Predicting short-term suicide risk: allowing for ongoing variation in severity of intent.
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ABSTRACT: Summary
This article considers the role that assessment of suicidal ideation may have in short-term prediction of suicide. Suicide risk assessment is a multifactorial process and it is assumed that assessment of suicidal ideation is one component. Denial that suicidal ideation has any useful role in risk assessment fails to allow for the marked ongoing short-term variability in severity of intent, which is a common feature of the suicidal state of mind. It is concluded that the assessment of suicidal ideation, provided it is carried out correctly and applied appropriately, should continue to be regarded as a central component of the overall prediction process. A 'two-take' approach to short-term risk assessment and mitigation is proposed that takes variability in severity of intent into account and includes anticipatory treatment planning for any problems that may occur in the near future.
SUBMITTER: Morgan G
PROVIDER: S-EPMC8111990 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ImportanceAlthough psychiatric inpatients are recognized to be at increased risk for suicide immediately after hospital discharge, little is known about the extent to which their short-term suicide risk varies across groups with major psychiatric disorders.ObjectiveTo describe the risk for suicide during the 90 days after hospital discharge for adults with first-listed diagnoses of depressive disorder, bipolar disorder, schizophrenia, substance use disorder, and other mental disorders in relation to inpatients with diagnoses of nonmental disorders and the general population.Design, setting, and participantsThis national retrospective longitudinal cohort included inpatients aged 18 to 64 years in the Medicaid program who were discharged with a first-listed diagnosis of a mental disorder (depressive disorder, bipolar disorder, schizophrenia, substance use disorder, and other mental disorder) and a 10% random sample of inpatients with diagnoses of nonmental disorders. The cohort included 770 643 adults in the mental disorder cohort, 1 090 551 adults in the nonmental disorder cohort, and 370 deaths from suicide from January 1, 2001, to December 31, 2007. Data were analyzed from March 5, 2015, to June 6, 2016.Main outcomes and measuresSuicide rates per 100 000 person-years were determined for each study group during the 90 days after hospital discharge and the demographically matched US general population. Adjusted hazard ratios (ARHs) of short-term suicide after hospital discharge were also estimated by Cox proportional hazards regression models. Information on suicide as a cause of death was obtained from the National Death Index.ResultsIn the overall population of 1 861 194 adults (27% men; 73% women; mean [SD] age, 35.4 [13.1] years), suicide rates for the cohorts with depressive disorder (235.1 per 100 000 person-years), bipolar disorder (216.0 per 100 000 person-years), schizophrenia (168.3 per 100 000 person-years), substance use disorder (116.5 per 100 000 person-years), and other mental disorders (160.4 per 100 000 person-years) were substantially higher than corresponding rates for the cohort with nonmental disorders (11.6 per 100 000 person-years) or the US general population (14.2 per 100 000 person-years). Among the cohort with mental disorders, AHRs of suicide were associated with inpatient diagnosis of depressive disorder (AHR, 2.0; 95% CI, 1.4-2.8; reference cohort, substance use disorder), an outpatient diagnosis of schizophrenia (AHR, 1.6; 95% CI, 1.1-2.2), an outpatient diagnosis of bipolar disorder (AHR, 1.6; 95% CI, 1.2-2.1), and an absence of any outpatient health care in the 6 months preceding hospital admission (AHR, 1.7; 95% CI, 1.2-2.5).Conclusions and relevanceAfter psychiatric hospital discharge, adults with complex psychopathologic disorders with prominent depressive features, especially patients who are not tied into a system of health care, appear to have a particularly high short-term risk for suicide.
| S-EPMC8259698 | biostudies-literature
Project description:Importance:Predicting suicidal behavior continues to be among the most challenging tasks in psychiatry. Objectives:To examine the trajectories of clinical predictors of suicide attempt (specifically, depression symptoms, hopelessness, impulsivity, aggression, impulsive aggression, and irritability) for their ability to predict suicide attempt and to compute a risk score for suicide attempts. Design, Setting, and Participants:This is a longitudinal study of the offspring of parents (or probands) with mood disorders who were recruited from inpatient units at Western Psychiatric Institute and Clinic (Pittsburgh) and New York State Psychiatric Institute. Participants were recruited from July 15, 1997, to September 6, 2005, and were followed up through January 21, 2014. Probands and offspring (n = 663) were interviewed at baseline and at yearly follow-ups for 12 years. Lifetime and current psychiatric disorders were assessed, and self-reported questionnaires were administered. Model evaluation used 10-fold cross-validation, which split the entire data set into 10 equal parts, fit the model to 90% of the data (training set), and assessed it on the remaining 10% (test set) and repeated that process 10 times. Preliminary analyses were performed from July 20, 2015, to October 5, 2016. Additional analyses were conducted from July 26, 2017, to July 24, 2018. Main Outcomes and Measures:The broad definition of suicide attempt included actual, interrupted, and aborted attempts as well as suicidal ideation that prompted emergency referrals during the study. The narrow definition referred to actual attempt only. Results:The sample of offspring (n = 663) was almost equally distributed by sex (316 female [47.7%]) and had a mean (SD) age of 23.8 (8.5) years at the time of censored observations. Among the 663 offspring, 71 (10.7%) had suicide attempts over the course of the study. The trajectory of depression symptoms with the highest mean scores and variability over time was the only trajectory to predict suicide attempt (odds ratio [OR], 4.72; 95% CI, 1.47-15.21; P = .01). In addition, we identified the following predictors: younger age (OR, 0.82; 95% CI, 0.74-0.90; P < .001), lifetime history of unipolar disorder (OR, 4.71; 95% CI, 1.63-13.58; P = .004), lifetime history of bipolar disorder (OR, 3.4; 95% CI, 0.96-12.04; P = .06), history of childhood abuse (OR, 2.98; 95% CI, 1.40-6.38; P = .01), and proband actual attempt (OR, 2.24; 95% CI, 1.06-4.75; P = .04). Endorsing a score of 3 or higher on the risk score tool resulted in high sensitivity (87.3%) and moderate specificity (63%; area under the curve = 0.80). Conclusions and Relevance:The specific predictors of suicide attempt identified are those that clinicians already assess during routine psychiatric evaluations; monitoring and treating depression symptoms to reduce their severity and fluctuation may attenuate the risk for suicidal behavior.
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Project description:In this multi-center cohort study, suicide attempters presenting to hospital (N = 355, 63% women) were interviewed using the Karolinska Interpersonal Violence Scale (KIVS) and followed-up by medical record review. Main outcome was non-fatal or fatal repeat suicide attempt within six months. Also, repeat attempt using a violent method was used as an additional outcome in separate analyses. Data were analyzed for the total group and for men and women separately. Repeat attempts were observed within six months in 78 persons (22%) and 21 (6%) of these used a violent method. KIVS total score of 6 or more was associated with repeat suicide attempt within six months (OR = 1.81, CI 1.08-3.02) and predicted new attempts with a sensitivity of 62% and a specificity of 53%. A three-fold increase in odds ratio was observed for repeat attempt using a violent method (OR = 3.40, CI 1.22-9.49). An association between exposure to violence in adulthood and violent reattempt was seen in women (OR = 1.38, CI 1.06-1.82). The overall conclusions are that information about interpersonal violence may help predict short-term risk for repeat suicide attempt, and that structured assessment of interpersonal violence may be of value in risk assessment after attempted suicide.
| S-EPMC5107950 | biostudies-literature
Project description:BackgroundAir pollution can cause various respiratory and neurological diseases and continuous exposure can lead to death. Previous studies have reported that particulate matter (PM) exposure increases the risk of depression, suicidal thoughts, and suicidal death; however, the results are inconsistent and limited. This study aimed to examine the relationship between short-term PM exposure and suicide deaths, as well as investigate the short-term effects of PM on suicide death within vulnerable groups based on factors such as sex, age group, suicide-related information (note, method, and cause), psychiatric disorders, and physical diseases.MethodsData on a total of 28,670 suicide deaths from 2013 to 2017, provided by the Korea Foundation for Suicide Prevention, were analyzed. The study design employed a time-series analysis with a two-stage approach. In the first step, a generalized additive model combined with a distributed lag nonlinear model was used to estimate the short-term effect of PM exposure on suicide risk specific to each city. In the second step, the estimated results from each city were pooled through a meta-analysis to derive the overall effect. We determined the effects of single lag, cumulative lag, and moving average PM concentrations from days 0-7 before suicide.ResultsWe confirmed an association between exposure to PM10 (≤ 10 μm in diameter) and deaths due to suicide. In particular, among individuals with psychiatric disorders and those who employed non-violent suicide methods, increased exposure to PM10 was associated with a higher risk of death by suicide, with percentage changes of 5.92 (95% confidence interval [CI]: 3.95-7.92) and 11.47 (95% CI: 7.95-15.11), respectively. Furthermore, in the group with psychiatric disorders, there was an observed tendency of increasing suicide risk as PM10 levels increased up to 120 µg/m3, whereas in the group with non-violent suicide deaths, there was a pronounced trend of rapid increase in suicide risk with an increase in PM10 up to 100 µg/m3.ConclusionsThese results show an association between short-term exposure to PM and suicide. Our study adds evidence for the benefits of reducing PM in preventing diseases and improving mental health.
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Project description:Effective methods for predicting COVID-19 disease trajectories are urgently needed. Here, enzyme-linked immunosorbent assay (ELISA) and coronavirus antigen microarray (COVAM) analysis mapped antibody epitopes in the plasma of COVID-19 patients (n = 86) experiencing a wide range of disease states. The experiments identified antibodies to a 21-residue epitope from nucleocapsid (termed Ep9) associated with severe disease, including admission to the intensive care unit (ICU), requirement for ventilators, or death. Importantly, anti-Ep9 antibodies can be detected within 6 days post-symptom onset and sometimes within 1 day. Furthermore, anti-Ep9 antibodies correlate with various comorbidities and hallmarks of immune hyperactivity. We introduce a simple-to-calculate, disease risk factor score to quantitate each patient’s comorbidities and age. For patients with anti-Ep9 antibodies, scores above 3.0 predict more severe disease outcomes with a 13.42 likelihood ratio (96.7% specificity). The results lay the groundwork for a new type of COVID-19 prognostic to allow early identification and triage of high-risk patients. Such information could guide more effective therapeutic intervention.
2021-04-21 | GSE172471 | GEO
Project description:IntroductionFew, if any, prior studies have considered whether undetermined intent (UDI) deaths and suicide deaths differ with respect to genetic liability for suicidal behavior or psychopathology.MethodsThe authors used Swedish national registry data to identify suicide deaths (N = 31,835) and UDI deaths (N = 10,623); sociodemographic covariates; and registrations for psychopathology. Family genetic risk scores (FGRS) were derived for each form of psychopathology. The authors used LASSO models to assess genetic and phenotypic differences across outcomes.ResultsIn the multivariate LASSO regressions, higher FGRS for major depression, bipolar disorder, and suicide death were associated with lower odds of UDI relative to unambiguous suicide (OR = 0.91-0.95), while those for alcohol and drug use disorders, ADHD, and criminal behavior were associated with higher odds of UDI relative to unambiguous suicide (OR = 1.04-1.12). When the corresponding phenotypic registration status for these outcomes was included in a subsequent model, the associations were attenuated and of small magnitude, but many remained different from OR = 1.ConclusionsAggregate genetic differences between unambiguous suicide decedents and UDI deaths are small, particularly when accounting for psychiatric comorbidity, but in some cases, statistically significant. These findings suggest that different analytic treatment of UDI deaths may be warranted depending on the research question. Replication in other samples, and using molecular genetic data, is necessary.
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Project description:ObjectiveThe aim of this study was to establish a nomogram model for predicting the risk of short-term recurrence in glioma patients.MethodsThe clinical data of recurrent glioma patients were summarized and analyzed in this study. Univariate and multivariate logistic regression analyses were performed to analyze the correlation between clinical data and the risk of short-term recurrence after operation. A nomogram was established based on the multivariate logistic regression model results.ResultsA total of 175 patients with recurrent glioma were enrolled, with 53 patients in the short-term recurrence (STR) group (recurrent time ≤6 months) and 122 patients in the long-term recurrence (LTR) group (recurrent time ≥36 months). Univariate analysis revealed that age at diagnosis, Karnofsky performance scores (KPSs), tumor location, glioma grade, glioma type, extent of resection (EOR), adjuvant chemotherapy (ad-CT), concurrent chemotherapy (co-CT), and isocitrate dehydrogenase (IDH) status were significantly associated with the short-term glioma recurrence. Multivariate analyses revealed that age at diagnosis, KPS, glioma grade, EOR, and IDH were independent risk factors for short-term glioma recurrence. A risk nomogram for the short-term recurrence of glioma was established, with the concordance index (C-index) of 0.971. The findings of calibration and receiver operating characteristic (ROC) curves showed that our nomogram model had good performance and discrimination to estimate short-term recurrence probability.ConclusionThis nomogram model provides reliable information about the risk of short-term glioma recurrence for oncologists and neurosurgeons. This model can predict the short-term recurrence probability and give assistance to decide the interval of follow-up or formulate individualized treatment strategies based on the predicted results. A free online prediction risk tool for this nomogram is provided: https://rj2021.shinyapps.io/Nomogram_ recurrence-risk/.
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Project description:IntroductionTo establish a prognostic model for predicting 14-day mortality in ICU patients with severe sepsis overall and according to place of infection acquisition and to sepsis episode number.MethodsIn this prospective multicentre observational study on a multicentre database (OUTCOMEREA) including data from 12 ICUs, 2268 patients with 2737 episodes of severe sepsis were randomly divided into a training cohort (n = 1458) and a validation cohort (n = 810). Up to four consecutive severe sepsis episodes per patient occurring within the first 28 ICU days were included. We developed a prognostic model for predicting death within 14 days after each episode, based on patient data available at sepsis onset.ResultsIndependent predictors of death were logistic organ dysfunction (odds ratio (OR), 1.22 per point, P < 10-4), septic shock (OR, 1.40; P = 0.01), rank of severe sepsis episode (1 reference, 2: OR, 1.26; P = 0.10 >or= 3: OR, 2.64; P < 10-3), multiple sources of infection (OR; 1.45, P = 0.03), simplified acute physiology score II (OR, 1.02 per point; P < 10-4), McCabe score ([greater than or equal to]2) (OR, 1.96; P < 10-4), and number of chronic co-morbidities (1: OR, 1.75; P < 10-3, >or= 2: OR, 2.24, P < 10-3). Validity of the model was good in whole cohorts (AUC-ROC, 0.76; 95%CI, 0.74 to 0.79; and HL Chi-square: 15.3 (P = 0.06) for all episodes pooled).ConclusionsIn ICU patients, a prognostic model based on a few easily obtained variables is effective in predicting death within 14 days after the first to fourth episode of severe sepsis complicating community-, hospital-, or ICU-acquired infection.
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