University of Oxford, Oxford, UK.

Funding

Wellcome Trust 202836/Z/16/Z
6 · The paper itself

Abstract

backgroundAssessment of suicide risk in individuals who have self-harmed is common in emergency departments, but is often based on tools developed for other purposes.

objectiveWe developed and validated a predictive model for suicide following self-harm.

methodsWe 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.

findingsAn 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).

conclusionsOxSATS 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.

Indexed as

Self-Injurious BehaviorSuicideCalibrationClinical Decision RulesDelivery of Health CareHumansAdult psychiatryDepression & mood disordersSubstance misuseSuicide & self-harm

Identifiers

PMID37385664
PMCPMC10335583

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.