Mapping gray and white matter volume abnormalities in early-onset psychosis: an ENIGMA multicenter voxel-based morphometry study.

INTRODUCTION: Regional gray matter (GM) alterations have been reported in early-onset psychosis (EOP, onset before age 18), but previous studies have yielded conflicting results, likely due to small sample sizes and the different brain regions examined. In this study, we conducted a whole brain voxel-based morphometry (VBM) analysis in a large sample of individuals with EOP, using the newly developed ENIGMA-VBM tool. METHODS: 15 independent cohorts from the ENIGMA-EOP working group participated in the study. The overall sample comprised T1-weighted MRI data from 482 individuals with EOP and 469 healthy controls. Each site performed the VBM analysis locally using the standardized ENIGMA-VBM tool. Statistical parametric T-maps were generated from each cohort and meta-analyzed to reveal voxel-wise differences between EOP and healthy controls as well as the individual-based association between GM volume and age of onset, chlorpromazine (CPZ) equivalent dose, and other clinical variables. RESULTS: Compared with healthy controls, individuals with EOP showed widespread lower GM volume encompassing most of the cortex, with the most marked effect in the left median cingulate (Hedges' g = 0.55, p = 0.001 corrected), as well as small clusters of lower white matter (WM), whereas no regional GM or WM volumes were higher in EOP. Lower GM volume in the cerebellum, thalamus and left inferior parietal gyrus was associated with older age of onset. Deficits in GM in the left inferior frontal gyrus, right insula, right precentral gyrus and right superior frontal gyrus were also associated with higher CPZ equivalent doses. CONCLUSION: EOP is associated with widespread reductions in cortical GM volume, while WM is affected to a smaller extent. GM volume alterations are associated with age of onset and CPZ equivalent dose but these effects are small compared to case-control differences. Mapping anatomical abnormalities in EOP may lead to a better understanding of the role of psychosis in brain development during childhood and adolescence.

Identifying engaging bird species and traits with community science observations.

Identifying rates at which birders engage with different species can inform the impact and efficacy of conservation outreach and the scientific use of community-collected biodiversity data. Species that are thought to be "charismatic" are often prioritized in conservation, and previous researchers have used sociological experiments and digital records to estimate charisma indirectly. In this study, we take advantage of community science efforts as another record of human engagement with animals that can reveal observer biases directly, which are in part driven by observer preference. We apply a multistage analysis to ask whether opportunistic birders contributing to iNaturalist engage more with larger, more colorful, and rarer birds relative to a baseline approximated from eBird contributors. We find that body mass, color contrast, and range size all predict overrepresentation in the opportunistic dataset. We also find evidence that, across 472 modeled species, 52 species are significantly overreported and 158 are significantly underreported, indicating a wide variety of species-specific effects. Understanding which birds are highly engaging can aid conservationists in creating impactful outreach materials and engaging new naturalists. The quantified differences between two prominent community science efforts may also be of use for researchers leveraging the data from one or both of them to answer scientific questions of interest.

Mutations of the histone linker H1-4 in neurodevelopmental disorders and functional characterization of neurons expressing C-terminus frameshift mutant H1.4.

Rahman syndrome (RMNS) is a rare genetic disorder characterized by mild to severe intellectual disability, hypotonia, anxiety, autism spectrum disorder, vision problems, bone abnormalities and dysmorphic facies. RMNS is caused by de novo heterozygous mutations in the histone linker gene H1-4; however, mechanisms underlying impaired neurodevelopment in RMNS are not understood. All reported mutations associated with RMNS in H1-4 are small insertions or deletions that create a shared frameshift, resulting in a H1.4 protein that is both truncated and possessing an abnormal C-terminus frameshifted tail (H1.4 CFT). To expand understanding of mutations and phenotypes associated with mutant H1-4, we identified new variants at both the C- and N-terminus of H1.4. The clinical features of mutations identified at the C-terminus are consistent with other reports and strengthen the support of pathogenicity of H1.4 CFT. To understand how H1.4 CFT may disrupt brain function, we exogenously expressed wild-type or H1.4 CFT protein in rat hippocampal neurons and assessed neuronal structure and function. Genome-wide transcriptome analysis revealed ~ 400 genes altered in the presence of H1.4 CFT. Neuronal genes downregulated by H1.4 CFT were enriched for functional categories involved in synaptic communication and neuropeptide signaling. Neurons expressing H1.4 CFT also showed reduced neuronal activity on multielectrode arrays. These data are the first to characterize the transcriptional and functional consequence of H1.4 CFT in neurons. Our data provide insight into causes of neurodevelopmental impairments associated with frameshift mutations in the C-terminus of H1.4 and highlight the need for future studies on the function of histone H1.4 in neurons.

Enhancing Clinical Decision Support in Nephrology: Addressing Algorithmic Bias Through Artificial Intelligence Governance.

There has been a steady rise in the use of clinical decision support (CDS) tools to guide Nephrology, as well as general clinical care. Through guidance set by federal agencies and concerns raised by clinical investigators, there has been an equal rise in understanding whether such tools exhibit algorithmic bias leading to unfairness. This has spurred the more fundamental question of whether sensitive variables such as race should be included in CDS tools. In order to properly answer this question, it is necessary to understand how algorithmic bias arises. We break down three sources of bias encountered when using electronic health record data to develop CDS tools: (1) use of proxy variables, (2) observability concerns and (3) underlying heterogeneity. We discuss how answering the question of whether to include sensitive variables like race often hinges more on qualitative considerations than on quantitative analysis, dependent on the function that the sensitive variable serves. Based on our experience with our own institution's CDS governance group, we show how health system-based governance committees play a central role in guiding these difficult and important considerations. Ultimately, our goal is to foster a community practice of model development and governance teams that emphasizes consciousness about sensitive variables and prioritizes equity.

Designing an Implementable Clinical Prediction Model for Near-Term Mortality and Long-Term Survival in Patients on Maintenance Hemodialysis.

RATIONALE & OBJECTIVE: The life expectancy of patients treated with maintenance hemodialysis (MHD) is heterogeneous. Knowledge of life-expectancy may focus care decisions on near-term versus long-term goals. The current tools are limited and focus on near-term mortality. Here, we develop and assess potential utility for predicting near-term mortality and long-term survival on MHD. STUDY DESIGN: Predictive modeling study. SETTING & PARTICIPANTS: 42,351 patients contributing 997,381 patient months over 11 years, abstracted from the electronic health record (EHR) system of midsize, nonprofit dialysis providers. NEW PREDICTORS & ESTABLISHED PREDICTORS: Demographics, laboratory results, vital signs, and service utilization data available within dialysis EHR. OUTCOME: For each patient month, we ascertained death within the next 6 months (ie, near-term mortality) and survival over more than 5 years during receipt of MHD or after kidney transplantation (ie, long-term survival). ANALYTICAL APPROACH: We used least absolute shrinkage and selection operator logistic regression and gradient-boosting machines to predict each outcome. We compared these to time-to-event models spanning both time horizons. We explored the performance of decision rules at different cut points. RESULTS: All models achieved an area under the receiver operator characteristic curve of≥0.80 and optimal calibration metrics in the test set. The long-term survival models had significantly better performance than the near-term mortality models. The time-to-event models performed similarly to binary models. Applying different cut points spanning from the 1st to 90th percentile of the predictions, a positive predictive value (PPV) of 54% could be achieved for near-term mortality, but with poor sensitivity of 6%. A PPV of 71% could be achieved for long-term survival with a sensitivity of 67%. LIMITATIONS: The retrospective models would need to be prospectively validated before they could be appropriately used as clinical decision aids. CONCLUSIONS: A model built with readily available clinical variables to support easy implementation can predict clinically important life expectancy thresholds and shows promise as a clinical decision support tool for patients on MHD. Predicting long-term survival has better decision rule performance than predicting near-term mortality. PLAIN-LANGUAGE SUMMARY: Clinical prediction models (CPMs) are not widely used for patients undergoing maintenance hemodialysis (MHD). Although a variety of CPMs have been reported in the literature, many of these were not well-designed to be easily implementable. We consider the performance of an implementable CPM for both near-term mortality and long-term survival for patients undergoing MHD. Both near-term and long-term models have similar predictive performance, but the long-term models have greater clinical utility. We further consider how the differential performance of predicting over different time horizons may be used to impact clinical decision making. Although predictive modeling is not regularly used for MHD patients, such tools may help promote individualized care planning and foster shared decision making.

Impaired coronary microvascular reactivity in youth with bipolar disorder.

BACKGROUND: Cardiovascular disease (CVD) is excessively prevalent and premature in bipolar disorder (BD), even after controlling for traditional cardiovascular risk factors. The increased risk of CVD in BD may be subserved by microvascular dysfunction. We examined coronary microvascular function in relation to youth BD. METHODS: Participants were 86 youth, ages 13-20 years (n = 39 BD, n = 47 controls). Coronary microvascular reactivity (CMVR) was assessed using quantitative T2 magnetic resonance imaging during a validated breathing-paradigm. Quantitative T2 maps were acquired at baseline, following 60-s of hyperventilation, and every 10-s thereafter during a 40-s breath-hold. Left ventricular structure and function were evaluated based on 12-15 short- and long-axis cardiac-gated cine images. A linear mixed-effects model that controlled for age, sex, and body mass index assessed for between-group differences in CMVR (time-by-group interaction). RESULTS: The breathing-paradigm induced a significant time-related increase in T2 relaxation time for all participants (i.e. CMVR; ß = 0.36, p < 0.001). CMVR was significantly lower in BD v. controls (ß = -0.11, p = 0.002). Post-hoc analyses found lower T2 relaxation time in BD youth after 20-, 30-, and 40 s of breath-holding (d = 0.48, d = 0.72, d = 0.91, respectively; all pFDR < 0.01). Gross left ventricular structure and function (e.g. mass, ejection fraction) were within normal ranges and did not differ between groups. CONCLUSION: Youth with BD showed evidence of subclinically impaired coronary microvascular function, despite normal gross cardiac structure and function. These results converge with prior findings in adults with major depressive disorder and post-traumatic stress disorder. Future studies integrating larger samples, prospective follow-up, and blood-based biomarkers are warranted.

Neurocognitive correlates of metabolic dysregulation in individuals with mood disorders: a systematic review and meta-analysis.

Individuals with mood disorders are predisposed to metabolic dysfunction, while those with metabolic dysregulation such as diabetes and obesity experience more severe depressive symptoms. Both metabolic dysfunction and mood disorders are independently associated with cognitive deficits. Therefore, given their close association, this study aimed to explore the association between metabolic dysfunction in individuals with mood disorders in relation to cognitive outcomes. A comprehensive search comprised of these three domains was carried out; a random-effects meta-analysis pooling mean cognitive outcomes was conducted (PROSPERO ID: CRD42022295765). Sixty-three studies were included in this review; 26 were synthesized in a quantitative meta-analysis. Comorbid metabolic dysregulation was associated with significantly lower global cognition among individuals with mood disorders. These trends were significant within each mood disorder subgroup, including major depressive disorder, bipolar disorder, and self-report depression/depressive symptoms. Type 2 diabetes was associated with the lowest cognitive performance in individuals with mood disorders, followed by peripheral insulin resistance, body mass index ⩾25 kg/m2, and metabolic syndrome. Significant reduction in scores was also observed among individual cognitive domains (in descending order) of working memory, attention, executive function, processing speed, verbal memory, and visual memory. These findings demonstrate the detrimental effects of comorbid metabolic dysfunction in individuals with mood disorders. Further research is required to understand the underlying mechanisms connecting mood disorders, metabolism, and cognition.

Sleep patterns among preschool offspring of parents with and without psychopathology: Association with the development of psychopathology in childhood.

BACKGROUND: Disturbed sleep during early childhood predicts social-emotional problems. However, it is not known how various early childhood sleep phenotypes are associated with the development of childhood psychopathology, nor whether these relationships vary as a function of parental psychopathology. We identified sleep phenotypes among preschool youth; examined whether these phenotypes were associated with child and parent factors; and determined if early sleep phenotypes predicted later childhood psychopathology. METHODS: Using data from the Pittsburgh Bipolar Offspring study, parents with bipolar disorder (BD), non-BD psychopathology, and healthy controls reported about themselves and their offspring (n = 218) when their children were ages 2-5. Offspring and parents were interviewed directly approximately every 2 years from ages 6-18. Latent class analysis (LCA) identified latent sleep classes; we compared these classes on offspring demographics, parental sleep variables, and parental diagnoses. Kaplan-Meier survival models estimated hazard of developing any new-onset Axis-I disorders, as well as BD specifically, for each class. RESULTS: The optimal LCA solution featured four sleep classes, which we characterized as (1) good sleep, (2) wake after sleep onset problems, (3) bedtime problems (e.g., trouble falling asleep, resists going to bed), and (4) poor sleep generally. Good sleepers tended to have significantly less parental psychopathology than the other three classes. Risk of developing new-onset Axis-I disorders was highest among the poor sleep class and lowest among the good sleep class. CONCLUSIONS: Preschool sleep phenotypes are an important predictor of the development of psychopathology. Future work is needed to understand the biopsychosocial processes underlying these trajectories.

Sex differences in cerebral blood flow among adolescents with bipolar disorder.

BACKGROUND: Abnormalities in cerebral blood flow (CBF) are common in bipolar disorder (BD). Despite known differences in CBF between healthy adolescent males and females, sex differences in CBF among adolescents with BD have never been studied. OBJECTIVE: To examine sex differences in CBF among adolescents with BD versus healthy controls (HC). METHODS: CBF images were acquired using arterial spin labeling (ASL) perfusion magnetic resonance imaging (MRI) in 123 adolescents (72 BD: 30M, 42F; 51 HC: 22M, 29F) matched for age (13-20 years). Whole brain voxel-wise analysis was performed in a general linear model with sex and diagnosis as fixed factors, sex-diagnosis interaction effect, and age as a covariate. We tested for main effects of sex, diagnosis, and their interaction. Results were thresholded at cluster forming p = 0.0125, with posthoc Bonferroni correction (p = 0.05/4 groups). RESULTS: A main effect of diagnosis (BD > HC) was observed in the superior longitudinal fasciculus (SLF), underlying the left precentral gyrus (F =10.24 (3), p < 0.0001). A main effect of sex (F > M) on CBF was detected in the precuneus/posterior cingulate cortex (PCC), left frontal and occipital poles, left thalamus, left SLF, and right inferior longitudinal fasciculus (ILF). No regions demonstrated a significant sex-by-diagnosis interaction. Exploratory pairwise testing in regions with a main effect of sex revealed greater CBF in females with BD versus HC in the precuneus/PCC (F = 7.1 (3), p < 0.01). CONCLUSION: Greater CBF in female adolescents with BD versus HC in the precuneus/PCC may reflect the role of this region in the neurobiological sex differences of adolescent-onset BD. Larger studies targeting underlying mechanisms, such as mitochondrial dysfunction or oxidative stress, are warranted.

Repurposing General Anesthetic Drugs to Treat Depression: A New Frontier for Anesthesiologists in Neuropsychiatric Care.

During the last 100 years, the role of anesthesiologists in psychiatry has focused primarily on facilitating electroconvulsive therapy and mitigating postoperative delirium and other perioperative neurocognitive disorders. The discovery of the rapid and sustained antidepressant properties of ketamine, and early results suggesting that other general anesthetic drugs (including nitrous oxide, propofol, and isoflurane) have antidepressant properties, has positioned anesthesiologists at a new frontier in the treatment of neuropsychiatric disorders. Moreover, shared interest in understanding the biologic underpinnings of anesthetic drugs as psychotropic agents is eroding traditional academic boundaries between anesthesiology and psychiatry. This article presents a brief overview of anesthetic drugs as novel antidepressants and identifies promising future candidates for the treatment of depression. The authors issue a call to action and outline strategies to foster collaborations between anesthesiologists and psychiatrists as they work toward the common goals of repurposing anesthetic drugs as antidepressants and addressing mood disorders in surgical patients.

Impact of preeclampsia on infant and maternal health among women with rheumatic diseases.

OBJECTIVES: We sought to identify the impact of preeclampsia on infant and maternal health among women with rheumatic diseases. METHODS: A retrospective single-center cohort study was conducted to describe pregnancy and infant outcomes among women with systemic lupus erythematosus (SLE) with and without preeclampsia as compared to women with other rheumatic diseases with and without preeclampsia. RESULTS: We identified 263 singleton deliveries born to 226 individual mothers (mean age 31 years, 35% non-Hispanic Black). Overall, 14% of women had preeclampsia; preeclampsia was more common among women with SLE than other rheumatic diseases (27% vs 8%). Women with preeclampsia had a longer hospital stay post-delivery. Infants born to mothers with preeclampsia were delivered an average of 3.3 weeks earlier than those without preeclampsia, were 4 times more likely to be born preterm, and twice as likely to be admitted to the neonatal intensive care unit. The large majority of women with SLE in this cohort were prescribed hydroxychloroquine and aspirin, with no clear association of these medications with preeclampsia. CONCLUSIONS: We found preeclampsia was an important driver of adverse infant and maternal outcomes. While preeclampsia was particularly common among women with SLE in this cohort, the impact of preeclampsia on the infants of all women with rheumatic diseases was similarly severe. In order to improve infant outcomes for women with rheumatic diseases, attention must be paid to preventing, identifying, and managing preeclampsia.

Factors Associated with Transition to Serious Mental Illness.

OBJECTIVE: There is increasing interest in early intervention and detection strategies for youth at-risk of developing a serious mental illness (SMI). Little is known about early factors that may be related to the later development of a SMI; thus, the aim of this study was to determine what clinical factors might relate to the development of in this study psychosis, bipolar disorder and severe or recurrent major depression in at-risk youth. METHOD: The sample consisted of 162 youth aged 12-26 years at different stages of risk. Thirty-one participants developed a SMI during the study. Those who made a transition were compared on a range of baseline clinical and functional measures with those who did not make the transition. A Cox regression model was used to assess the association between measures and later development of a SMI. RESULTS: Female sex, attenuated psychotic symptoms as assessed with the Scale of Psychosis-Risk Symptoms (SOPS) and ratings on the K-10 Distress Scale, were found to be significantly associated with the later transition to mental illness. Females were 2.77 times more likely to transition compared to males. For the SOPS and K-10 scales, there is a 14% increase in the transition rate relative to a one-scale increase in SOPS and a 7% increase in the transition rate relative to a one-point increase in the K-10. CONCLUSIONS: Results from these longitudinal data provide further insight into the specific clinical measures that may be pertinent in early detection of mental illnesses.

Changes in Media Reporting Quality and Suicides Following National Media Engagement on Responsible Reporting of Suicide in Canada: Changements de la Qualité des reportages dans les médias sur les suicides suite à l'engagement des médias nationaux à la déclaration responsable du suicide au Canada.

OBJECTIVE: Responsible media reporting is an accepted strategy for preventing suicide. In 2015, suicide prevention experts launched a media engagement initiative aimed at improving suicide-related reporting in Canada; its impact on media reporting quality and suicide deaths is unknown. METHOD: This pre-post observational study examined changes in reporting characteristics in a random sample of suicide-related articles from major publications in the Greater Toronto Area (GTA) media market. Articles (n = 900) included 450 from the 6-year periods prior to and after the initiative began. We also examined changes in suicide counts in the GTA between these epochs. We used chi-square tests to analyse changes in reporting characteristics and time-series analyses to identify changes in suicide counts. Secondary outcomes focused on guidelines developed by media professionals in Canada and how they may have influenced media reporting quality as well as on the overarching narrative of media articles during the most recent years of available data. RESULTS: Across-the-board improvement was observed in suicide-related reporting with substantial reductions in many elements of putatively harmful content and substantial increases in all aspects of putatively protective content. However, overarching article narratives remained potentially harmful with 55.2% of articles telling the story of someone's death and 20.8% presenting an other negative message. Only 3.6% of articles told a story of survival. After controlling for potential confounders, a nonsignificant numeric decrease in suicide counts was identified after initiative implementation (ω = -5.41, SE = 3.43, t = 1.58, p = 0.12). CONCLUSIONS: We found evidence that a strategy to engage media in Canada changed the content of reporting, but there was only a nonsignificant trend towards fewer suicides. A more fundamental change in media narratives to focus on survival rather than death appears warranted.

Higher Levels of C-reactive Protein Are Associated With Higher Cortical Surface Area and Lower Cortical Thickness in Youth With Bipolar Disorder.

BACKGROUND: Inflammation is implicated in the neuropathology of bipolar disorder (BD). The association of C-reactive protein (CRP) with brain structure has been examined in relation to BD among adults but not youth. METHODS: Participants included 101 youth (BD, n = 55; control group [CG], n = 46; aged 13-20 years). Blood samples were assayed for levels of CRP. T1-weighted brain images were acquired to obtain cortical surface area (SA), volume, and thickness for 3 regions of interest (ROI; whole-brain cortical gray matter, prefrontal cortex, orbitofrontal cortex [OFC]) and for vertex-wise analyses. Analyses included CRP main effects and interaction effects controlling for age, sex, and intracranial volume. RESULTS: In ROI analyses, higher CRP was associated with higher whole-brain SA (ß = 0.16; P = .03) and lower whole-brain (ß = -0.31; P = .03) and OFC cortical thickness (ß = -0.29; P = .04) within the BD group and was associated with higher OFC SA (ß = 0.17; P = .03) within the CG. In vertex-wise analyses, higher CRP was associated with higher SA and lower cortical thickness in frontal and parietal regions within BD. A significant CRP-by-diagnosis interaction was found in frontal and temporal regions, whereby higher CRP was associated with lower neurostructural metrics in the BD group but higher neurostructural metrics in CG. CONCLUSIONS: This study found that higher CRP among youth with BD is associated with higher SA but lower cortical thickness in ROI and vertex-wise analyses. The study identified 2 regions in which the association of CRP with brain structure differs between youth with BD and the CG. Future longitudinal, repeated-measures studies incorporating additional inflammatory markers are warranted.

Resting-state functional connectivity indicators of risk and resilience for self-harm in adolescent bipolar disorder.

BACKGROUND: Suicide is the second leading cause of death in all youth and among adults with bipolar disorder (BD). The risk of suicide in BD is among the highest of all psychiatric conditions. Self-harm, including suicide attempts and non-suicidal self-injury, is a leading risk factor for suicide. Neuroimaging studies suggest reward circuits are implicated in both BD and self-harm; however, studies have yet to examine self-harm related resting-state functional connectivity (rsFC) phenotypes within adolescent BD. METHODS: Resting-state fMRI data were analyzed for 141 adolescents, ages 13-20 years, including 38 with BD and lifetime self-harm (BDSH+), 33 with BD and no self-harm (BDSH-), and 70 healthy controls (HC). The dorsolateral prefrontal cortex (dlPFC), orbitofrontal cortex (OFC) and amygdala were examined as regions of interest in seed-to-voxel analyses. A general linear model was used to explore the bivariate correlations for each seed. RESULTS: BDSH- had increased positive rsFC between the left amygdala and left lateral occipital cortex, and between the right dlPFC and right frontal pole, and increased negative rsFC between the left amygdala and left superior frontal gyrus compared to BDSH+ and HC. BDSH+ had increased positive rsFC of the right OFC with the precuneus and left paracingulate gyrus compared to BDSH- and HC. CONCLUSIONS: This study provides preliminary evidence of altered reward-related rsFC in relation to self-harm in adolescents with BD. Between-group differences conveyed a combination of putative risk and resilience connectivity patterns. Future studies are warranted to evaluate changes in rsFC in response to treatment and related changes in self-harm.

Proof-of-concept randomized controlled trial of single-session nitrous oxide treatment for refractory bipolar depression: Focus on cerebrovascular target engagement.

BACKGROUND: There remain few efficacious treatments for bipolar depression, which dominates the course of bipolar disorder (BD). Despite multiple studies reporting associations between depression and cerebral blood flow (CBF), little is known regarding CBF as a treatment target, or predictor and/or indicator of treatment response, in BD. Nitrous oxide, an anesthetic gas with vasoactive and putative antidepressant properties, has a long history as a neuroimaging probe. We undertook an experimental medicine paradigm, coupling in-scanner single-session nitrous oxide treatment of bipolar depression with repeated measures of CBF. METHODS: In this double-blind randomized controlled trial, 25 adults with BD I/II and current treatment-refractory depression received either: (1) nitrous oxide (20 min at 25% concentration) plus intravenous saline (n = 12), or (2) medical air plus intravenous midazolam (2 mg total; n = 13). Study outcomes included changes in depression severity (Montgomery-Asberg Depression Rating Scale scores, primary) and changes in CBF (via arterial spin labeling magnetic resonance imaging). RESULTS: There were no significant between-group differences in 24-h post-treatment MADRS change or treatment response. However, the nitrous oxide group had significantly greater same-day reductions in depression severity. Lower baseline regional CBF predicted greater 24-h post-treatment MADRS reductions with nitrous oxide but not midazolam. In region-of-interest and voxel-wise analyses, there was a pattern of regional CBF reductions following treatment with midazolam versus nitrous oxide. CONCLUSIONS: Present findings, while tentative and based on secondary endpoints, suggest differential associations of nitrous oxide versus midazolam with bipolar depression severity and cerebral hemodynamics. Larger studies integrating neuroimaging targets and repeated nitrous oxide treatment sessions are warranted.

Early indicators of bipolar risk in preschool offspring of parents with bipolar disorder.

BACKGROUND: Offspring of parents with bipolar disorder (BD-I/II) are at increased risk to develop the disorder. Previous work indicates that bipolar spectrum disorder (BPSD) is often preceded by mood/anxiety symptoms. In school-age offspring of parents with BD, we previously built a risk calculator to predict BPSD onset, which generates person-level risk scores. Here, we test whether preschool symptoms predict school-age BPSD risk. METHODS: We assessed 113 offspring of parents with BD 1-3 times during preschool years (2-5 years old) and then approximately every 2 years for a mean of 10.6 years. We used penalized (lasso) regression with linear mixed models to assess relationships between preschool mood, anxiety, and behavioral symptoms (parent-reported) and school-age predictors of BPSD onset (i.e., risk score, subthreshold manic symptoms, and mood lability), adjusting for demographics and parental symptomatology. Finally, we conducted survival analyses to assess associations between preschool symptoms and school-age onset of BPSD and mood disorder. RESULTS: Of 113 preschool offspring, 33 developed new-onset mood disorder, including 19 with new-onset BPSD. Preschool irritability, sleep problems, and parental factors were lasso-selected predictors of school-age risk scores. After accounting for demographic and parental factors, preschool symptoms were no longer significant. Lasso regressions to predict mood lability and subthreshold manic symptoms yielded similar predictors (irritability, sleep problems, and parental affective lability), but preschool symptoms remained predictive even after adjusting for parental factors (ps < .005). Exploratory analyses indicated that preschool irritability univariately predicted new-onset BPSD (p = .02) and mood disorder (p = .02). CONCLUSIONS: These results provide initial prospective evidence that, as early as preschool, youth who will develop elevated risk scores, mood lability, and subthreshold manic symptoms are already showing symptomatology; these preschool symptoms also predict new-onset BPSD. While replication of findings in larger samples is warranted, results point to the need for earlier assessment of risk and development of early interventions.

Classifying youth with bipolar disorder versus healthy youth using cerebral blood flow patterns.

BACKGROUND: Clinical neuroimaging studies often investigate group differences between patients and controls, yet multivariate imaging features may enable individual-level classification. This study aims to classify youth with bipolar disorder (BD) versus healthy youth using grey matter cerebral blood flow (CBF) data analyzed with logistic regressions. METHODS: Using a 3 Tesla magnetic resonance imaging (MRI) system, we collected pseudo-continuous, arterial spin-labelling, resting-state functional MRI (rfMRI) and T 1-weighted images from youth with BD and healthy controls. We used 3 logistic regression models to classify youth with BD versus controls, controlling for age and sex, using mean grey matter CBF as a single explanatory variable, quantitative CBF features based on principal component analysis (PCA) or relative (intensity-normalized) CBF features based on PCA. We also carried out a comparison analysis using rfMRI data. RESULTS: The study included 46 patients with BD (mean age 17 yr, standard deviation [SD] 1 yr; 25 females) and 49 healthy controls (mean age 16 yr, SD 2 yr; 24 females). Global mean CBF and multivariate quantitative CBF offered similar classification performance that was above chance. The association between CBF images and the feature map was not significantly different between groups (p = 0.13); however, the multivariate classifier identified regions with lower CBF among patients with BD (ΔCBF = -2.94 mL/100 g/min; permutation test p = 0047). Classification performance decreased when considering rfMRI data. LIMITATIONS: We cannot comment on which CBF principal component is most relevant to the classification. Participants may have had various mood states, comorbidities, demographics and medication records. CONCLUSION: Brain CBF features can classify youth with BD versus healthy controls with above-chance accuracy using logistic regression. A global CBF feature may offer similar classification performance to distinct multivariate CBF features.

Utilization and Outcomes of Extracorporeal Membrane Oxygenation Following Traumatic Brain Injury in the United States.

Objectives: Describe contemporary ECMO utilization patterns among patients with traumatic brain injury (TBI) and examine clinical outcomes among TBI patients requiring ECMO. Design: Retrospective cohort study. Setting: Premier Healthcare Database (PHD) between January 2016 to June 2020. Subjects: Adult patients with TBI who were mechanically ventilated and stratified by exposure to ECMO. Results: Among patients exposed to ECMO, we examined the following clinical outcomes: hospital LOS, ICU LOS, duration of mechanical ventilation, and hospital mortality. Of our initial cohort (n = 59,612), 118 patients (0.2%) were placed on ECMO during hospitalization. Most patients were placed on ECMO within the first 2 days of admission (54.3%). Factors associated with ECMO utilization included younger age (OR 0.96, 95% CI (0.95-0.97)), higher injury severity score (ISS) (OR 1.03, 95% CI (1.01-1.04)), vasopressor utilization (2.92, 95% CI (1.90-4.48)), tranexamic acid utilization (OR 1.84, 95% CI (1.12-3.04)), baseline comorbidities (OR 1.06, 95% CI (1.03-1.09)), and care in a teaching hospital (OR 3.04, 95% CI 1.31-7.05). A moderate degree (ICC = 19.5%) of variation in ECMO use was explained at the individual hospital level. Patients exposed to ECMO had longer median (IQR) hospital and ICU length of stay (LOS) [26 days (11-36) versus 9 days (4-8) and 19.5 days (8-32) versus 5 days (2-11), respectively] and a longer median (IQR) duration of mechanical ventilation [18 days (8-31) versus 3 days (2-8)]. Patients exposed to ECMO experienced a hospital mortality rate of 33.9%, compared to 21.2% of TBI patients unexposed to ECMO. Conclusions: ECMO utilization in mechanically ventilated patients with TBI is rare, with significant variation across hospitals. The impact of ECMO on healthcare utilization and hospital mortality following TBI is comparable to non-TBI conditions requiring ECMO. Further research is necessary to better understand the role of ECMO following TBI and identify patients who may benefit from this therapy.

The carbon footprint of household energy use in the United States.

Residential energy use accounts for roughly 20% of greenhouse gas (GHG) emissions in the United States. Using data on 93 million individual households, we estimate these GHGs across the contiguous United States and clarify the respective influence of climate, affluence, energy infrastructure, urban form, and building attributes (age, housing type, heating fuel) in driving these emissions. A ranking by state reveals that GHGs (per unit floor space) are lowest in Western US states and highest in Central states. Wealthier Americans have per capita footprints ∼25% higher than those of lower-income residents, primarily due to larger homes. In especially affluent suburbs, these emissions can be 15 times higher than nearby neighborhoods. If the electrical grid is decarbonized, then the residential housing sector can meet the 28% emission reduction target for 2025 under the Paris Agreement. However, grid decarbonization will be insufficient to meet the 80% emissions reduction target for 2050 due to a growing housing stock and continued use of fossil fuels (natural gas, propane, and fuel oil) in homes. Meeting this target will also require deep energy retrofits and transitioning to distributed low-carbon energy sources, as well as reducing per capita floor space and zoning denser settlement patterns.