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Identifying risk factors for mortality among patients previously hospitalized for a suicide attempt.

ABSTRACT: Age-adjusted suicide rates in the US have increased over the past two decades across all age groups. The ability to identify risk factors for suicidal behavior is critical to selected and indicated prevention efforts among those at elevated risk of suicide. We used widely available statewide hospitalization data to identify and test the joint predictive power of clinical risk factors associated with death by suicide for patients previously hospitalized for a suicide attempt (N?=?19,057). Twenty-eight clinical factors from the prior suicide attempt were found to be significantly associated with the hazard of subsequent suicide mortality. These risk factors and their two-way interactions were used to build a joint predictive model via stepwise regression, in which the predicted individual survival probability was found to be a valid measure of risk for later suicide death. A high-risk group with a four-fold increase in suicide mortality risk was identified based on the out-of-sample predicted survival probabilities. This study demonstrates that the combination of state-level hospital discharge and mortality data can be used to identify suicide attempters who are at high risk of subsequent suicide death.

SUBMITTER: Doshi RP

PROVIDER: S-EPMC7495431 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Identifying risk factors for mortality among patients previously hospitalized for a suicide attempt.

Doshi Riddhi P RP Chen Kun K Wang Fei F Schwartz Harold H Herzog Alfred A Aseltine Robert H RH

Scientific reports 20200916 1

Age-adjusted suicide rates in the US have increased over the past two decades across all age groups. The ability to identify risk factors for suicidal behavior is critical to selected and indicated prevention efforts among those at elevated risk of suicide. We used widely available statewide hospitalization data to identify and test the joint predictive power of clinical risk factors associated with death by suicide for patients previously hospitalized for a suicide attempt (N = 19,057). Twenty- ...[more]

PMID: 32938955

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Project description:BackgroundMedical training poses significant challenge to medical student wellbeing. With the alarming trend of trainee burnout, mental illness, and suicide, previous studies have reported potential risk factors associated with suicidal behaviours among medical students. The objective of this study is to provide a systematic overview of risk factors for suicidal ideation (SI) and suicide attempt (SA) among medical students and summarize the overall risk associated with each risk factor using a meta-analytic approach.MethodsSystemic search of six electronic databases including MEDLINE, Embase, Education Source, Scopus, PsycInfo, and CINAHL was performed from database inception to March 19, 2021. Studies reporting original quantitative or epidemiological data on risk factors associated with SI and SA among undergraduate medical students were included. When two or more studies reported outcome on the same risk factor, a random-effects inverse variance meta-analysis was performed to estimate the overall effect size.ResultsOf 4,053 articles identified, 25 studies were included. Twenty-two studies reported outcomes on SI risk factors only, and three studies on both SI and SA risk factors. Meta-analysis was performed on 25 SI risk factors and 4 SA risk factors. Poor mental health outcomes including depression (OR 6.87; 95% CI [4.80-9.82] for SI; OR 9.34 [4.18-20.90] for SA), burnout (OR 6.29 [2.05-19.30] for SI), comorbid mental illness (OR 5.08 [2.81-9.18] for SI), and stress (OR 3.72 [1.39-9.94] for SI) presented the strongest risk for SI and SA among medical students. Conversely, smoking cigarette (OR 1.92 [0.94-3.92]), family history of mental illness (OR 1.79 [0.86-3.74]) and suicidal behaviour (OR 1.38 [0.80-2.39]) were not significant risk factors for SI, while stress (OR 3.25 [0.59-17.90]), female (OR 3.20 [0.95-10.81]), and alcohol use (OR 1.41 [0.64-3.09]) were not significant risk factors for SA among medical students.ConclusionsMedical students face a number of personal, environmental, and academic challenges that may put them at risk for SI and SA. Additional research on individual risk factors is needed to construct effective suicide prevention programs in medical school.

Project description:ImportanceBecause more than one-third of people making nonfatal suicide attempts do not receive mental health treatment, it is essential to extend suicide attempt risk factors beyond high-risk clinical populations to the general adult population.ObjectiveTo identify future suicide attempt risk factors in the general population using a data-driven machine learning approach including more than 2500 questions from a large, nationally representative survey of US adults.Design, setting, and participantsData came from wave 1 (2001 to 2002) and wave 2 (2004 to 2005) of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). NESARC is a face-to-face longitudinal survey conducted with a national representative sample of noninstitutionalized civilian population 18 years and older in the US. The cumulative response rate across both waves was 70.2% resulting in 34 653 wave 2 interviews. A balanced random forest was trained using cross-validation to develop a suicide attempt risk model. Out-of-fold model prediction was used to assess model performance, including the area under the receiver operator curve, sensitivity, and specificity. Survey design and nonresponse weights allowed estimates to be representative of the US civilian population based on the 2000 census. Analyses were performed between May 15, 2019, and June 10, 2020.Main outcomes and measuresAttempted suicide in the 3 years between wave 1 and wave 2 interviews.ResultsOf 34 653 participants, 20 089 were female (weighted proportion, 52.1%). The weighted mean (SD) age was 45.1 (17.3) years at wave 1 and 48.2 (17.3) years at wave 2. Attempted suicide during the 3 years between wave 1 and wave 2 interviews was self-reported by 222 of 34 653 participants (0.6%). Using survey questions measured at wave 1, the suicide attempt risk model yielded a cross-validated area under the receiver operator characteristic curve of 0.857 with a sensitivity of 85.3% (95% CI, 79.8-89.7) and a specificity of 73.3% (95% CI, 72.8-73.8) at an optimized threshold. The model identified 1.8% of the US population to be at a 10% or greater risk of suicide attempt. The most important risk factors were 3 questions about previous suicidal ideation or behavior; 3 items from the 12-Item Short Form Health Survey, namely feeling downhearted, doing activities less carefully, or accomplishing less because of emotional problems; younger age; lower educational achievement; and recent financial crisis.Conclusions and relevanceIn this study, after searching through more than 2500 survey questions, several well-known risk factors of suicide attempt were confirmed, such as previous suicidal behaviors and ideation, and new risks were identified, including functional impairment resulting from mental disorders and socioeconomic disadvantage. These results may help guide future clinical assessment and the development of new suicide risk scales.

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Identifying risk factors for mortality among patients previously hospitalized for a suicide attempt.

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Identifying risk factors for mortality among patients previously hospitalized for a suicide attempt.

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