PurposeSuicide is a global concern, especially among young people. Suicide prediction models have the potential to make it easier to identify patients who are at a high risk of suicide, but they have very little predictive power when there is a positive value for suicide mortality. Therefore, the aim of the study is to uncover potential risk factors associated with suicide by self-poisoning and further to provide a trustworthy nomogram to predict self-poisoning suicide among poisoned patients.MethodsThis study prospectively enrolled 237 patients who were treated for poisoning at the Fifth Medical Center of PLA General Hospital (Beijing) between May 2021 and May 2022. Patient's basic characteristics, daily activities, mental health status, and history of psychological illnesses were gathered to examine their predictive power for self-poisoning suicide. On developing a prediction model, patients were split 8:2 into a training (n = 196) group and a validation (n = 41) group at random via computer. The training group worked on model development, while the validation group worked on model validation. In this study, the Hosmer and Lemeshow test, accuracy, and area under the curve were the primary evaluation criteria. Shapley Additive exPlanations (SHAP) was determined to evaluate feature importance. To make the prediction model easy for researchers to utilize, it was presented in nomogram format. Two risk groups of patients were identified based on the ideal cut-off value.ResultsOf all poisoned patients, 64.6% committed suicide by self-poisoning. With regard to self-poisoning attempted suicide, multivariate analysis demonstrated that female gender, smoking, generalized anxiety disorder-7 (GAD-7), and beck hopelessness scale-20 (BHS-20) were significant risk factors, whereas married status, relatively higher education level, a sedentary time of 1–3 h per day, higher sport frequency per week, higher monthly income were significant protective features. The nomogram contained each of the aforementioned nine features. In the training group, the area under curve (AUC) of the nomogram was up to 0.938 (0.904–0.972), whereas in the validation group, it reached a maximum of 0.974 (0.937–1.000). Corresponding accuracy rates were up to 0.883 and 0.927, respectively, and the P-values for the Hosmer and Lemeshow test were 0.178 and 0.346, respectively. SHAP demonstrated that the top three most important features were BHS-20, GAD-7, and marital status. Based on the best cut-off value of the nomogram (40%), patients in the high-risk group had a nearly six-time larger likelihood of committing suicide by self-poisoning than patients in the low-risk group (88.68 vs. 15.38%, P < 0.001). The dynamic nomogram was made available at the following address: https://xiaobo.shinyapps.io/Nomogramselfpoisoningsuicide/.ConclusionsThis study proposes a prediction model to stratify patients at a high risk of suicide by self-poisoning and to guide individual preventive strategies. Patients in the high-risk group require further mental health counseling to alleviate anxiety and hopelessness, healthy lifestyle like quitting smoking and exercising more, and restriction of access to poison and psychiatric drugs.

Background The objective of this study was to examine the relationship of mental health status between self-poisoning suicide patients and their family members, and it also sought to identify potential patient’s risk and parental factors for the prediction of suicide attempt, anxiety, and depression. Methods In this study, 151 poisoned patients were prospectively included, and they were matched 1:1 with 151 family members. We gathered information on patient’s and their matched family member’s demographics, lifestyle choices, mental health status, level of intimacy, and history of psychiatry disease. The relationship of patient’s and their family member’s mental health state was investigated using a correlation matrix. Multivariable analyses (multiple logistic regression) were conducted among patients and their matched family members, to identify potential risk factors for self-poisoning suicide, anxiety, and depression. Results Of the total patients, 67.55% (102/151) attempted self-poisoning suicide. Poisoned patients had more severe anxiety and depression symptoms than their matched family members, and this difference was even more pronounced among patients with self-poisoning suicide. Generalized anxiety disorder-7 (GAD-7) score for family members was significantly and favorably correlated with patient’s GAD-7 score after eliminating non-suicide patients and their matched family members. The patient health questionnaire-9 (PHQ-9) score showed a similar pattern, and the family member’s PHQ-9 score was strongly and favorably associated with patient’s PHQ-9 and Beck hopelessness scale-20 (BHS-20) score. Multivariable analysis showed that married marital status (P = 0.038), quitting smoking (P = 0.003), sedentary time of 1 to 6 h (P = 0.013), and participation in a sports more than five times per week (P = 0.046) were all significantly associated with a lower risk of suicide by self-poisoning, while a more serious anxiety state (P = 0.001) was significantly associated with a higher risk of self-poisoning suicide. Multivariable analysis demonstrated that, specifically among self-poisoning suicide patients, married marital status (P = 0.011) and no history of psychiatry disease (P < 0.001) were protective factors for anxiety, while divorced or widowed marital status (P = 0.004), a sedentary time of 1 to 3 h (P = 0.022), and a higher monthly income (P = 0.027) were significant contributors to anxiety. The propensity of additional family-matched characteristics to predict patient’s suicidality, anxiety, and depression was also examined. Conclusions Self-poisoning suicide patients have severe mental health issues. Patients who self-poison have a close connection to their family member’s mental health, particularly their levels of anxiety and depression. According to the findings, being married and adopting healthy lifestyle habits, such as quitting smoking and drinking, increasing their physical activity levels, and managing their idle time, are able to help patients with mental health concerns and even suicidal thoughts.