Vasoplegia syndrome is a potentially life-threatening condition that can occur following cardiopulmonary bypass. Heart transplantation is a recognized risk factor for developing this vasodilatory state. The objective of this study was to determine the effects of vasoplegia syndrome on 1-year heart transplant outcomes. A retrospective review of orthotopic heart transplants at a single institution between November 2010 and December 2014 was performed. Of the 347 consecutive adult patients, 107 patients (30.8%) met criteria for vasoplegia syndrome. Preoperative factors and intraoperative variables were collected and compared between vasoplegia and non-vasoplegia cohorts. The incidence of postoperative complications, transplant rejection and patient survival within 1 year were evaluated. Demographics and preoperative medication profiles were similar in both groups, while mechanical circulatory support device use was associated with vasoplegia syndrome (30.8% vs 20.0%; P = 0.039). Perioperative characteristics such as longer cardiopulmonary bypass [165.0 (interquartile range [IQR] 74) min vs 140.0 (IQR 42.7) min; P < 0.001] and increased blood product usage (24.7 ± 17.2 units vs 17.7 ± 14.3 units; P < 0.001) were associated with vasoplegia. Non-vasoplegia patients were more likely to be extubated [42.9 (IQR 37.3) h vs 66.8 (IQR 50.2) h; P < 0.001] and discharged earlier [10.0 (IQR 6) days vs 14.0 (IQR 11.5) days; P < 0.001]. One-year patient survival (92.0% vs 88.6%; P = 0.338) and any-treated rejection rates (82.7% vs 84.3%; P = 0.569) were not significantly different between groups. Although vasoplegia syndrome was associated with an increase in perioperative morbidity, including greater mechanical ventilation time and hospital length of stay, no significant differences in survival or allograft rejection at 1 year was demonstrated.

Most adolescents with depression remain undiagnosed and untreated-missed opportunities that are costly from both personal and public health perspectives. A promising approach to detecting adolescent depression in real-time and at a large scale is through their social communication on the smartphone (e.g., text messages, social media posts). Past research has shown that language from online social communication reliably indicates interindividual differences in depression. To move toward detecting the emergence of depression symptoms intraindividually, the present study tested whether sentiment (i.e., words connoting positive and negative affect) from smartphone social communication prospectively predicted daily mood fluctuations in 83 adolescents (M_age = 16.49, 73.5% female) with a wide range of depression severity. Participants completed daily mood ratings across a 90-day period, during which 354,278 messages were passively collected from social communication apps. Greater positive sentiment (i.e., more positive weighted composite valence score and a greater proportion of words expressing positive sentiment) predicted more positive next-day mood, controlling for previous-day mood. Moreover, greater proportions of positive and negative sentiment were, respectively, associated with lower anhedonia and greater dysphoria symptoms measured at baseline. Exploratory analyses of nonaffective linguistic features showed that greater use of social engagement words (e.g., friends and affiliation) and emojis (primarily consisting of hearts) predicted more positive changes in mood. Collectively, findings suggest that language from smartphone social communication can detect mood fluctuations in adolescents, laying the foundation for language-based tools to identify periods of heightened depression risk. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Evidence suggests that individuals with schizophrenia (SZ) report anticipatory pleasure deficits compared to controls and that these deficits are linked to decreased motivation to engage socially. However, these deficits have been identified via self-report measures of hypothetical pleasant stimuli, leaving it unclear whether they exist in reference to actual social situations. To address this issue, we created a live social interaction that minimized the reliance of higher-order cognitive processes. SZ and control participants were told that they would be playing an "enjoyable sharing game" with another study participant (who was actually a confederate) that involved asking and answering questions (36 interpersonal closeness generation questions; Aron et al., 1997). Participants then reported their current mood and the emotions they anticipated experiencing during the pleasant social interaction. Immediately following the interaction, they reported their experienced emotions. We found that the SZ group anticipated more negative emotion (d = 1.0), but were less accurate in forecasting negative emotion (d = .81), than controls, and these effects were large. There were small, non-significant group differences in anticipation, experience, and accuracy in forecasting of positive emotion (all ds < .29). Also, social anhedonia was positively correlated with anticipated negative affect and negatively associated with experienced positive emotion. At the same time, controls reported finding the interaction to be a more positive emotional experience overall, d = 0.75. This is the first study to show that "anticipatory pleasure deficits" in SZ might actually be heightened anticipated negative emotion and that inaccurate forecasting could be linked to decreased social motivation.

There is a critical need for identifying time-sensitive and cost-effective markers of psychosis risk early in the illness course. One solution may lie in affect dynamics, or the fluctuations of affect across time, which have been demonstrated to predict transitions in psychopathology. Across three studies, the current research is the first to comprehensively investigate affect dynamics in relation to subthreshold positive symptoms (perceptual aberration and magical ideation) and negative symptoms (social anhedonia) of the psychosis spectrum. Across multiple time scales and contexts, we modeled affect dynamics from inexpensive laboratory paradigms and social-media text. Findings provided strong evidence for positive symptoms linked to heightened magnitude and frequency of affective fluctuations in response to emotional materials. Alternatively, negative symptoms showed modest association with heightened persistence of baseline states. These affect-dynamic signatures of psychosis risk provide insight on the distinct developmental pathways to psychosis and could facilitate current risk-detection approaches.