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Browsing by Author "Roseberry, Kyle"
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Item Assessing Risk of Future Suicidality in Emergency Department Patients(Wiley, 2020-04-02) Brucker, Krista; Duggan, Carter; Niezer, Joseph; Roseberry, Kyle; Le-Niculescu, Helen; Niculescu, Alexander B.; Kline, Jeffrey A.; Emergency Medicine, School of MedicineBackground. Emergency Departments (ED) are the first line of evaluation for patients at risk and in crisis, with or without overt suicidality (ideation, attempts). Currently employed triage and assessments methods miss some of the individuals who subsequently become suicidal. The Convergent Functional Information for Suicidality (CFI-S) 22 item checklist of risk factors, that does not ask directly about suicidal ideation, has demonstrated good predictive ability for suicidality in previous studies in psychiatric outpatients, but has not been tested in the real world-setting of emergency departments (EDs). Methods. We administered CFI-S prospectively to a convenience sample of consecutive ED patients. Median administration time was 3 minutes. Patients were also asked at triage about suicidal thoughts or intentions per standard ED suicide clinical screening (SCS), and the treating ED physician was asked to fill a physician gestalt visual analog scale (VAS) for likelihood of future suicidality spectrum events (SSE) (ideation, preparatory acts, attempts, completed suicide). We performed structured chart review and telephone follow-up at 6 months post index visit. Results. The median time to complete the CFI-S was three minutes (1st to 3rd quartile 3–6 minutes). Of the 338 patients enrolled, 45 (13.3%) were positive on the initial SCS, and 32 (9.5%) experienced a SSE in the 6 months follow-up. Overall, across genders, SCS had a modest diagnostic discrimination for future SSE (ROC AUC 0.63,). The physician VAS was better (AUC 0.76 CI 0.66–0.85), and the CFI-S was slightly higher (AUC 0.81, CI 0.76–0.87). The top CFI-S differentiating items were psychiatric illness, perceived uselessness, and social isolation. The top CFI-S items were family history of suicide, age, and past history of suicidal acts. Conclusions. Using CFI-S, or some of its items, in busy EDs may help improve the detection of patients at high risk for future suicidality.Item Polyphenic risk score shows robust predictive ability for long-term future suicidality(Discover Mental Health, 2022-06-13) Cheng, M; Roseberry, Kyle; Choi, Y; Quast, L; Gaines, Madelynn; Sandusky, George; Kline, JA; Bogdan, Paul; Niculescu, AlexanderSuicides are preventable tragedies, if risk factors are tracked and mitigated. We had previously developed a new quantitative suicidality risk assessment instrument (Convergent Functional Information for Suicidality, CFI-S), which is in essence a simple polyphenic risk score, and deployed it in a busy urban hospital Emergency Department, in a naturalistic cohort of consecutive patients. We report a four years follow-up of that population (n = 482). Overall, the single administration of the CFI-S was significantly predictive of suicidality over the ensuing 4 years (occurrence- ROC AUC 80%, severity- Pearson correlation 0.44, imminence-Cox regression Hazard Ratio 1.33). The best predictive single phenes (phenotypic items) were feeling useless (not needed), a past history of suicidality, and social isolation. We next used machine learning approaches to enhance the predictive ability of CFI-S. We divided the population into a discovery cohort (n = 255) and testing cohort (n = 227), and developed a deep neural network algorithm that showed increased accuracy for predicting risk of future suicidality (increasing the ROC AUC from 80 to 90%), as well as a similarity network classifier for visualizing patient's risk. We propose that the widespread use of CFI-S for screening purposes, with or without machine learning enhancements, can boost suicidality prevention efforts. This study also identified as top risk factors for suicidality addressable social determinants.