ABSTRACT
Pre-existing mental disorders are linked to COVID-19-related outcomes. However, the findings are inconsistent and a thorough analysis of a broader spectrum of outcomes such as COVID-19 infection severity, morbidity, and mortality is required. We investigated whether the presence of psychiatric diagnoses and/or the use of antidepressants influenced the severity of the outcome of COVID-19. This retrospective cohort study evaluated electronic health records from the INSIGHT Clinical Research Network in 116,498 individuals who were diagnosed with COVID-19 between March 1, 2020, and February 23, 2021. We examined hospitalization, intubation/mechanical ventilation, acute kidney failure, severe sepsis, and death as COVID-19-related outcomes. After using propensity score matching to control for demographics and medical comorbidities, we used contingency tables to assess whether patients with (1) a history of psychiatric disorders were at higher risk of more severe COVID-19-related outcomes and (2) if use of antidepressants decreased the risk of more severe COVID-19 infection. Pre-existing psychiatric disorders were associated with an increased risk for hospitalization, and subsequent outcomes such as acute kidney failure and severe sepsis, including an increased risk of death in patients with schizophrenia spectrum disorders or bipolar disorders. The use of antidepressants was associated with significantly reduced risk of sepsis (p = 0.033), death (p = 0.026). Psychiatric disorder diagnosis prior to a COVID-19-related healthcare encounter increased the risk of more severe COVID-19-related outcomes as well as subsequent health complications. However, there are indications that the use of antidepressants might decrease this risk. This may have significant implications for the treatment and prognosis of patients with COVID-19.
Subject(s)
Acute Kidney Injury , COVID-19 , Mental Disorders , Sepsis , Humans , COVID-19/complications , Retrospective Studies , Mental Disorders/complications , Mental Disorders/drug therapy , Mental Disorders/psychology , Antidepressive Agents/therapeutic use , Sepsis/complications , Sepsis/drug therapyABSTRACT
This editorial summary provides an overview of the 39th annual meeting of the International Society for Traumatic Stress Studies (ISTSS) held from November 1-4, 2023. The meeting, themed "Scalable Strategies to Address the Impact of Trauma Worldwide: Innovations and Implementation," encouraged presenters to focus on the scalability of traumatic stress research and practice. The articles presented at the meeting, which form this issue, cover a broad spectrum of topics, from basic biological mechanisms to innovative digital engagement to population-wide treatments. These articles emphasize eliminating biases in research design and psychiatric practice, promoting health equity, and addressing the unique challenges of traumatic stress. This summary underscores the importance of scalability in developing flexible, dynamic, and inclusive mental health care interventions.
ABSTRACT
Post-traumatic stress disorder (PTSD) is a protracted and debilitating consequence of traumatic events. Identifying early predictors of PTSD can inform the disorder's risk stratification and prevention. We used advanced computational models to evaluate the contribution of early neurocognitive performance measures to the accuracy of predicting chronic PTSD from demographics and early clinical features. We consecutively enrolled adult trauma survivors seen in a general hospital emergency department (ED) to a 14-month long prospective panel study. Extreme Gradient Boosting algorithm evaluated the incremental contribution to 14 months PTSD risk of demographic variables, 1-month clinical variables, and concurrent neurocognitive performance. The main outcome variable was PTSD diagnosis, 14 months after ED admission, obtained by trained clinicians using the Clinician-Administered PTSD Scale (CAPS). N = 138 trauma survivors (mean age = 34.25 ± 11.73, range = 18-64; n = 73 [53%] women) were evaluated 1 month after ED admission and followed for 14 months, at which time n = 33 (24%) met PTSD diagnosis. Demographics and clinical variables yielded a discriminatory accuracy of AUC = 0.68 in classifying PTSD diagnostic status. Adding neurocognitive functioning improved the discriminatory accuracy (AUC = 0.88); the largest contribution emanating from poorer cognitive flexibility, processing speed, motor coordination, controlled and sustained attention, emotional bias, and higher response inhibition, and recall memory. Impaired cognitive functioning 1-month after trauma exposure is a significant and independent risk factor for PTSD. Evaluating cognitive performance could improve early screening and prevention.
Subject(s)
Stress Disorders, Post-Traumatic , Adult , Attention , Child, Preschool , Emotions , Female , Humans , Infant , Male , Mental Recall , Prospective Studies , Stress Disorders, Post-Traumatic/psychologyABSTRACT
Substance use disorders (SUD) are associated with increased risk of worse COVID-19 outcomes. Likewise, racial/ethnic minority patients experience greater risk of severe COVID-19 disease compared to white patients. Providers should understand the role of race and ethnicity as an effect modifier on COVID-19 severity among individuals with SUD. This retrospective cohort study assessed patient race/ethnicity as an effect modifier of the risk of severe COVID-19 disease among patients with histories of SUD and overdose. We used merged electronic health record data from 116,471 adult patients with a COVID-19 encounter between March 2020 and February 2021 across five healthcare systems in New York City. Exposures were patient histories of SUD and overdose. Outcomes were risk of COVID-19 hospitalization and subsequent COVID-19-related ventilation, acute kidney failure, sepsis, and mortality. Risk factors included patient age, sex, and race/ethnicity, as well as medical comorbidities associated with COVID-19 severity. We tested for interaction between SUD and patient race/ethnicity on COVID-19 outcomes. Findings showed that Non-Hispanic Black, Hispanic/Latino, and Asian/Pacific Islander patients experienced a higher prevalence of all adverse COVID-19 outcomes compared to non-Hispanic white patients. Past-year alcohol (OR 1.24 [1.01-1.53]) and opioid use disorders (OR 1.91 [1.46-2.49]), as well as overdose history (OR 4.45 [3.62-5.46]), were predictive of COVID-19 mortality, as well as other adverse COVID-19 outcomes. Among patients with SUD, significant differences in outcome risk were detected between patients of different race/ethnicity groups. Findings indicate that providers should consider multiple dimensions of vulnerability to adequately manage COVID-19 disease among populations with SUDs.
Subject(s)
COVID-19 , Drug Overdose , Substance-Related Disorders , Adult , Humans , Ethnicity , Electronic Health Records , Retrospective Studies , New York City/epidemiology , Race Factors , Minority Groups , Substance-Related Disorders/epidemiologyABSTRACT
BACKGROUND: Visual and auditory signs of patient functioning have long been used for clinical diagnosis, treatment selection, and prognosis. Direct measurement and quantification of these signals can aim to improve the consistency, sensitivity, and scalability of clinical assessment. Currently, we investigate if machine learning-based computer vision (CV), semantic, and acoustic analysis can capture clinical features from free speech responses to a brief interview 1 month post-trauma that accurately classify major depressive disorder (MDD) and posttraumatic stress disorder (PTSD). METHODS: N = 81 patients admitted to an emergency department (ED) of a Level-1 Trauma Unit following a life-threatening traumatic event participated in an open-ended qualitative interview with a para-professional about their experience 1 month following admission. A deep neural network was utilized to extract facial features of emotion and their intensity, movement parameters, speech prosody, and natural language content. These features were utilized as inputs to classify PTSD and MDD cross-sectionally. RESULTS: Both video- and audio-based markers contributed to good discriminatory classification accuracy. The algorithm discriminates PTSD status at 1 month after ED admission with an AUC of 0.90 (weighted average precision = 0.83, recall = 0.84, and f1-score = 0.83) as well as depression status at 1 month after ED admission with an AUC of 0.86 (weighted average precision = 0.83, recall = 0.82, and f1-score = 0.82). CONCLUSIONS: Direct clinical observation during post-trauma free speech using deep learning identifies digital markers that can be utilized to classify MDD and PTSD status.
Subject(s)
Deep Learning , Depressive Disorder, Major , Stress Disorders, Post-Traumatic , Arousal , Depression , Depressive Disorder, Major/diagnosis , Depressive Disorder, Major/psychology , Humans , Stress Disorders, Post-Traumatic/diagnosis , Stress Disorders, Post-Traumatic/psychologyABSTRACT
Active-duty Army personnel can be exposed to traumatic warzone events and are at increased risk for developing post-traumatic stress disorder (PTSD) compared with the general population. PTSD is associated with high individual and societal costs, but identification of predictive markers to determine deployment readiness and risk mitigation strategies is not well understood. This prospective longitudinal naturalistic cohort study-the Fort Campbell Cohort study-examined the value of using a large multidimensional dataset collected from soldiers prior to deployment to Afghanistan for predicting post-deployment PTSD status. The dataset consisted of polygenic, epigenetic, metabolomic, endocrine, inflammatory and routine clinical lab markers, computerized neurocognitive testing, and symptom self-reports. The analysis was computed on active-duty Army personnel (N = 473) of the 101st Airborne at Fort Campbell, Kentucky. Machine-learning models predicted provisional PTSD diagnosis 90-180 days post deployment (random forest: AUC = 0.78, 95% CI = 0.67-0.89, sensitivity = 0.78, specificity = 0.71; SVM: AUC = 0.88, 95% CI = 0.78-0.98, sensitivity = 0.89, specificity = 0.79) and longitudinal PTSD symptom trajectories identified with latent growth mixture modeling (random forest: AUC = 0.85, 95% CI = 0.75-0.96, sensitivity = 0.88, specificity = 0.69; SVM: AUC = 0.87, 95% CI = 0.79-0.96, sensitivity = 0.80, specificity = 0.85). Among the highest-ranked predictive features were pre-deployment sleep quality, anxiety, depression, sustained attention, and cognitive flexibility. Blood-based biomarkers including metabolites, epigenomic, immune, inflammatory, and liver function markers complemented the most important predictors. The clinical prediction of post-deployment symptom trajectories and provisional PTSD diagnosis based on pre-deployment data achieved high discriminatory power. The predictive models may be used to determine deployment readiness and to determine novel pre-deployment interventions to mitigate the risk for deployment-related PTSD.
Subject(s)
Military Personnel , Stress Disorders, Post-Traumatic , Afghanistan , Cohort Studies , Humans , Machine Learning , Prospective Studies , Risk Factors , Sleep QualityABSTRACT
Posttraumatic stress disorder (PTSD) is prevalent and associated with significant morbidity. Mild traumatic brain injury (mTBI) concurrent with psychiatric trauma may be associated with PTSD. Prior studies of PTSD-related structural brain alterations have focused on military populations. The current study examined correlations between PTSD, acute mTBI, and structural brain alterations longitudinally in civilian patients (N = 504) who experienced a recent Criterion A traumatic event. Participants who reported loss of consciousness (LOC) were characterized as having mTBI; all others were included in the control group. PTSD symptoms were assessed at enrollment and over the following year; a subset of participants (n = 89) underwent volumetric brain MRI (M = 53 days posttrauma). Classes of PTSD symptom trajectories were modeled using latent growth mixture modeling. Associations between PTSD symptom trajectories and cortical thicknesses or subcortical volumes were assessed using a moderator-based regression. mTBI with LOC during trauma was positively correlated with the likelihood of developing a chronic PTSD symptom trajectory. mTBI showed significant interactions with cortical thickness in the rostral anterior cingulate cortex (rACC) in predicting PTSD symptoms, r = .461-.463. Bilateral rACC thickness positively predicted PTSD symptoms but only among participants who endorsed LOC, p < .001. The results demonstrate positive correlations between mTBI with LOC and PTSD symptom trajectories, and findings related to mTBI with LOC and rACC thickness interactions in predicting subsequent chronic PTSD symptoms suggest the importance of further understanding the role of mTBI in the context of PTSD to inform intervention and risk stratification.
Subject(s)
Brain Concussion , Military Personnel , Stress Disorders, Post-Traumatic , Brain/diagnostic imaging , Brain Concussion/complications , Brain Concussion/diagnostic imaging , Brain Concussion/psychology , Humans , Military Personnel/psychology , Stress Disorders, Post-Traumatic/complications , Stress Disorders, Post-Traumatic/diagnostic imaging , Stress Disorders, Post-Traumatic/psychology , Unconsciousness/diagnostic imaging , Unconsciousness/etiology , Unconsciousness/psychologyABSTRACT
BACKGROUND: Emergency department (ED) crowding is associated with numerous healthcare issues, but little is known about its effect on psychosocial aspects of patient-provider interactions or interpersonal care. We examined whether ED crowding was associated with perceptions of interpersonal care in patients evaluated for acute coronary syndrome (ACS). METHODS: Patients presenting to a quaternary academic medical centre ED in New York City for evaluation of suspected ACS were enrolled between November 2013 and December 2016. ED crowding was measured using the ED Work Index (EDWIN), which incorporates patient volume, triage category, physician staffing and bed availability. Patients completed the 18-item Interpersonal Processes of Care (IPC) survey, which assesses communication, patient-centred decision-making and interpersonal style. Regression analyses examined associations between EDWIN and IPC scores, adjusting for demographics, comorbidities and depression. RESULTS: Among 933 included patients, 11% experienced ED overcrowding (EDWIN score >2) at admission, 11% experienced ED overcrowding throughout the ED stay and 30% reported suboptimal interpersonal care (defined as per-item IPC score <5). Higher admission EDWIN score was associated with modestly lower IPC score in both unadjusted (ß=-1.70, 95% CI -3.15 to -0.24, p=0.02) and adjusted models (ß = -1.77, 95% CI -3.31 to -0.24, p=0.02). EDWIN score averaged over the entire ED stay was not significantly associated with IPC score (unadjusted ß=-1.30, 95% CI -3.19 to 0.59, p=0.18; adjusted ß=-1.24, 95% CI -3.21 to 0.74, p=0.22). CONCLUSION: Increased crowding at the time of ED admission was associated with poorer perceptions of interpersonal care among patients with suspected ACS.
Subject(s)
Acute Coronary Syndrome , Acute Coronary Syndrome/diagnosis , Acute Coronary Syndrome/psychology , Crowding , Emergency Service, Hospital , Humans , Length of Stay , Surveys and Questionnaires , TriageABSTRACT
Death anxiety is common in advanced cancer due to heightened mortality salience. We tested terror management theory (TMT) in this population (N = 305) by evaluating the buffering effect of the distal defenses (attachment security, meaning, self-esteem) on the impact of physical impairment (a proxy for mortality salience) on death anxiety. Patients with greater numbers of strong distal defenses reported lower death anxiety than those with no strong defenses or one strong defense. These findings support the relevance of TMT in individuals facing the actual threat of death and the need for further TMT research in such populations.
ABSTRACT
Impaired cognitive functioning constitutes an important symptom of major depressive disorder (MDD), potentially associated with elevated cortisol levels. Adverse childhood experiences (ACE) enhance the risk for MDD and can contribute to disturbances in the stress systems, including cortisol and cognitive functions. In healthy participants, cortisol administration as well as acute stress can affect cognitive performance. In the current study, we tested cognitive performance in MDD patients with (N = 32) and without (N = 52) ACE and healthy participants with (N = 22) and without (N = 37) ACE after psychosocial stress induction (Trier Social Stress Test, TSST) and a control condition (Placebo-TSST). MDD predicted lower performance in verbal learning and both selective and sustained attention, while ACE predicted lower performance in psychomotoric speed and working memory. There were no interaction effects of MDD and ACE. After stress, MDD patients were more likely to show lower performance in working memory as well as in selective and sustained attention compared with participants without MDD. Individuals with ACE were more likely to show lower performance in verbal memory after stress compared with individuals without ACE. Our results indicate negative effects of MDD and ACE on distinct cognitive domains. Furthermore, MDD and/or ACE seem to enhance susceptibility for stress-related cognitive impairments.
Subject(s)
Depressive Disorder, Major , Child , Cognition , Humans , Hydrocortisone , Hypothalamo-Hypophyseal System , Pituitary-Adrenal SystemABSTRACT
The influence of stress on executive functions has been demonstrated in numerous studies and is potentially mediated by the stress-induced cortisol release. Yet, the impact of cortisol on cognitive flexibility and task switching in particular remains equivocal. In this study, we investigated the influence of pharmacological glucocorticoid receptor (GR) and mineralocorticoid receptor (MR) stimulation, two corticosteroid receptor types known to be responsible for cortisol effects on the brain. We conducted two experiments, each with 80 healthy participants (40 women and 40 men), and tested the effect of the unspecific MR/GR agonist hydrocortisone (Experiment I) and the more specific MR agonist fludrocortisone (Experiment II) on switch costs and task rule congruency in a bivalent, cued task switching paradigm. The results did not confirm our hypotheses; we found no significant effects of our manipulations on task switching capacity, although general switching and congruency effects were observed. We discuss the absence of MR/GR-mediated effects and propose alternative mechanisms that could explain stress induced effects on task switching.
Subject(s)
Executive Function/drug effects , Fludrocortisone/pharmacology , Hydrocortisone/pharmacology , Receptors, Glucocorticoid/agonists , Receptors, Mineralocorticoid/agonists , Adolescent , Adult , Cues , Diagnostic Techniques, Neurological , Double-Blind Method , Female , Glucocorticoids/pharmacology , Healthy Volunteers , Humans , Hydrocortisone/metabolism , Male , Mineralocorticoids/pharmacology , Placebos , Task Performance and Analysis , Young AdultABSTRACT
Posttraumatic stress responses are characterized by a heterogeneity in clinical appearance and etiology. This heterogeneity impacts the field's ability to characterize, predict, and remediate maladaptive responses to trauma. Machine learning (ML) approaches are increasingly utilized to overcome this foundational problem in characterization, prediction, and treatment selection across branches of medicine that have struggled with similar clinical realities of heterogeneity in etiology and outcome, such as oncology. In this article, we review and evaluate ML approaches and applications utilized in the areas of posttraumatic stress, stress pathology, and resilience research, and present didactic information and examples to aid researchers interested in the relevance of ML to their own research. The examined studies exemplify the high potential of ML approaches to build accurate predictive and diagnostic models of posttraumatic stress and stress pathology risk based on diverse sources of available information. The use of ML approaches to integrate high-dimensional data demonstrates substantial gains in risk prediction even when the sources of data are the same as those used in traditional predictive models. This area of research will greatly benefit from collaboration and data sharing among researchers of posttraumatic stress disorder, stress pathology, and resilience.
Spanish Abstracts by Asociación Chilena de Estrés Traumático (ACET) Aprendizaje de Máquinas para la Predicción del Estrés Postraumático y Resiliencia después del Trauma: Una Visión General de los Conceptos Básicos y Avances Recientes APRENDIZAJE DE MAQUINAS Y ESTRÉS POSTRAUMÁTICO Las respuestas al estrés postraumático se caracterizan por una heterogeneidad en el aspecto clínico y etiología. Esta heterogeneidad afecta la capacidad del campo para caracterizar, predecir y remediar respuestas desadaptativas al trauma. Los enfoques de aprendizaje maquinas (AM) son cada vez más utilizados para superar este problema fundamental en la caracterización, predicción y selección de tratamiento a través de las ramas de la medicina que han luchado con realidades clínicas similares de heterogeneidad en la etiología y resultados, como la oncología. En este artículo, revisamos y evaluamos los enfoques y las aplicaciones de AM utilizados en las áreas de estrés postraumático, patología del estrés, e investigación en resiliencia y presenta información didáctica y ejemplos para ayudar a investigadores interesados ââen la relevancia del AM para su propia investigación. Los estudios examinados ejemplifican el alto potencial de los enfoques de AM para construir modelos predictivos y de diagnóstico precisos de estrés postraumático y riesgo de estrés patológico basados ââen diversas fuentes de Información disponible. El uso de enfoques de AM para integrar datos multidimensionales demuestran ganancias sustanciales en la predicción del riesgo, incluso cuando las fuentes de datos son las mismas que las utilizadas en los modelos predictivos tradicionales. Esta área de investigación se beneficiará enormemente de la colaboración y el intercambio de datos entre los investigadores del trastorno de estrés postraumático, la patología del estrés y resiliencia.
Subject(s)
Machine Learning , Stress Disorders, Post-Traumatic/diagnosis , Humans , Risk Assessment , Risk FactorsABSTRACT
OBJECTIVES: Stress hormones such as cortisol are known to influence a wide range of cognitive functions, including hippocampal based spatial memory. In the brain, cortisol acts via two different receptors: the glucocorticoid (GR) and the mineralocorticoid receptor (MR). As the MR has a high density in the hippocampus, we examined the effects of pharmacological MR stimulation on spatial memory. METHODS: Eighty healthy participants (40 women, 40 men, mean age=23.9years±SD=3.3) completed the virtual Morris Water Maze (vMWM) task to test spatial encoding and spatial memory retrieval after receiving 0.4mg fludrocortisone, a MR agonist, or placebo. RESULTS: There was no effect of MR stimulation on spatial encoding during the vMWM task. However, participants who received fludrocortisone exhibited improved spatial memory retrieval performance. There was neither a main effect of sex nor a sex-by-treatment interaction. CONCLUSION: In young healthy participants, MR stimulation improved hippocampal based spatial memory retrieval in a virtual Morris Water Maze task. Our study not only confirms the importance of MR function in spatial memory, but suggests beneficial effects of acute MR stimulation on spatial memory retrieval in humans.
Subject(s)
Fludrocortisone/pharmacology , Maze Learning/physiology , Mineralocorticoids/pharmacology , Receptors, Mineralocorticoid/agonists , Spatial Memory/physiology , Adolescent , Adult , Female , Fludrocortisone/administration & dosage , Humans , Male , Maze Learning/drug effects , Mineralocorticoids/administration & dosage , Spatial Memory/drug effects , Young AdultABSTRACT
BACKGROUND: Primary adrenal insufficiency (AI) requires hormone replacement therapy with fludrocortisone and hydrocortisone stimulating glucocorticoid (GR) and mineralocorticoid receptors (MR). Evidence from animal and human studies shows that MR function is crucial for cognitive function and mood. Regarding patients with AI, very little is known about the role of MR in cognitive function and mood. METHODS: A repeated-measures within-subject design was used to determine whether cognitive function and mood are related to MR occupation in patients with AI. Intraindividually, patients were examined twice, with 1 week between testing days: once with fludrocortisone (high MR occupation) and once without fludrocortisone (low MR occupation). All patients kept their stable regimen of hydrocortisone. The assessment of cognitive function included executive function, attention, and verbal, visuospatial and working memory. Additionally, mood and blood pressure were measured. RESULTS: Verbal memory improved significantly during high MR occupation (after fludrocortisone intake) compared to low MR occupation [without fludrocortisone, t(29) = -2.1, p = 0.046]. There were trend level differences in the Number-Combination test [t(29) = -1.9, p = 0.074] and in the Stroop interference task [t(29) = -1.9, p = 0.068]. No significant differences in visuospatial and working memory were found. Furthermore, the current mood state was better during high MR occupation compared to low MR occupation [t(29) = -2.4, p = 0.023] as was diastolic blood pressure [F(2, 29) = 3.6, p = 0.07]. CONCLUSIONS: Cognitive function and mood in patients with AI depend in part on MR occupation. Because the medium effect size indicates a potential clinical significance, further studies should systematically examine which dosages of fludrocortisone are associated with optimal cognitive function and mood in AI patients.
Subject(s)
Addison Disease/complications , Anti-Inflammatory Agents/metabolism , Cognition Disorders/etiology , Fludrocortisone/metabolism , Mood Disorders/etiology , Addison Disease/drug therapy , Adult , Aged , Anti-Inflammatory Agents/therapeutic use , Cognition Disorders/drug therapy , Female , Fludrocortisone/therapeutic use , Humans , Male , Middle Aged , Mood Disorders/drug therapy , Neuropsychological Tests , Psychiatric Status Rating ScalesABSTRACT
Firefighters are at increased risk of developing posttraumatic stress disorder (PTSD) due to exposure to potentially traumatic events during their careers. However, little is known about the prevalence of PTSD among this population, particularly when taking moderating variables into account. Using Gaussian Graphical Models and Directed Acyclic Graphs, we conducted network analyses to examine the interactions between clusters of PTSD symptoms, perceived stress, hardiness, and experiential avoidance among 187 firefighters. The data and code are published with the paper. Experiential avoidance, as part of psychological inflexibility, was found to be the only variable that interacted with PTSD symptomatology. Strong positive associations were observed between experiential avoidance and the "negative mood and cognitions" subscale of the PTSD Checklist for DSM-5 (PCL-5). Through this association, other PTSD symptoms were activated, particularly avoidance and arousal. Our findings suggest that experiential avoidance and negative mood and cognition symptoms are particularly important in the expression of PTSD symptomatology in firefighters. In addition, experiential avoidance may be used as a coping strategy to reduce perceived stress during potentially traumatic events. Therefore, experiential avoidance may be a prime target for future interventions and training focused on flexible self-regulation strategies in this population.
Subject(s)
Firefighters , Resilience, Psychological , Stress Disorders, Post-Traumatic , Humans , Stress Disorders, Post-Traumatic/psychology , Adaptation, PsychologicalABSTRACT
Background: Women are more likely to develop post-traumatic stress disorder (PTSD) than men. Recent research suggests an impact of oral contraceptive (OC) intake on PTSD and intrusive memories, a hallmark symptom of PTSD. Although a majority of women use OCs at some point in their lives, the effects on PTSD pathogenesis are only poorly understood.Objective: In the current paper, we aimed to investigate the impact of OC intake on the acquisition and consolidation of intrusive memories in healthy women after watching a trauma film paradigm.Methods: We performed a secondary analysis of a pooled dataset (N = 437) of two previously conducted and published studies investigating the effect of oxytocin on the development of intrusive memories.Results: Women taking OCs showed an attenuated decline of intrusive memories over time after having watched the trauma film compared to naturally cycling women (F(2.75, 1167) = 3.79, p = .03, ηp2 = .01).Conclusion: These findings indicate that the intake of OCs is associated with the development of intrusive memories after a trauma film paradigm. This indication emphasizes the need to further investigate the complex impact of OCs and gonadal hormones on fear learning processes and PTSD.
The objective of the current study was to analyze the effect of oral contraceptives on the development of intrusive memories after a trauma film paradigm by conducting a secondary analysis of previously published data.Women taking oral contraceptives show an attenuated decline of intrusive memories after watching a trauma film paradigm compared to naturally cycling women in the luteal phase.Women using oral contraceptives show higher basal saliva cortisol levels.
Subject(s)
Memory , Stress Disorders, Post-Traumatic , Male , Humans , Female , Contraceptives, Oral/pharmacology , Fear , Motion PicturesABSTRACT
BACKGROUND AND AIMS: Individuals with opioid use disorder (OUD) suffer disproportionately from COVID-19. To inform clinical management of OUD patients, research is needed to identify characteristics associated with COVID-19 progression and death among this population. We aimed to investigate the role of OUD and specific comorbidities on COVID-19 progression among hospitalized OUD patients. DESIGN: Retrospective cohort study of merged electronic health records (EHR) from five large private health systems. SETTING: New York City, New York, USA, 2011-21. PARTICIPANTS: Adults with a COVID-19 encounter and OUD or opioid overdose diagnosis between March 2020 and February 2021. MEASUREMENTS: Primary exposure included diagnosis of OUD/opioid overdose. Risk factors included age, sex, race/ethnicity and common medical, substance use and psychiatric comorbidities known to be associated with COVID-19 severity. Outcomes included COVID-19 hospitalization and subsequent intubation, acute kidney failure, severe sepsis and death. FINDINGS: Of 110 917 COVID-19+ adults, 1.17% were ever diagnosed with OUD/opioid overdose. OUD patients had higher risk of COVID-19 hospitalization [adjusted risk ratio (aRR) = 1.40, 95% confidence interval (CI) = 1.33, 1.47], intubation [adjusted odds ratio (aOR) = 2.05, 95% CI = 1.74, 2.42], kidney failure (aRR = 1.51, 95% CI = 1.34, 1.70), sepsis (aRR = 2.30, 95% CI = 1.88, 2.81) and death (aRR = 2.10, 95% CI = 1.84, 2.40). Among hospitalized OUD patients, risks for worse COVID-19 outcomes included being male; older; of a race/ethnicity other than white, black or Hispanic; and having comorbid chronic kidney disease, diabetes, obesity or cancer. Protective factors included having asthma, hepatitis-C and chronic pain. CONCLUSIONS: Opioid use disorder patients appear to have a substantial risk for COVID-19-associated morbidity and mortality, with particular comorbidities and treatments moderating this risk.
Subject(s)
COVID-19 , Opiate Overdose , Opioid-Related Disorders , Adult , Humans , Male , Female , COVID-19/epidemiology , Retrospective Studies , Opiate Overdose/epidemiology , Opioid-Related Disorders/drug therapy , Hospitals , New York City/epidemiologyABSTRACT
Oxytocin administration during a trauma analogue has been shown to increase intrusive memories, which are a core symptom of post-traumatic stress disorder (PTSD). However, it is unknown whether oxytocin influences the acquisition or the consolidation of the trauma. The current study investigates the effect of the activation of the oxytocin system during the consolidation of an analogue trauma on the formation of intrusive memories over four consecutive days and whether this effect is influenced by individual neurobiological, genetic, or psychological factors. We conducted a randomized double-blind placebo-controlled study in 217 healthy women. They received either a single dose of intranasal oxytocin (24 IU) or placebo after exposure to a trauma film paradigm, which reliably induces intrusive memories. We used a general random forest to examine a potential heterogeneous treatment effect of oxytocin on the consolidation of intrusive memories. Furthermore, we used a poisson regression to examine whether salivary alpha amylase activity (sAA) as a marker of noradrenergic activity and cortisol response to the film, polygenic risk score (PRS) for psychiatric disorders, and psychological factors influence the number of intrusive memories. We found no significant effect of oxytocin on the formation of intrusive memories (F(2, 543.16) = 0.75, p = 0.51, ηp2 = 0.00) and identified no heterogeneous treatment effect. We replicated previous associations of the PRS for PTSD, sAA and the cortisol response on intrusive memories. We further found a positive association between high trait anxiety and intrusive memories, and a negative association between the emotion regulation strategy reappraisal and intrusive memories. Data of the present study suggest that the consolidation of intrusive memories in women is modulated by genetic, neurobiological and psychological factors, but is not influenced by oxytocin. Trial registration: NCT03875391.
Subject(s)
Memory Consolidation , Stress Disorders, Post-Traumatic , Humans , Female , Hydrocortisone , Oxytocin/pharmacology , Placebo Effect , Stress Disorders, Post-Traumatic/drug therapy , Stress Disorders, Post-Traumatic/psychologyABSTRACT
A considerable number of depressed patients do not respond to treatment. Accurate prediction of non-response to routine clinical care may help in treatment planning and improve results. A longitudinal sample of N = 239 depressed patients was assessed at admission to multi-modal day clinic treatment, after six weeks, and at discharge. First, patient's treatment response was modelled by identifying longitudinal trajectories using the Hamilton Depression Rating Scale (HDRS-17). Then, individual items of the HDRS-17 at admission as well as individual patient characteristics were entered as predictors of response/non-response trajectories into the binary classification model (eXtremeGradient Boosting; XGBoost). The model was evaluated on a hold-out set and explained in human-interpretable form by SHapley Additive explanation (SHAP) values. The prediction model yielded a multi-class AUC = 0.80 in the hold-out set. The predictive power for the binary classification yielded an AUC = 0.83 (sensitivity = .80, specificity = .77). Most relevant predictors for non-response were insomnia symptoms, younger age, anxiety symptoms, depressed mood, being unemployed, suicidal ideation and somatic symptoms of depressive disorder. Non-responders to routine treatment for depression can be identified and screened for potential next-generation treatments. Such predictors may help personalize treatment and improve treatment response.
Subject(s)
Sleep Initiation and Maintenance Disorders , Suicidal Ideation , Humans , Machine LearningABSTRACT
Background: The COVID-19 pandemic has resulted in over 6 million deaths worldwide as of March 2022. Adverse psychological effects on patients and the general public linked to the pandemic have been well documented. Methods: We conducted a retrospective analysis of adult emergency department (ED) encounters with diagnoses of anxiety, depression, and suicidal ideation using International Classification of Diseases, Tenth Revision (ICD-10) codes at a tertiary care hospital in New York City from March 15 through July 31, 2020 and compared it with ED encounters during the same time period in the previous 3 years (2017-2019). The relative risk (RR) of these diagnoses was calculated comparing a prepandemic sample to a pandemic sample, accounting for total volume of ED visits. Results: A total of 2816 patient encounters met the inclusion criteria. The study period in 2020 had 31.5% lower overall ED volume seen during the same time period in the previous 3 years (27,874 vs average 40,716 ED encounters). The risk of presenting with anxiety during the study period in 2020 compared to prior 3 years was 1.40 (95% confidence interval [CI] 1.21-1.63), for depression was 1.47 (95% CI 1.28-1.69), and for suicidal ideation was 1.05 (95% CI 0.90-1.23). There was an increase in admissions for depression during the pandemic period (15.2% increase, 95% CI 4.6%-25.7%). Conclusion: There was a relative increase in patients presenting to the ED with complaints of anxiety and depression during the height of the COVID-19 pandemic, while absolute numbers remained stable. Our results highlight the importance of acute care-based mental health resources and interventions to support patients during this pandemic.