Nightmare Distress as a Risk Factor for Suicide Among Adolescents with Major Depressive Disorder.

Purpose: Nightmare is common and is also independently implicated in suicide risk among the adolescent population. Adolescents with major depressive disorder (MDD) are at an increased risk of suicide. Therefore, comorbid nightmares may amplify suicide risk among this clinical population. This study aimed to explore the effects of nightmares on suicide risk among adolescents with MDD. Patients and Methods: Subjects were 499 outpatients aged 12-18 in four large psychiatric hospitals clinic of China, from January 1 to October 31, 2021. Simultaneously, we matched 499 healthy controls according to gender and age. All participants underwent affective state (depressive and anxiety symptoms) and sleep variable (nightmare frequency/distress, insomnia symptoms, and daytime sleepiness) evaluation as well as MDD diagnoses and determination of suicide risk by a fully structured diagnostic clinical interview. Results: Adolescents with MDD reported a higher incidence of frequent nightmares (at least one night per week) and level of nightmare distress than healthy controls (22.0% vs 6.1%; 28.85 ± 11.92 vs 17.30 ± 5.61). Over half of the patients with suicide risk (51.6%) experienced frequent nightmares compared with approximately one-third of those at a risk for suicide (30.7%). Patients with suicide risk scored scientifically higher on sleep variables, depressive and anxiety symptoms than those without the risk. Further logistic regression analysis indicated that female gender, junior grade, recurrent depressive episode, severe nightmare distress and severe depressive symptoms were independently and significantly associated with suicide risk. Conclusion: Our study provided evidence that adolescents with MDD experienced a higher prevalence of frequent nightmares and suffered more nightmare distress. Nightmare distress is an independent risk factor for suicide risk.

Relation Between Unconjugated Bilirubin and Peripheral Biomarkers of Inflammation Derived From Complete Blood Counts in Patients With Acute Stage of Schizophrenia.

Background: Inflammation and oxidative stress are the major leading hypothetical causes of schizophrenia. Unconjugated bilirubin (UCB) is an efficient endogenous plasma antioxidant. Inflammation is closely linked to oxidative stress. The relationship between UCB and inflammatory markers should be paid close attention in schizophrenia acute stage. In this paper, combined UCB and inflammatory markers were evaluated for their capability in predicting schizophrenia in the acute stage to find an easy and effective indicator to identify acute schizophrenia. Methods: A total of 6,937 acute schizophrenia patients and 6,404 healthy controls (HCs) were enrolled. UCB and peripheral biomarkers of inflammation derived from complete blood counts (CBC) were investigated in the subjects with acute schizophrenia, and the results were compared with HCs. Simultaneously, Spearman test was employed to assess the correlation between the variables, while logistic regression was adopted to determine the combined equation and receiver operating characteristic curve was used to evaluate the combined value of UCB and peripheral biomarkers of inflammation derived from CBC to predict schizophrenia in the acute stage. Results: The study indicates that white blood cells, neutrophil, monocyte, mean platelet volume (MPV), red cell distribution width (RDW), neutrophil/lymphocyte ratio (NLR), and monocyte/lymphocyte ratio (MLR) have significantly increased in schizophrenia (p < 0.05 for all), while platelet, lymphocyte, and platelet/lymphocyte ratio (PLR) in schizophrenia have significantly decreased (p < 0.05 for all). UCB exhibits negative correlation with MPV significantly (r = 0.121, p < 0.001), and no correlation with neutrophil and monocyte. The correlations between UCB and other peripheral biomarkers of inflammation derived from CBC are very weak. MPV, RDW, NLR, MLR, PLR, and UCB were taken as independent variables for a logistic regression analysis. The model was as follows: Logit  ( P 1 ) = - 6 . 141 + 0 . 827  MPV + 5 . 613  MLR - 0 . 005  PLR - 0 . 346  UBC . The combination demonstrates better effectiveness in predicting schizophrenia in the acute stage (AUC 0.831, 95% CI 0.825 to 0.837). Conclusion: UCB has a protective effect on acute stage of schizophrenia, which is weak and indirect by affecting the proinflammatory processes. Our findings suggest that a combination of MLR, MPV, PLR, and UBC could be used to predict acute stage of schizophrenia.