Use of Patient-Reported Outcome Measures to Assess the Effectiveness of Hybrid Psychiatric Visits.

OBJECTIVE: Little empirical evidence exists to support the effectiveness of hybrid psychiatric care, defined as care delivered through a combination of telephone, videoconferencing, and in-person visits. The authors aimed to investigate the effectiveness of hybrid psychiatric care compared with outpatient waitlist groups, assessed with patient-reported outcome measures (PROMs). METHOD: Participants were recruited from an adult psychiatry clinic waitlist on which the most common primary diagnoses were unipolar depression, generalized anxiety disorder, and bipolar disorder. Patients (N=148) were randomly assigned to one of two waitlist groups that completed PROMs once or monthly before treatment initiation. PROMs were used to assess symptoms of depression (Patient Health Questionnaire-9 [PHQ-9]), anxiety (Generalized Anxiety Disorder-7 [GAD-7]), and daily psychological functioning (Brief Adjustment Scale-6 [BASE-6]). Patient measures were summarized descriptively with means, medians, and SDs and then compared by using the Kruskal-Wallis test; associated effect sizes were calculated. PROM scores for patients who received hybrid psychiatric treatment during a different period (N=272) were compared with scores of the waitlist groups. RESULTS: PROM assessments of patients who engaged in hybrid care indicated significant improvements in symptom severity compared with the waitlist groups, regardless of the number of PROMs completed while patients were on the waitlist. Between the hybrid care and waitlist groups, the effect size for the PHQ-9 score was moderate (d=0.66); effect sizes were small for the GAD-7 (d=0.46) and BASE-6 (d=0.45) scores. CONCLUSIONS: The findings indicate the clinical effectiveness of hybrid care and that PROMs can be used to assess this effectiveness.

Ultrasound evaluation of portal venous gas and its mimics.

Portal venous gas on abdominal ultrasound classically represents an indirect indicator of bowel ischemia, a critical condition which poses a high patient mortality and therefore warrants emergent corrective action. While the classic appearance of portal venous gas on ultrasound is well-described in the literature, the characteristic descriptors are nonspecific and may actually represent other less emergent mimics. Therefore, while radiologists should remain vigilant for the detection of findings corresponding to portal venous gas, they should also be aware of similar-appearing entities in order to provide the most accurate diagnosis. This pictorial essay will open with imaging examples of true portal venous gas attributable to bowel ischemia and describe the classic features which should alert radiologists to this specific diagnosis. Subsequently, this pictorial essay will provide imaging examples of other various other clinical entities which on ultrasound may share similar imaging characteristics. An important objective of this pictorial essay is to highlight distinguishing imaging features along with specific clinical circumstances for each pathological entity which can direct radiologists into identifying the correct diagnosis.

High- versus low-gradient aortic stenosis: Is our evaluation limited by aorto-mitral angle on cardiovascular CT?

BACKGROUND: Accurate assessment of aortic valve (AV) stenosis (AS) on transthoracic echocardiogram is crucial for appropriate clinical management. However, discordance between aortic valve area (AVA) and Doppler can complicate the diagnosis of severe AS in low-gradient (LG) AS phenotypes. METHODS: We reviewed 220 consecutive patients with suspected severe AS and AVA ≤1.0 cm2 on transthoracic echocardiogram who were evaluated for transcatheter AV replacement (TAVR) within a large health system from 2015 to 2019. We compared AV calcium score and aorto-mitral angle (AMA) on 3-chamber views from ECG-gated cardiovascular CT among patients with high-gradient (HG) AS (N = 19), paradoxical low-flow low-gradient (PLFLG) AS (N = 24) and normal-flow low-gradient (NFLG) AS (N = 14). RESULTS: All groups had comparable age, comorbidities, and AV calcium scores. Compared to patients with HG AS (mean AMA 120 ± 10°), those with PLFLG AS (104 ± 12°; p < 0.001) and NFLG AS (106 ± 13°; p = 0.008) had narrower mean AMA values on cardiovascular CT. CONCLUSION: LG AS patients have significantly narrower AMA than HG AS patients on cardiovascular CT. Due to difficulty obtaining parallel Doppler alignment, narrower AMA may contribute to AVA-Doppler discordance on echocardiogram. These findings emphasize the need for additional information in the setting of LG AS.

Artificial intelligence-guided detection of under-recognized cardiomyopathies on point-of-care cardiac ultrasound.

Background: Point-of-care ultrasonography (POCUS) enables access to cardiac imaging directly at the bedside but is limited by brief acquisition, variation in acquisition quality, and lack of advanced protocols. Objective: To develop and validate deep learning models for detecting underdiagnosed cardiomyopathies on cardiac POCUS, leveraging a novel acquisition quality-adapted modeling strategy. Methods: To develop the models, we identified transthoracic echocardiograms (TTEs) of patients across five hospitals in a large U.S. health system with transthyretin amyloid cardiomyopathy (ATTR-CM, confirmed by Tc99m-pyrophosphate imaging), hypertrophic cardiomyopathy (HCM, confirmed by cardiac magnetic resonance), and controls enriched for the presence of severe AS. In a sample of 290,245 TTE videos, we used novel augmentation approaches and a customized loss function to weigh image and view quality to train a multi-label, view agnostic video-based convolutional neural network (CNN) to discriminate the presence of ATTR-CM, HCM, and/or AS. Models were tested across 3,758 real-world POCUS videos from 1,879 studies in 1,330 independent emergency department (ED) patients from 2011 through 2023. Results: Our multi-label, view-agnostic classifier demonstrated state-of-the-art performance in discriminating ATTR-CM (AUROC 0.98 [95%CI: 0.96-0.99]) and HCM (AUROC 0.95 [95% CI: 0.94-0.96]) on standard TTE studies. Automated metrics of anatomical view correctness confirmed significantly lower quality in POCUS vs TTE videos (median view classifier confidence of 0.63 [IQR: 0.44-0.88] vs 0.93 [IQR: 0.69-1.00], p<0.001). When deployed to POCUS videos, our algorithm effectively discriminated ATTR-CM and HCM with AUROC of up to 0.94 (parasternal long-axis (PLAX)), and 0.85 (apical 4 chamber), corresponding to positive diagnostic odds ratios of 46.7 and 25.5, respectively. In total, 18/35 (51.4%) of ATTR-CM and 32/57 (41.1%) of HCM patients in the POCUS cohort had an AI-positive screen in the year before their eventual confirmatory imaging. Conclusions: We define and validate an AI framework that enables scalable, opportunistic screening of under-diagnosed cardiomyopathies using POCUS.

A Multimodal Video-Based AI Biomarker for Aortic Stenosis Development and Progression.

Importance: Aortic stenosis (AS) is a major public health challenge with a growing therapeutic landscape, but current biomarkers do not inform personalized screening and follow-up. A video-based artificial intelligence (AI) biomarker (Digital AS Severity index [DASSi]) can detect severe AS using single-view long-axis echocardiography without Doppler characterization. Objective: To deploy DASSi to patients with no AS or with mild or moderate AS at baseline to identify AS development and progression. Design, Setting, and Participants: This is a cohort study that examined 2 cohorts of patients without severe AS undergoing echocardiography in the Yale New Haven Health System (YNHHS; 2015-2021) and Cedars-Sinai Medical Center (CSMC; 2018-2019). A novel computational pipeline for the cross-modal translation of DASSi into cardiac magnetic resonance (CMR) imaging was further developed in the UK Biobank. Analyses were performed between August 2023 and February 2024. Exposure: DASSi (range, 0-1) derived from AI applied to echocardiography and CMR videos. Main Outcomes and Measures: Annualized change in peak aortic valve velocity (AV-Vmax) and late (>6 months) aortic valve replacement (AVR). Results: A total of 12 599 participants were included in the echocardiographic study (YNHHS: n = 8798; median [IQR] age, 71 [60-80] years; 4250 [48.3%] women; median [IQR] follow-up, 4.1 [2.4-5.4] years; and CSMC: n = 3801; median [IQR] age, 67 [54-78] years; 1685 [44.3%] women; median [IQR] follow-up, 3.4 [2.8-3.9] years). Higher baseline DASSi was associated with faster progression in AV-Vmax (per 0.1 DASSi increment: YNHHS, 0.033 m/s per year [95% CI, 0.028-0.038] among 5483 participants; CSMC, 0.082 m/s per year [95% CI, 0.053-0.111] among 1292 participants), with values of 0.2 or greater associated with a 4- to 5-fold higher AVR risk than values less than 0.2 (YNHHS: 715 events; adjusted hazard ratio [HR], 4.97 [95% CI, 2.71-5.82]; CSMC: 56 events; adjusted HR, 4.04 [95% CI, 0.92-17.70]), independent of age, sex, race, ethnicity, ejection fraction, and AV-Vmax. This was reproduced across 45 474 participants (median [IQR] age, 65 [59-71] years; 23 559 [51.8%] women; median [IQR] follow-up, 2.5 [1.6-3.9] years) undergoing CMR imaging in the UK Biobank (for participants with DASSi ≥0.2 vs those with DASSi <.02, adjusted HR, 11.38 [95% CI, 2.56-50.57]). Saliency maps and phenome-wide association studies supported associations with cardiac structure and function and traditional cardiovascular risk factors. Conclusions and Relevance: In this cohort study of patients without severe AS undergoing echocardiography or CMR imaging, a new AI-based video biomarker was independently associated with AS development and progression, enabling opportunistic risk stratification across cardiovascular imaging modalities as well as potential application on handheld devices.

Study Protocol for the Artificial Intelligence-Driven Evaluation of Structural Heart Diseases Using Wearable Electrocardiogram (ID-SHD).

Introduction: Portable devices capable of electrocardiogram (ECG) acquisition have the potential to enhance structural heart disease (SHD) management by enabling early detection through artificial intelligence-ECG (AI-ECG) algorithms. However, the performance of these AI algorithms for identifying SHD in a real-world screening setting is unknown. To address this gap, we aim to evaluate the validity of our wearable-adapted AI algorithm, which has been previously developed and validated for detecting SHD from single-lead portable ECGs in patients undergoing routine echocardiograms in the Yale New Haven Hospital (YNHH). Research Methods and Analysis: This is the protocol for a cross-sectional study in the echocardiographic laboratories of YNHH. The study will enroll 585 patients referred for outpatient transthoracic echocardiogram (TTE) as part of their routine clinical care. Patients expressing interest in participating in the study will undergo a screening interview, followed by enrollment upon meeting eligibility criteria and providing informed consent. During their routine visit, patients will undergo a 1-lead ECG with two devices - one with an Apple Watch and the second with another portable 1-lead ECG device. With participant consent, these 1-lead ECG data will be linked to participant demographic and clinical data recorded in the YNHH electronic health records (EHR). The study will assess the performance of the AI-ECG algorithm in identifying SHD, including left ventricular systolic dysfunction (LVSD), valvular disease and severe left ventricular hypertrophy (LVH), by comparing the algorithm's results with data obtained from TTE, which is the established gold standard for diagnosing SHD. Ethics and Dissemination: All patient EHR data required for assessing eligibility and conducting the AI-ECG will be accessed through secure servers approved for protected health information. Data will be maintained on secure, encrypted servers for a minimum of five years after the publication of our findings in a peer-reviewed journal, and any unanticipated adverse events or risks will be reported by the principal investigator to the Yale Institutional Review Board, which has reviewed and approved this protocol (Protocol Number: 2000035532).

Evidence for cytokine dysregulation in schizophrenia spectrum disorders: A comparison of cerebrospinal fluid and blood samples.

Abnormalities in immune function have been described in schizophrenia but few studies have investigated cytokines in cerebrospinal fluid (CSF) and their correlation with blood levels. In this cross-sectional study, cytokines were measured in CSF and plasma of 30 subjects with schizophrenia spectrum disorder (SSD) diagnosis and 23 healthy volunteers (HV). Results showed that CSF TNFα was increased in SSD subjects compared to HV and there were no correlations between CSF and plasma cytokine levels. The present findings provide evidence of dysregulation of TNFα in CSF of schizophrenia. These results identify elevated CSF TNFα levels as a potential biomarker in schizophrenia.

Common and distinct cortical thickness alterations in youth with autism spectrum disorder and attention-deficit/hyperactivity disorder.

BACKGROUND: Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are neurodevelopmental disorders with overlapping behavioral features and genetic etiology. While brain cortical thickness (CTh) alterations have been reported in ASD and ADHD separately, the degree to which ASD and ADHD are associated with common and distinct patterns of CTh changes is unclear. METHODS: We searched PubMed, Web of Science, Embase, and Science Direct from inception to 8 December 2023 and included studies of cortical thickness comparing youth (age less than 18) with ASD or ADHD with typically developing controls (TDC). We conducted a comparative meta-analysis of vertex-based studies to identify common and distinct CTh alterations in ASD and ADHD. RESULTS: Twelve ASD datasets involving 458 individuals with ASD and 10 ADHD datasets involving 383 individuals with ADHD were included in the analysis. Compared to TDC, ASD showed increased CTh in bilateral superior frontal gyrus, left middle temporal gyrus, and right superior parietal lobule (SPL) and decreased CTh in right temporoparietal junction (TPJ). ADHD showed decreased CTh in bilateral precentral gyri, right postcentral gyrus, and right TPJ relative to TDC. Conjunction analysis showed both disorders shared reduced TPJ CTh located in default mode network (DMN). Comparative analyses indicated ASD had greater CTh in right SPL and TPJ located in dorsal attention network and thinner CTh in right TPJ located in ventral attention network than ADHD. CONCLUSIONS: These results suggest shared thinner TPJ located in DMN is an overlapping neurobiological feature of ASD and ADHD. This alteration together with SPL alterations might be related to altered biological motion processing in ASD, while abnormalities in sensorimotor systems may contribute to behavioral control problems in ADHD. The disorder-specific thinner TPJ located in disparate attention networks provides novel insight into distinct symptoms of attentional deficits associated with the two neurodevelopmental disorders. TRIAL REGISTRATION: PROSPERO CRD42022370620. Registered on November 9, 2022.

PRECISION-TBI: a study protocol for a vanguard prospective cohort study to enhance understanding and management of moderate to severe traumatic brain injury in Australia.

INTRODUCTION: Traumatic brain injury (TBI) is a heterogeneous condition in terms of pathophysiology and clinical course. Outcomes from moderate to severe TBI (msTBI) remain poor despite concerted research efforts. The heterogeneity of clinical management represents a barrier to progress in this area. PRECISION-TBI is a prospective, observational, cohort study that will establish a clinical research network across major neurotrauma centres in Australia. This network will enable the ongoing collection of injury and clinical management data from patients with msTBI, to quantify variations in processes of care between sites. It will also pilot high-frequency data collection and analysis techniques, novel clinical interventions, and comparative effectiveness methodology. METHODS AND ANALYSIS: PRECISION-TBI will initially enrol 300 patients with msTBI with Glasgow Coma Scale (GCS) <13 requiring intensive care unit (ICU) admission for invasive neuromonitoring from 10 Australian neurotrauma centres. Demographic data and process of care data (eg, prehospital, emergency and surgical intervention variables) will be collected. Clinical data will include prehospital and emergency department vital signs, and ICU physiological variables in the form of high frequency neuromonitoring data. ICU treatment data will also be collected for specific aspects of msTBI care. Six-month extended Glasgow Outcome Scores (GOSE) will be collected as the key outcome. Statistical analysis will focus on measures of between and within-site variation. Reports documenting performance on selected key quality indicators will be provided to participating sites. ETHICS AND DISSEMINATION: Ethics approval has been obtained from The Alfred Human Research Ethics Committee (Alfred Health, Melbourne, Australia). All eligible participants will be included in the study under a waiver of consent (hospital data collection) and opt-out (6 months follow-up). Brochures explaining the rationale of the study will be provided to all participants and/or an appropriate medical treatment decision-maker, who can act on the patient's behalf if they lack capacity. Study findings will be disseminated by peer-review publications. TRIAL REGISTRATION NUMBER: NCT05855252.

Factors associated with reporting left ventricular ejection fraction with 3D echocardiography in real-world practice.

BACKGROUND: Guidelines recommend 3D echocardiography (3DE) to assess left ventricular ejection fraction (LVEF) on transthoracic echocardiogram (TTE) when possible, but it is unclear which factors are most strongly associated with reporting 3DE LVEF in real-world practice. METHODS: We evaluated 3DE LVEF reporting by age, sex, BMI, TTE location and variation in reporting by sonographer and reader. All TTEs were performed without contrast enhancement agent at a large medical center from 9/2015 to 12/2020 using ultrasound machines capable of 3DE. We used multivariable logistic regression to assess which factors were most associated with reporting 3DE LVEF. RESULTS: Among 35 641 TTEs included in this study, 57.4% were performed on women. 3DE LVEF was reported on 18 391 TTEs (51.6% of cohort; 50.5% for women and 52.4% for men). Portable inpatient TTEs (n = 5569) had the lowest rates of 3DE LVEF reporting (30.9%), while general outpatient TTEs (n = 15 933) had greater reporting (56.9%). Outpatient TTEs with an indication for chemotherapy (n = 3244) had the highest rates of 3DE LVEF (87.2%). The median (IQR) percentage of TTEs reporting 3D LVEF was 52.7% (43.1%-68.1%) among sonographers and 51.6% (46.5%-59.6%) among readers. Among 20082 (56.3%) TTEs with 3DE LVEF measured by sonographers, 91.6% were included by readers in the final report. After adjustment, performing sonographer in the highest reporting quartile was most strongly associated with reporting 3DE LVEF (OR 7.04, 95% CI 6.55-7.56), while an inpatient portable study had the strongest negative association for reporting (OR .38, 95% CI .35-.40). CONCLUSIONS: Use of 3DE LVEF in real-world practice varies substantially based on performing sonographer and is low for hospitalized patients, but can be frequently used for chemotherapy. Initiatives are needed to increase sonographer 3DE acquisition in most clinical settings.

A Multimodality Video-Based AI Biomarker For Aortic Stenosis Development And Progression.

Importance: Aortic stenosis (AS) is a major public health challenge with a growing therapeutic landscape, but current biomarkers do not inform personalized screening and follow-up. Objective: A video-based artificial intelligence (AI) biomarker (Digital AS Severity index [DASSi]) can detect severe AS using single-view long-axis echocardiography without Doppler. Here, we deploy DASSi to patients with no or mild/moderate AS at baseline to identify AS development and progression. Design Setting and Participants: We defined two cohorts of patients without severe AS undergoing echocardiography in the Yale-New Haven Health System (YNHHS) (2015-2021, 4.1[IQR:2.4-5.4] follow-up years) and Cedars-Sinai Medical Center (CSMC) (2018-2019, 3.4[IQR:2.8-3.9] follow-up years). We further developed a novel computational pipeline for the cross-modality translation of DASSi into cardiac magnetic resonance (CMR) imaging in the UK Biobank (2.5[IQR:1.6-3.9] follow-up years). Analyses were performed between August 2023-February 2024. Exposure: DASSi (range: 0-1) derived from AI applied to echocardiography and CMR videos. Main Outcomes and Measures: Annualized change in peak aortic valve velocity (AV-Vmax) and late (>6 months) aortic valve replacement (AVR). Results: A total of 12,599 participants were included in the echocardiographic study (YNHHS: n=8,798, median age of 71 [IQR (interquartile range):60-80] years, 4250 [48.3%] women, and CSMC: n=3,801, 67 [IQR:54-78] years, 1685 [44.3%] women). Higher baseline DASSi was associated with faster progression in AV-Vmax (per 0.1 DASSi increments: YNHHS: +0.033 m/s/year [95%CI:0.028-0.038], n=5,483, and CSMC: +0.082 m/s/year [0.053-0.111], n=1,292), with levels ≥ vs <0.2 linked to a 4-to-5-fold higher AVR risk (715 events in YNHHS; adj.HR 4.97 [95%CI: 2.71-5.82], 56 events in CSMC: 4.04 [0.92-17.7]), independent of age, sex, ethnicity/race, ejection fraction and AV-Vmax. This was reproduced across 45,474 participants (median age 65 [IQR:59-71] years, 23,559 [51.8%] women) undergoing CMR in the UK Biobank (adj.HR 11.4 [95%CI:2.56-50.60] for DASSi ≥vs<0.2). Saliency maps and phenome-wide association studies supported links with traditional cardiovascular risk factors and diastolic dysfunction. Conclusions and Relevance: In this cohort study of patients without severe AS undergoing echocardiography or CMR imaging, a new AI-based video biomarker is independently associated with AS development and progression, enabling opportunistic risk stratification across cardiovascular imaging modalities as well as potential application on handheld devices.

Effect of non-invasive spinal cord stimulation in unmedicated adults with major depressive disorder: a pilot randomized controlled trial and induced current flow pattern.

Converging theoretical frameworks suggest a role and a therapeutic potential for spinal interoceptive pathways in major depressive disorder (MDD). Here, we aimed to evaluate the antidepressant effects and tolerability of transcutaneous spinal direct current stimulation (tsDCS) in MDD. This was a double-blind, randomized, sham-controlled, parallel group, pilot clinical trial in unmedicated adults with moderate MDD. Twenty participants were randomly allocated (1:1 ratio) to receive "active" 2.5 mA or "sham" anodal tsDCS sessions with a thoracic (anode; T10)/right shoulder (cathode) electrode montage 3 times/week for 8 weeks. Change in depression severity (MADRS) scores (prespecified primary outcome) and secondary clinical outcomes were analyzed with ANOVA models. An E-Field model was generated using the active tsDCS parameters. Compared to sham (n = 9), the active tsDCS group (n = 10) showed a greater baseline to endpoint decrease in MADRS score with a large effect size (-14.6 ± 2.5 vs. -21.7 ± 2.3, p = 0.040, d = 0.86). Additionally, compared to sham, active tsDCS induced a greater decrease in MADRS "reported sadness" item (-1.8 ± 0.4 vs. -3.2 ± 0.4, p = 0.012), and a greater cumulative decrease in pre/post tsDCS session diastolic blood pressure change from baseline to endpoint (group difference: 7.9 ± 3.7 mmHg, p = 0.039). Statistical trends in the same direction were observed for MADRS "pessimistic thoughts" item and week-8 CGI-I scores. No group differences were observed in adverse events (AEs) and no serious AEs occurred. The current flow simulation showed electric field at strength within the neuromodulation range (max. ~0.45 V/m) reaching the thoracic spinal gray matter. The results from this pilot study suggest that tsDCS is feasible, well-tolerated, and shows therapeutic potential in MDD. This work also provides the initial framework for the cautious exploration of non-invasive spinal cord neuromodulation in the context of mental health research and therapeutics. The underlying mechanisms warrant further investigation. Clinicaltrials.gov registration: NCT03433339 URL: https://clinicaltrials.gov/ct2/show/NCT03433339 .

Aberrant Neurofunctional Responses During Emotional and Attentional Processing Differentiate ADHD Youth With and Without a Family History of Bipolar I Disorder.

OBJECTIVE: To compare neurofunctional responses in emotional and attentional networks of psychostimulant-free ADHD youth with and without familial risk for bipolar I disorder (BD). METHODS: ADHD youth with (high-risk, HR, n = 48) and without (low-risk, LR, n = 50) a first-degree relative with BD and healthy controls (n = 46) underwent functional magnetic resonance imaging while performing a continuous performance task with emotional distracters. Region-of-interest analyses were performed for bilateral amygdala (AMY), ventrolateral (VLPFC) and dorsolateral (DLPFC) prefrontal cortex, and anterior (ACC) and posterior cingulate cortex (PCC). RESULTS: Compared with HC, HR, but not LR, exhibited predominantly left-lateralized AMY, VLPFC, DLPFC, PCC, and rostral ACC hyperactivation to emotional distractors, whereas LR exhibited right VLPFC and bilateral dorsal ACC hypoactivation to attentional targets. Regional responses correlated with emotional and attention symptoms. CONCLUSION: Aberrant neurofunctional responses during emotional and attentional processing differentiate ADHD youth with and without a family history of BD and correlate with relevant symptoms ratings.

Cortical and subcortical structural differences in psychostimulant-free ADHD youth with and without a family history of bipolar I disorder: a cross-sectional morphometric comparison.

Although attention-deficit/hyperactivity disorder (ADHD) and a family history of bipolar I disorder (BD) are associated with increased risk for developing BD, their neuroanatomical substrates remain poorly understood. This study compared cortical and subcortical gray matter morphology in psychostimulant-free ADHD youth with and without a first-degree relative with BD and typically developing healthy controls. ADHD youth (ages 10-18 years) with ('high-risk', HR) or without ('low-risk', LR) a first-degree relative with BD and healthy comparison youth (HC) were enrolled. High-resolution 3D T1-weighted images were acquired using a Philips 3.0 T MR scanner. The FreeSurfer image analysis suite was used to measure cortical thickness, surface area, and subcortical volumes. A general linear model evaluated group differences in MRI features with age and sex as covariates, and exploratory correlational analyses evaluated associations with symptom ratings. A total of n = 142 youth (mean age: 14.16 ± 2.54 years, 35.9% female) were included in the analysis (HC, n = 48; LR, n = 49; HR, n = 45). The HR group exhibited a more severe symptom profile, including higher mania and dysregulation scores, compared to the LR group. For subcortical volumes, the HR group exhibited smaller bilateral thalamic, hippocampal, and left caudate nucleus volumes compared to both LR and HC, and smaller right caudate nucleus compared with LR. No differences were found between LR and HC groups. For cortical surface area, the HR group exhibited lower parietal and temporal surface area compared with HC and LR, and lower orbitofrontal and superior frontal surface area compared to LR. The HR group exhibited lower left anterior cingulate surface area compared with HC. LR participants exhibited greater right pars opercularis surface area compared with the HC. Some cortical alterations correlated with symptom severity ratings. These findings suggest that ADHD in youth with a BD family history is associated with a more a severe symptom profile and a neuroanatomical phenotype that distinguishes it from ADHD without a BD family history.

Noninferiority Clinical Trial of Adapted START NOW Psychotherapy for Outpatient Opioid Treatment.

Background: Medications for opioid use disorder (MOUD) such as buprenorphine is effective for treating opioid use disorder (OUD). START NOW (SN) is a manualized, skills-based group psychotherapy originally developed and validated for the correctional population and has been shown to result in reduced risk of disciplinary infractions and future psychiatric inpatient days with a dose response effect. We investigate whether adapted START NOW is effective for treating OUD in a MOUD office-based opioid treatment (OBOT) setting in this non-inferiority clinical trial. Methods: Patients enrolled in once weekly buprenorphine/suboxone MOUD OBOT were eligible for enrollment in this study. Participants were cluster-randomized, individually-randomized, or not randomized into either START NOW psychotherapy or treatment-as-usual (TAU) for 32 weeks of therapy. Treatment effectiveness was measured as the number of groups attended, treatment duration, intensity of attendance, and overall drug use as determined by drug screens. Results: 137 participants were quasi-randomized to participate in SN (n = 79) or TAU (n = 58). Participants receiving START NOW psychotherapy, when compared to TAU, had comparable number of groups attended (16.5 vs. 16.7, p = 0.80), treatment duration in weeks (24.1 vs. 23.8, p = 0.62), and intensity defined by number of groups attended divided by the number of weeks to last group (0.71 vs. 0.71, p = 0.90). SN compared to TAU also had similar rates of any positive drug screen result (81.0% vs. 91.4%, p = 0.16). This suggests that adapted START NOW is noninferior to TAU, or the standard of care at our institution, for treating opioid use disorder. Conclusion: Adapted START NOW is an effective psychotherapy for treating OUD when paired with buprenorphine/naloxone in the outpatient group therapy setting. Always free and publicly available, START NOW psychotherapy, along with its clinician manual and training materials, are easily accessible and distributable and may be especially useful for low-resource settings in need of evidence-based psychotherapy.

Brain network structural connectome abnormalities among youth with attention-deficit/hyperactivity disorder at varying risk for bipolar I disorder: a cross-sectional graph-based magnetic resonance imaging study.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is highly prevalent among youth with or at familial risk for bipolar-I disorder (BD-I), and ADHD symptoms commonly precede and may increase the risk for BD-I; however, associated neuropathophysiological mechanisms are not known. In this cross-sectional study, we sought to investigate brain structural network topology among youth with ADHD, with and without familial risk of BD-I. METHODS: We recruited 3 groups of psychostimulant-free youth (aged 10-18 yr), namely youth with ADHD and at least 1 biological parent or sibling with BD-I (high-risk group), youth with ADHD who did not have a first- or second-degree relative with a mood or psychotic disorder (low-risk group) and healthy controls. We used graph-based network analysis of structural magnetic resonance imaging data to investigate topological properties of brain networks. We also evaluated relationships between topological metrics and mood and ADHD symptom ratings. RESULTS: A total of 149 youth were included in the analysis (49 healthy controls, 50 low-risk youth, 50 high-risk youth). Low-risk and high-risk ADHD groups exhibited similar differences from healthy controls, mainly in the default mode network and central executive network. We found topological alterations in the salience network of the high-risk group, relative to both low-risk and control groups. We found significant abnormalities in global network properties in the high-risk group only, compared with healthy controls. Among both low-risk and high-risk ADHD groups, nodal metrics in the right triangular inferior frontal gyrus correlated positively with ADHD total and hyperactivity/impulsivity subscale scores. LIMITATIONS: The cross-sectional design of this study could not determine the relevance of these findings to BD-I risk progression. CONCLUSION: Youth with ADHD, with and without familial risk for BD-I, exhibit common regional abnormalities in the brain connectome compared with healthy youth, whereas alterations in the salience network distinguish these groups and may represent a prodromal feature relevant to BD-I risk.

Severe aortic stenosis detection by deep learning applied to echocardiography.

BACKGROUND AND AIMS: Early diagnosis of aortic stenosis (AS) is critical to prevent morbidity and mortality but requires skilled examination with Doppler imaging. This study reports the development and validation of a novel deep learning model that relies on two-dimensional (2D) parasternal long axis videos from transthoracic echocardiography without Doppler imaging to identify severe AS, suitable for point-of-care ultrasonography. METHODS AND RESULTS: In a training set of 5257 studies (17 570 videos) from 2016 to 2020 [Yale-New Haven Hospital (YNHH), Connecticut], an ensemble of three-dimensional convolutional neural networks was developed to detect severe AS, leveraging self-supervised contrastive pretraining for label-efficient model development. This deep learning model was validated in a temporally distinct set of 2040 consecutive studies from 2021 from YNHH as well as two geographically distinct cohorts of 4226 and 3072 studies, from California and other hospitals in New England, respectively. The deep learning model achieved an area under the receiver operating characteristic curve (AUROC) of 0.978 (95% CI: 0.966, 0.988) for detecting severe AS in the temporally distinct test set, maintaining its diagnostic performance in geographically distinct cohorts [0.952 AUROC (95% CI: 0.941, 0.963) in California and 0.942 AUROC (95% CI: 0.909, 0.966) in New England]. The model was interpretable with saliency maps identifying the aortic valve, mitral annulus, and left atrium as the predictive regions. Among non-severe AS cases, predicted probabilities were associated with worse quantitative metrics of AS suggesting an association with various stages of AS severity. CONCLUSION: This study developed and externally validated an automated approach for severe AS detection using single-view 2D echocardiography, with potential utility for point-of-care screening.

Different brain functional network abnormalities between attention-deficit/hyperactivity disorder youth with and without familial risk for bipolar disorder.

Attention-deficit/hyperactivity disorder (ADHD) commonly precedes the initial onset of mania in youth with familial risk for bipolar disorder (BD). Although ADHD youth with and without BD familial risk exhibit different clinical features, associated neuropathophysiological mechanisms remain poorly understood. This study aimed to identify brain functional network abnormalities associated with ADHD in youth with and without familial risk for BD. Resting-state functional magnetic resonance imaging scans were acquired from 37 ADHD youth with a family history of BD (high-risk), 45 ADHD youth without a family history of BD (low-risk), and 32 healthy controls (HC). Individual whole-brain functional networks were constructed, and graph theory analysis was applied to estimate network topological metrics. Topological metrics, including network efficiency, small-worldness and nodal centrality, were compared across groups, and associations between topological metrics and clinical ratings were evaluated. Compared to HC, low-risk ADHD youth exhibited weaker global integration (i.e., decreased global efficiency and increased characteristic path length), while high-risk ADHD youth showed a disruption of localized network components with decreased frontoparietal and frontolimbic connectivity. Common topological deficits were observed in the medial superior frontal gyrus between low- and high-risk ADHD. Distinct network deficits were found in the inferior parietal lobule and corticostriatal circuitry. Associations between global topological metrics and externalizing symptoms differed significantly between the two ADHD groups. Different patterns of functional network topological abnormalities were found in high- as compared to low-risk ADHD, suggesting that ADHD in youth with BD familial risk may represent a phenotype that is different from ADHD alone.

Two- Versus 8-Zone Lung Ultrasound in Heart Failure: Analysis of a Large Data Set Using a Deep Learning Algorithm.

OBJECTIVE: Scanning protocols for lung ultrasound often include 8 or more lung zones, which may limit real-world clinical use. We sought to compare a 2-zone, anterior-superior thoracic ultrasound protocol for B-line artifact detection with an 8-zone approach in patients with known or suspected heart failure using a deep learning (DL) algorithm. METHODS: Adult patients with suspected heart failure and B-lines on initial lung ultrasound were enrolled in a prospective observational study. Subjects received daily ultrasounds with a hand-held ultrasound system using an 8-zone protocol (right and left anterior/lateral and superior/inferior). A previously published deep learning algorithm that rates severity of B-lines on a 0-4 scale was adapted for use on hand-held ultrasound full video loops. Average severities for 8 and 2 zones were calculated utilizing DL ratings. Bland-Altman plot analyses were used to assess agreement and identify bias between 2- and 8-zone scores for both primary (all patients, 5728 videos, 205 subjects) and subgroup (confirmed diagnosis of heart failure or pulmonary edema, 4464 videos, 147 subjects) analyses. RESULTS: Bland-Altman plot analyses revealed excellent agreement for both primary and subgroup analyses. The absolute difference on the 4-point scale between 8- and 2-zone average scores was not significant for the primary dataset (0.03; 95% CI -0.01 to 0.07) or the subgroup (0.01; 95% CI -0.04 to 0.06). CONCLUSION: Utilization of a 2-zone, anterior-superior thoracic ultrasound protocol provided similar severity information to an 8-zone approach for a dataset of subjects with known or suspected heart failure.