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OBJECTIVE: Selective serotonin reuptake inhibitor (SSRI) use is common in pregnancy. It is associated with delayed neonatal adaptation. Most previous studies have not adjusted for the severity of maternal mental health disorders or examined the impact of SSRI type and dosage. We examined whether treatment with SSRIs in late pregnancy (after 20 weeks) is associated with delayed neonatal adaptation independent of maternal depression and anxiety. DESIGN, SETTING AND PATIENTS: Retrospective population-based birth cohort of 280 090 term infants born at 15 Kaiser Permanente Northern California hospitals, 2011-2019. Individual-level pharmacy, maternal, pregnancy and neonatal data were obtained from electronic medical records. EXPOSURE: Dispensed maternal SSRI prescription after 20 weeks of pregnancy. MAIN OUTCOME MEASURES: Delayed neonatal adaptation defined as a 5 min Apgar score ≤5, resuscitation at birth or admission to a neonatal intensive care unit for respiratory support. Secondary outcomes included each individual component of the primary outcome and more severe neonatal outcomes (pulmonary hypertension, hypoxic-ischaemic encephalopathy and seizures). RESULTS: 7573 (2.7%) infants were exposed to SSRIs in late pregnancy. Delayed neonatal adaptation occurred in 11.2% of exposed vs 4.4% of unexposed infants (relative risk 2.52 (95% CI 2.36 to 2.70)). After multivariable adjustment, there was an association between SSRI exposure and delayed neonatal adaptation (adjusted OR 2.14 (95% CI 1.96 to 2.32)). This association was dose dependent. Escitalopram and fluoxetine were associated with the highest risk of delayed neonatal adaptation. CONCLUSIONS: Infants exposed to SSRIs have increased risks of delayed adaptation in a type and dose-dependent relationship, pointing toward a causal relationship.

ImportanceEpidural analgesia is used by approximately 70% of birthing persons in the US to alleviate labor pain and is a common cause of elevated temperature in the birthing parent during labor, which, in turn, is associated with adverse neonatal outcomes such as hypoxic-ischemic encephalopathy (HIE).ObjectiveTo determine whether epidural analgesia is associated with increased risk of HIE after adjusting for the birthing person's maximal temperature before epidural placement and for the propensity to get an epidural.Design, setting, and participantsThis retrospective, population-based cohort study was conducted at 15 Kaiser Permanente Northern California hospitals. Participants included singleton neonates born at 35 weeks' or later gestational age between 2012 and 2019. Elective cesarean deliveries and deliveries within 2 hours of hospital admission were excluded. Data analysis was performed from November 2022 to June 2024.ExposureThe primary exposure was epidural analgesia during labor.Main outcomes and measuresThe primary outcome was HIE, defined as the presence of both neonatal acidosis (ie, pH

Interest in incorporating historical data in the clinical trial has increased with the rising cost of conducting clinical trials. The intervention arm for the current trial often requires prospective data to assess a novel treatment, and thus borrowing historical control data commensurate in distribution to current control data is motivated in order to increase the allocation ratio to the current intervention arm. Existing historical control borrowing adaptive designs adjust allocation ratios based on the commensurability assessed through study-level summary statistics of the response agnostic of the distributions of the trial subject characteristics in the current and historical trials. This can lead to distributional imbalance of the current trial subject characteristics across the treatment arms as well as between current control data and borrowed historical control data. Such covariate imbalance may threaten the internal validity of the current trial by introducing confounding factors that affect study endpoints. In this article, we propose a Bayesian design which borrows and updates the treatment allocation ratios both covariate-adaptively and commensurate to covariate dependently assessed similarity between the current and historical control data. We employ covariate-dependent discrepancy parameters which are allowed to grow with the sample size and propose a regularized local regression procedure for the estimation of the parameters. The proposed design also permits the current and the historical controls to be similar to varying degree, depending on the subject level characteristics. We evaluate the proposed design extensively under the settings derived from two placebo-controlled randomized trials on vertebral fracture risk in post-menopausal women.

OBJECTIVE: We investigated how diagnosis and injury location on neonatal brain MRI following onset of acute provoked seizures was associated with short term outcome. STUDY DESIGN: A multicenter cohort of neonates with acute provoked seizures enrolled in the Neonatal Seizure Registry. MRIs were centrally evaluated by a neuroradiologist for location of injury and radiologic diagnosis. Clinical outcomes were determined by chart review. Multivariate logistic regression was used to examine the association between MRI findings and outcomes. RESULTS: Among 236 newborns with MRI at median age 4 days (IQR 3-8), 91% had abnormal MRI. Radiologic diagnoses of intracranial hemorrhage (OR 3.2 [1.6-6.5], p

Background Multiple qualitative scoring systems have been created to capture the imaging severity of hypoxic ischemic brain injury. Purpose To evaluate quantitative volumes of acute brain injury at MRI in neonates with hypoxic ischemic brain injury and correlate these findings with 24-month neurodevelopmental outcomes and qualitative brain injury scoring by radiologists. Materials and Methods In this secondary analysis, brain diffusion-weighted MRI data from neonates in the High-dose Erythropoietin for Asphyxia and Encephalopathy trial, which recruited participants between January 2017 and October 2019, were analyzed. Volume of acute brain injury, defined as brain with apparent diffusion coefficient (ADC) less than 800 × 10-6 mm2/sec, was automatically computed across the whole brain and within the thalami and white matter. Outcomes of death and neurodevelopmental impairment (NDI) were recorded at 24-month follow-up. Associations between the presence and volume (in milliliters) of acute brain injury with 24-month outcomes were evaluated using multiple logistic regression. The correlation between quantitative acute brain injury volume and qualitative MRI scores was assessed using the Kendall tau-b test. Results A total of 416 neonates had available MRI data (mean gestational age, 39.1 weeks ± 1.4 [SD]; 235 male) and 113 (27%) showed evidence of acute brain injury at MRI. Of the 387 participants with 24-month follow-up data, 185 (48%) died or had any NDI. Volume of acute injury greater than 1 mL (odds ratio [OR], 13.9 [95% CI: 5.93, 32.45]; P < .001) and presence of any acute injury in the brain (OR, 4.5 [95% CI: 2.6, 7.8]; P < .001) were associated with increased odds of death or any NDI. Quantitative whole-brain acute injury volume was strongly associated with radiologists qualitative scoring of diffusion-weighted images (Kendall tau-b = 0.56; P < .001). Conclusion Automated quantitative volume of brain injury is associated with death, moderate to severe NDI, and cerebral palsy in neonates with hypoxic ischemic encephalopathy and correlated well with qualitative MRI scoring of acute brain injury. Clinical trial registration no. NCT02811263 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Huisman in this issue.

The logopenic variant of primary progressive aphasia (lvPPA) is a neurodegenerative syndrome characterized linguistically by gradual loss of repetition and naming skills resulting from left posterior temporal and inferior parietal atrophy. Here, we sought to identify which specific cortical loci are initially targeted by the disease (epicenters) and investigate whether atrophy spreads through predetermined networks. First, we used cross-sectional structural MRI data from individuals with lvPPA to define putative disease epicenters using a surface-based approach paired with an anatomically fine-grained parcellation of the cortical surface (i.e., HCP-MMP1.0 atlas). Second, we combined cross-sectional functional MRI data from healthy controls and longitudinal structural MRI data from individuals with lvPPA to derive the epicenter-seeded resting-state networks most relevant to lvPPA symptomatology and ascertain whether functional connectivity in these networks predicts longitudinal atrophy spread in lvPPA. Our results show that two partially distinct brain networks anchored to the left anterior angular and posterior superior temporal gyri epicenters were preferentially associated with sentence repetition and naming skills in lvPPA. Critically, the strength of connectivity within these two networks in the neurologically-intact brain significantly predicted longitudinal atrophy progression in lvPPA. Taken together, our findings indicate that atrophy progression in lvPPA, starting from inferior parietal and temporoparietal junction regions, predominantly follows at least two partially nonoverlapping pathways, which may influence the heterogeneity in clinical presentation and prognosis.

IntroductionUnhealthy alcohol use is associated with a range of adverse outcomes among people with HIV (PWH). Testing the efficacy and promoting the availability of effective interventions to address unhealthy alcohol use among PWH is thus a priority. Alcohol use outcomes in intervention studies are often measured by self-report alone, which can lead to spurious results due to information biases (eg, social desirability). Measuring alcohol outcomes objectively through biomarkers, such as phosphatidylethanol (PEth), in addition to self-report has potential to improve the validity of intervention studies. This protocol outlines the methods for a systematic review and individual participant data meta-analysis that will estimate the efficacy of interventions to reduce alcohol use as measured by a combined categorical self-report/PEth variable among PWH and compare these estimates to those generated when alcohol is measured by self-report or PEth alone.Methods and analysisWe will include randomised controlled trials that: (A) tested an alcohol intervention (behavioural and/or pharmacological), (B) enrolled participants 15 years or older with HIV; (C) included both PEth and self-report measurements, (D) completed data collection by 31 August 2023. We will contact principal investigators of eligible studies to inquire about their willingness to contribute data. The primary outcome variable will be a combined self-report/PEth alcohol categorical variable. Secondary outcomes will include PEth alone, self-report alone and HIV viral suppression. We will use a two-step meta-analysis and random effects modelling to estimate pooled treatment effects; I2 will be calculated to evaluate heterogeneity. Secondary and sensitivity analyses will explore treatment effects in adjusted models and within subgroups. Funnel plots will be used to explore publication bias.Ethics and disseminationThe study will be conducted with deidentified data from completed randomised controlled trials and will be considered exempt from additional ethical approval. Results will be disseminated through peer-reviewed publications and international scientific meetings.Prospero registration numberCRD42022373640.

BackgroundMucin disulfide cross-links mediate pathologic mucus formation in muco-obstructive lung diseases. MUC-031, a novel thiol-modified carbohydrate compound, cleaves disulfides to cause mucolysis. The aim of this study was to determine the mucolytic and therapeutic effects of MUC-031 in sputum from patients with cystic fibrosis (CF) and mice with muco-obstructive lung disease (βENaC-Tg mice).MethodsWe compared the mucolytic efficacy of MUC-031 and existing mucolytics (N-acetylcysteine (NAC) and recombinant human deoxyribonuclease I (rhDNase)) using rheology to measure the elastic modulus (G') of CF sputum, and we tested effects of MUC-031 on airway mucus plugging, inflammation and survival in βENaC-Tg mice to determine its mucolytic efficacy in vivo.ResultsIn CF sputum, compared to the effects of rhDNase and NAC, MUC-031 caused a larger decrease in sputum G', was faster in decreasing sputum G' by 50% and caused mucolysis of a larger proportion of sputum samples within 15 min of drug addition. Compared to vehicle control, three treatments with MUC-031 in 1 day in adult βENaC-Tg mice decreased airway mucus content (16.8±3.2 versus 7.5±1.2 nL·mm-2, p

BackgroundEpigenetic inhibition of the O6-methylguanine-DNA-methyltransferase (MGMT) gene has emerged as a clinically relevant prognostic marker in glioblastoma (GBM). Methylation of the MGMT promoter has been shown to increase chemotherapy efficacy. While traditionally reported as a binary marker, recent methodological advancements have led to quantitative methods of measuring promoter methylation, providing clearer insight into its functional relationship with survival.MethodsA CLIA assay and bisulfite sequencing was utilized to develop a quantitative, 17-point, MGMT promoter methylation index. GBMs of 240 newly diagnosed patients were sequenced and risk for mortality was assessed. Nonlinearities were captured by fitting splines to Cox proportional hazard models and plotting smoothed residuals. Covariates included age, Karnofsky performance status, IDH1 mutation, and extent of resection.ResultsMedian follow-up time and progression-free survival were 16 and 9 months, respectively. A total of 176 subjects experienced death. A one-unit increase in promoter CpG methylation resulted in a 4% reduction in hazard (95% CI 0.93-0.99, P

BackgroundMild hypoxic-ischemic encephalopathy (HIE) is increasingly recognized as a risk factor for neonatal brain injury. We examined the timing and pattern of brain injury in mild HIE.MethodsThis retrospective cohort study includes infants with mild HIE treated at 9 hospitals. Neonatal brain MRIs were scored by 2 reviewers using a validated classification system, with discrepancies resolved by consensus. Severity and timing of MRI brain injury (i.e., acute, subacute, chronic) was scored on the subset of MRIs that were performed at or before 8 days of age.ResultsOf 142 infants with mild HIE, 87 (61%) had injury on MRI at median age 5 (IQR 4-6) days. Watershed (23%), deep gray (20%) and punctate white matter (18%) injury were most common. Among the 125 (88%) infants who received a brain MRI at ≤8 days, mild (44%) injury was more common than moderate (11%) or severe (4%) injury. Subacute (37%) lesions were more commonly observed than acute (32%) or chronic lesions (1%).ConclusionSubacute brain injury is common in newborn infants with mild HIE. Novel neuroprotective treatments for mild HIE will ideally target both subacute and acute injury mechanisms.ImpactAlmost two-thirds of infants with mild HIE have evidence of brain injury on MRI obtained in the early neonatal period. Subacute brain injury was seen in 37% of infants with mild HIE. Neuroprotective treatments for mild HIE will ideally target both acute and subacute injury mechanisms.

Musculoskeletal conditions impede patient biomechanical function. However, clinicians rely on subjective functional assessments with poor test characteristics for biomechanical outcomes because more advanced assessments are impractical in the ambulatory care setting. Using markerless motion capture (MMC) in clinic to record time-series joint position data, we implemented a spatiotemporal assessment of patient kinematics during lower extremity functional testing to evaluate whether kinematic models could identify disease states beyond conventional clinical scoring. 213 trials of the star excursion balance test (SEBT) were recorded by 36 subjects during routine ambulatory clinic visits using both MMC technology and conventional clinician scoring. Conventional clinical scoring failed to distinguish patients with symptomatic lower extremity osteoarthritis (OA) from healthy controls in each component of the assessment. However, principal component analysis of shape models generated from MMC recordings revealed significant differences in subject posture between the OA and control cohorts for six of the eight components. Additionally, time-series models of subject posture change over time revealed distinct movement patterns and reduced overall postural change in the OA cohort compared to the controls. Finally, a novel metric quantifying postural control was derived from subject specific kinematic models and was shown to distinguish OA (1.69), asymptomatic postoperative (1.27), and control (1.23) cohorts (p = 0.0025) and to correlate with patient-reported OA symptom severity (R = -0.72, p = 0.018). Time series motion data have superior discriminative validity and clinical utility than conventional functional assessments in the case of the SEBT. Novel spatiotemporal assessment approaches can enable routine in-clinic collection of objective patient-specific biomechanical data for clinical decision-making and monitoring recovery.

Background contextFor chronic low back pain, the causal mechanisms between pathological features from imaging and patient symptoms are unclear. For instance, disc herniations can often be present without symptoms. There remains a need for improved knowledge of the pathophysiological mechanisms that explore spinal tissue damage and clinical manifestations of pain and disability. Spaceflight and astronaut health provides a rare opportunity to study potential low back pain mechanisms longitudinally. Spaceflight disrupts diurnal loading on the spine and several lines of evidence indicate that astronauts are at a heightened risk for low back pain and disc herniation following spaceflight.PurposeTo examine the relationship between prolonged exposure to microgravity and the elevated incidence of postflight disc herniation, we conducted a longitudinal study to track the spinal health of twelve NASA astronauts before and after approximately 6 months in space. We hypothesize that the incidence of postflight disc herniation and low back complaints associates with spaceflight-included muscle atrophy and pre-existing spinal pathology.Study designThis is a prospective longitudinal study.Patient sampleOur sample included a cohort of twelve astronaut crewmembers.Outcome measuresFrom 3T MRI, we quantified disc water content (ms), disc degeneration (Pfirrmann grade), vertebral endplate irregularities, facet arthropathy and/ fluid, high intensity zones, disc herniation, multifidus total cross-sectional area (cm2), multifidus lean muscle cross-sectional area (cm2), and muscle quality/composition (%). From quantitative fluoroscopy we quantified, maximum flexion-extension ROM (°), maximum lateral bending ROM (°), and maximum translation (%). Lastly, patient outcomes and clinical notes were used for identifying postflight symptoms associated with disc herniations from 3T MRI.MethodsAdvanced imaging data from 3T MRI were collected at three separate time points in relation to spending six months in space: (1) within a year before launch ("pre-flight"), (2) within a week after return to Earth ("post-flight"), and (3) between 1 and 2 months after return to Earth ("recovery"). Fluoroscopy of segmental kinematics was collected at preflight and postflight timepoints. We assessed the effect of spaceflight and postflight recovery on longitudinal changes in spinal structure and function, as well as differences between crew members who did and did not present a symptomatic disc herniation following spaceflight.ResultsHalf of our astronauts (n=6) experienced new symptoms associated with a new or previously asymptomatic lumbar disc protrusion or extrusion following spaceflight. We observed decreased multifidus muscle quality following spaceflight in the lower lumbar spine, with a reduced percentage of lean muscle at L4L5 (-6.2%, p=.009) and L5S1 (-7.0%, p=.006) associated with the incidence of new disc herniation. Additionally, we observed reduced lumbar segment flexion-extension ROM for L2L3 (-17.2%, p=.006) and L3L4 (-20.5%, p=.02) following spaceflight, and furthermore that reduced ROM among the upper three lumbar segments (-24.1%, p=.01) associated with the incidence of disc herniation. Existing endplate pathology was most prevalent in the upper lumbar spine and associated with reduced segmental ROM (-20.5%, p=.02).ConclusionsIn conclusion from a 10-year study investigating the effects of spaceflight on the lumbar spine and risk for disc herniation, we found the incidence of lumbar disc herniation following spaceflight associates with compromised multifidus muscle quality and spinal segment kinematics, as well as pre-existing spinal endplate irregularities. These findings suggest differential effects of spinal stiffness and muscle loss in the upper versus lower lumbar spine regions that may specifically provoke risk for symptomatic disc herniation in the lower lumbar spine following spaceflight. Results from this study provide a unique longitudinal assessment of mechanisms and possible risk factors for developing disc herniations and related low back pain. Furthermore, these findings will help inform physiologic countermeasures to maintain spinal health in astronauts during long-duration missions in space.

BackgroundThere is mounting evidence for the presence of postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC), but there is limited information on the spectrum, magnitude, duration, and patterns of these sequelae as well as their influence on quality of life.MethodsWe assembled a cohort of adults with a documented history of SARS-CoV-2 RNA positivity at ≥2 weeks past onset of coronavirus disease 2019 (COVID-19) symptoms or, if asymptomatic, first positive test. At 4-month intervals, we queried physical and mental health symptoms and quality of life.ResultsOf the first 179 participants enrolled, 10 were asymptomatic during the acute phase of SARS-CoV-2 infection, 125 were symptomatic but not hospitalized, and 44 were symptomatic and hospitalized. During the postacute phase, fatigue, shortness of breath, concentration problems, headaches, trouble sleeping, and anosmia/dysgeusia were most common through 8 months of observation. Symptoms were typically at least somewhat bothersome and sometimes exhibited a waxing-and-waning course. Some participants experienced symptoms of depression, anxiety, and post-traumatic stress, as well as difficulties with performance of usual activities. The median visual analogue scale rating of general health was lower at 4 and 8 months compared with pre-COVID-19. Two clusters of symptom domains were identified.ConclusionsMany participants report bothersome symptoms following onset of COVID-19 with variable patterns of persistence and impact on quality of life. The substantial variability suggests the existence of multiple subphenotypes of PASC. A rigorous approach to the prospective measurement of symptoms and functional manifestations sets the stage for the next phase of research focusing on the pathophysiologic causes of the various subgroups of PASC.

BackgroundThere is great interest in finding ways to identify patients who will develop toxicity to cancer therapies. This has become especially pressing in the era of immune therapy, where toxicity can be long-lasting and life-altering, and primarily comes in the form of immune-related adverse effects (irAEs). Treatment with the first drugs in this class, anti-programmed death 1 (anti-PD1)/programmed death-ligand 1 (PDL1) checkpoint therapies, results in grade 2 or higher irAEs in up to 25%-30% of patients, which occur most commonly within the first 6 months of treatment and can include arthralgias, rash, pruritus, pneumonitis, diarrhea and/or colitis, hepatitis, and endocrinopathies. We tested the hypothesis that germline microRNA pathway functional variants, known to predict altered systemic stress responses to cancer therapies, would predict irAEs in patients across cancer types.MethodsMicroRNA pathway variants were evaluated for an association with grade 2 or higher toxicity using four classifiers on 62 patients with melanoma, and then the panel's performance was validated on 99 patients with other cancer types. Trained classifiers included classification trees, LASSO-regularized logistic regression, boosted trees, and random forests. Final performance measures were reported on the training set using leave-one-out cross validation and validated on held-out samples. The predicted probability of toxicity was evaluated for its association, if any, with response categories to anti-PD1/PDL1 therapy in the melanoma cohort.ResultsA biomarker panel was identified that predicts toxicity with 80% accuracy (F1=0.76, area under the curve (AUC)=0.82) in the melanoma training cohort and 77.6% accuracy (F1=0.621, AUC=0.778) in the pan-cancer validation cohort. In the melanoma cohort, the predictive probability of toxicity was not associated with response categories to anti-PD1/PDL1 therapy (p=0.70). In the same cohort, the most significant biomarker of toxicity in RAC1, predicting a greater than ninefold increased risk of toxicity (p

Abstract BACKGROUND Epigenetic inhibition of the O6-methylguanine-DNA-methyltransferase (MGMT) gene has emerged as a clinically relevant prognostic marker in glioblastoma (GBM). Methylation of the MGMT promoter has been shown to increase chemotherapy efficacy. While traditionally reported as a binary marker, recent methodological advancements have led to quantitative approaches that measure methylation, providing clearer insights into methylation’s functional relationship with survival. METHODS A CLIA assay and bisulfite sequencing was utilized to develop a quantitative, 17-point MGMT promoter methylation index derived from the number of methylated CpG sites. Retrospective review of 240 newly diagnosed GBM patients was performed in order to discern how risk for mortality transforms as promoter methylation increases. Non-linearities were captured by fitting splines to Cox proportional hazard models, plotting smoothed residuals, and creating survival plots. Covariates included age, KPS, IDH1 mutation, and extent of resection. RESULTS Median follow-up time and progression free survival were 16 and 9 months, respectively. 176 subjects experienced death. A one-unit increase in CpG methylation on a scale of 1-17 resulted in a 4% reduction in hazard (95% CI 0.93–0.99, P< 0.005). Moreover, GBM patients with low-levels of methylation (1-6 CpG sites) fared markedly worse (HR=1.62, 95% CI 1.03-2.54, P< 0.036) than individuals who were unmethylated (reference group). Subjects with medium-levels of methylation (7-12 CpG sites) had the greatest reduction in hazard (HR=0.48, 95% CI 0.29-0.80, P< 0.004), followed by individuals in the highest methylation tertile (HR=0.62, 95% CI 0.40-0.97, P< 0.035). CONCLUSION This novel approach offers greater bisulfite conversion efficiency when compared to alternative methods, reducing the likelihood of false positives. Analysis of the resulting methylation index scores demonstrates a non-linear relationship between MGMT methylation and survival, suggesting conformation of the marker’s protective effect. These findings challenge the current understanding of MGMT’s functional form and underline why implementing an “optimal cutoff point” may be disadvantageous.

ObjectiveTo evaluate the association of therapeutic hypothermia with magnetic resonance imaging (MRI) findings and 30-month neurodevelopment in term neonatal encephalopathy.Study designCross-sectional analysis of 30-month neurodevelopment (IQR 19.0-31.4) in a prospective cohort of mild-to-severe neonatal encephalopathy imaged on day 4 (1993-2017 with institutional implementation of therapeutic hypothermia in 2007). MRI injury was classified as normal, watershed, or basal ganglia/thalamus. Abnormal motor outcome was defined as Bayley-II psychomotor developmental index

Abstract Background Epigenetic inhibition of the O6-methylguanine-DNA-methyltransferase (MGMT) gene has emerged as a clinically relevant prognostic marker in glioblastoma (GBM). Methylation of the MGMT promoter has been shown to increase chemotherapy efficacy. While traditionally reported as a binary marker, recent methodological advancements have led to quantitative methods of measuring methylation, allowing for clearer insights into methylation’s functional relationship with survival. Methods A CLIA assay and bisulfite sequencing was utilized to develop a quantitative, 17-point MGMT promoter methylation index derived from the number of methylated CpG sites. Retrospective review of 242 newly diagnosed GBM patients was performed in order to discern how risk for mortality transforms as promoter methylation increases. Non-linearities were captured by fitting splines to Cox proportional hazard models, plotting smoothed residuals, and creating survival plots. Covariates included age, KPS, IDH1 mutation, and extent of resection. Results Median follow-up time and progression free survival were 15.9 and 9 months, respectively. 176 subjects experienced death. A one-unit increase in CpG methylation resulted in a 4% reduction in hazard (95% CI 0.93–0.99, P

Electroencephalography (EEG) data possess a complex structure that includes regional, functional, and longitudinal dimensions. Our motivating example is a word segmentation paradigm in which typically developing (TD) children, and children with autism spectrum disorder (ASD) were exposed to a continuous speech stream. For each subject, continuous EEG signals recorded at each electrode were divided into one-second segments and projected into the frequency domain via fast Fourier transform. Following a spectral principal components analysis, the resulting data consist of region-referenced principal power indexed regionally by scalp location, functionally across frequencies, and longitudinally by one-second segments. Standard EEG power analyses often collapse information across the longitudinal and functional dimensions by averaging power across segments and concentrating on specific frequency bands. We propose a hybrid principal components analysis for region-referenced longitudinal functional EEG data, which utilizes both vector and functional principal components analyses and does not collapse information along any of the three dimensions of the data. The proposed decomposition only assumes weak separability of the higher-dimensional covariance process and utilizes a product of one dimensional eigenvectors and eigenfunctions, obtained from the regional, functional, and longitudinal marginal covariances, to represent the observed data, providing a computationally feasible non-parametric approach. A mixed effects framework is proposed to estimate the model components coupled with a bootstrap test for group level inference, both geared towards sparse data applications. Analysis of the data from the word segmentation paradigm leads to valuable insights about group-region differences among the TD and verbal and minimally verbal children with ASD. Finite sample properties of the proposed estimation framework and bootstrap inference procedure are further studied via extensive simulations.

Biomarker development is currently a high priority in neurodevelopmental disorder research. For many types of biomarkers (particularly biomarkers of diagnosis), reliability over short periods is critically important. In the field of autism spectrum disorder (ASD), resting electroencephalography (EEG) power spectral densities (PSD) are well-studied for their potential as biomarkers. Classically, such data have been decomposed into pre-specified frequency bands (e.g., delta, theta, alpha, beta, and gamma). Recent technical advances, such as the Fitting Oscillations and One-Over-F (FOOOF) algorithm, allow for targeted characterization of the features that naturally emerge within an EEG PSD, permitting a more detailed characterization of the frequency band-agnostic shape of each individual's EEG PSD. Here, using two resting EEGs collected a median of 6 days apart from 22 children with ASD and 25 typically developing (TD) controls during the Feasibility Visit of the Autism Biomarkers Consortium for Clinical Trials, we estimate test-retest reliability based on the characterization of the PSD shape in two ways: (1) Using the FOOOF algorithm we estimate six parameters (offset, slope, number of peaks, and amplitude, center frequency and bandwidth of the largest alpha peak) that characterize the shape of the EEG PSD; and (2) using nonparametric functional data analyses, we decompose the shape of the EEG PSD into a reduced set of basis functions that characterize individual power spectrum shapes. We show that individuals exhibit idiosyncratic PSD signatures that are stable over recording sessions using both characterizations. Our data show that EEG activity from a brief 2-min recording provides an efficient window into characterizing brain activity at the single-subject level with desirable psychometric characteristics that persist across different analytical decomposition methods. This is a necessary step towards analytical validation of biomarkers based on the EEG PSD and provides insights into parameters of the PSD that offer short-term reliability (and thus promise as potential biomarkers of trait or diagnosis) vs. those that are more variable over the short term (and thus may index state or other rapidly dynamic measures of brain function). Future research should address the longer-term stability of the PSD, for purposes such as monitoring development or response to treatment.

BackgroundThere are more than two million people living with HIV (PLH) in India, with more than 30% on antiretroviral treatment (ART) estimated to be non-adherent. This study aimed to (I) document adherence rates and related factors among ART patients in a large ART clinic in India, and (II) pilot test daily and weekly interactive voice response (IVR) calls to improve ART adherence and related outcomes.MethodsART patients reporting missing at least one dose in prior 6 months (N=362) were enrolled and assessed via self-report and medical record review. Participants were randomized to one of two conditions: (I) twice-daily IVR call reminders with self-management support messaging, plus a weekly IVR adherence assessment; or (II) an attention control, with only weekly IVR adherence assessment. Participants completed study assessments at baseline, 2-, 4-, and 6-months with high retention (88% to 96%).ResultsIntention-to-treat analyses found limited support for intervention effects for improving or maintaining ART adherence or CD4 counts between the two study arms over 6-months follow-up. Adherence increased significantly in the six months prior to baseline from about 65% to >95% with perfect adherence based on pill counts from medical records and consistent with patient self-report measures, which presented ceiling effects for detecting improvements in ART adherence in response to IVR intervention exposure. There was also limited support for intervention effects on secondary, self-management outcomes.ConclusionsHigh levels of adherence were sustained throughout the 6-month RCT. IVR regulation changes in India delayed study launch for 6 months, which likely allowed mobilization of improved adherence at the clinic, provider and patient levels in anticipation of the study launch. Therefore, ceiling effects limited inferences on intervention effects to improve adherence. Results suggest that clinic-level adherence monitoring may be sufficient to mobilize adherence improvements by providers and patients.Trial registrationClinicalTrials.gov registration #NCT02118454.

Electroencephalography (EEG) studies produce region-referenced functional data in the form of EEG signals recorded across electrodes on the scalp. It is of clinical interest to relate the highly structured EEG data to scalar outcomes such as diagnostic status. In our motivating study, resting-state EEG is collected on both typically developing (TD) children and children with autism spectrum disorder (ASD) aged 2 to 12 years old. The peak alpha frequency (PAF), defined as the location of a prominent peak in the alpha frequency band of the spectral density, is an important biomarker linked to neurodevelopment and is known to shift from lower to higher frequencies as children age. To retain the most amount of information from the data, we consider the oscillations in the spectral density within the alpha band, rather than just the peak location, as a functional predictor of diagnostic status (TD vs ASD), adjusted for chronological age. A covariate-adjusted region-referenced generalized functional linear model is proposed for modeling scalar outcomes from region-referenced functional predictors, which utilizes a tensor basis formed from one-dimensional discrete and continuous bases to estimate functional effects across a discrete regional domain while simultaneously adjusting for additional nonfunctional covariates, such as age. The proposed methodology provides novel insights into differences in neural development of TD and ASD children. The efficacy of the proposed methodology is investigated through extensive simulation studies.

Diverse genetic and environmental etiologies converge onto circuit level brain dysfunction in autism spectrum disorder (ASD), manifesting at a macroscopic level as aberrant neural connectivity. Previous studies have described atypical patterns of decreased short range and increased long range connectivity in ASD [1]. However, it remains unclear whether group level features of circuit dysfunction are consistently present across the range of cognitive function seen in the autism spectrum. The dynamics of neural oscillations in the alpha range (6-12 Hz) are exquisitely sensitive to healthy development of functional and structural connectivity. Alpha-band coherence, measured with high temporal-precision electroencephalography (EEG) therefore represents an ideal tool for studying neural connectivity in developmental populations. Here we examined spontaneous alpha phase coherence in a heterogeneous sample of 59 children with ASD and 39 age matched typically developing children. Using a data driven approach, we conducted an unbiased examination of all possible atypical connectivity patterns across all cortical regions. Long-range hypoconnectivity was present in children with ASD compared to typically developing children, with temporal interhemispheric connectivity showing the largest difference between the two groups. Decreased long range alpha coherence distinguishes a heterogeneous group of ASD children from typically developing children. Interhemispheric temporal hypoconnectivity represents a fundamental functional difference in children with ASD across a wide cognitive and age range that may reflect white matter disturbances or increased signal variability at temporal sites in ASD.

ObjectiveThe consequences of maternal depressed mood on children's growth, health, and cognitive and language development are examined over the first 3 years of life.MethodPregnant women in 24 periurban township neighborhoods in Cape Town, South Africa (N = 1,238 mothers) were randomized by neighborhood to a home visiting intervention or a standard care condition. Reassessments were conducted for 93%-85% of mothers at 2-weeks, 6-, 18-, and 36-months postbirth. Regressions were conducted on measures of children's growth, behavior, language, and cognition to examine the impact of four patterns of depressed mood: antenatal only (n = 154, 13.8%), postnatal only (n = 272, 24.3%), antenatal and postnatal (n = 220, 19.7%), and no depressed mood on any assessment (n = 473, 42.3%).ResultsPatterns of depressed mood were similar across intervention conditions. Depressed mothers were significantly less educated, had lower incomes, were less likely to be employed or to have electricity; were more likely to report problematic drinking of alcohol, experience food insecurity, interpersonal partner violence, and to be HIV seropositive. At 36 months, the pattern of maternal depressed mood over time was significantly associated with children's compromised physical growth, both in weight and height, and more internalizing and externalizing symptoms of behavior problems. Measures of language and cognition were similar across maternal patterns of depressed mood.ConclusionsMothers who report depressed mood face significantly more life challenges, both environmental stressors related to poverty and other problematic behaviors. More proximal, postnatal depressed mood appears to have a larger influence on their children, compared with antenatal depressed mood. (PsycINFO Database Record

The electroencephalography (EEG) data created in event-related potential (ERP) experiments have a complex high-dimensional structure. Each stimulus presentation, or trial, generates an ERP waveform which is an instance of functional data. The experiments are made up of sequences of multiple trials, resulting in longitudinal functional data and moreover, responses are recorded at multiple electrodes on the scalp, adding an electrode dimension. Traditional EEG analyses involve multiple simplifications of this structure to increase the signal-to-noise ratio, effectively collapsing the functional and longitudinal components by identifying key features of the ERPs and averaging them across trials. Motivated by an implicit learning paradigm used in autism research in which the functional, longitudinal, and electrode components all have critical interpretations, we propose a multidimensional functional principal components analysis (MD-FPCA) technique which does not collapse any of the dimensions of the ERP data. The proposed decomposition is based on separation of the total variation into subject and subunit level variation which are further decomposed in a two-stage functional principal components analysis. The proposed methodology is shown to be useful for modeling longitudinal trends in the ERP functions, leading to novel insights into the learning patterns of children with Autism Spectrum Disorder (ASD) and their typically developing peers as well as comparisons between the two groups. Finite sample properties of MD-FPCA are further studied via extensive simulations.

Mothers living with HIV (MLH) and their children are typically studied to ensure that perinatal HIV transmission is blocked. Yet, HIV impacts MLH and their children lifelong. We examine child outcomes from pregnancy to 3 years post-birth among a peri-urban population of pregnant MLH and mothers without HIV (MWOH). Almost all pregnant women in 12 neighborhoods (98 %; N = 584) in Cape Town, South Africa were recruited and repeatedly assessed within 2 weeks of birth (92 %), at 6 months (88 %), 18 months (84 %), and 3 years post-birth (86 %). There were 186 MLH and 398 MWOH. Controlling for neighborhood and repeated measures, child and maternal outcomes were contrasted over time using longitudinal random effects regression analyses. For measures collected only at 3 years, outcomes were analyzed using multiple regressions. Compared to MWOH, MLH had less income, more informal housing and food insecurity, used alcohol more often during pregnancy, and were more depressed during pregnancy and over time. Only 4.8 % of MLH's children were seropositive; seropositive children were excluded from additional analyses. Children of MLH tended to have significantly lower weights (p

Among adults living with HIV, unstable housing is a barrier to health. Stably- and unstably-housed adults living with HIV were assessed for over 25 months. At baseline, unstably-housed adults living with HIV had a more recent HIV diagnosis, higher viral loads, worse physical and mental health, lower rates of antiretroviral therapy use and insurance coverage, and higher rates of hard drug use than stably-housed adults living with HIV. At follow-up, the health of both groups was similar, but unstably-housed adults living with HIV reported significantly more hard drug use and mental health symptoms when compared to the stably-housed adults living with HIV. Drug and mental health risks decreased for both groups, but decreases in unprotected sex were greater among unstably-housed adults living with HIV.

Almost all pregnant women (98 %) in 24 Cape Town neighborhoods were randomized by neighborhood to (1) the standard care (SC) condition (n = 12 neighborhoods; n = 594 pregnant women) or (2) the Philani Intervention Program (PIP) in which home visits by Community Health Workers (CHW) were conducted (n = 12 neighborhoods; n = 644 pregnant women). At 36 months post-birth (84.6 % follow-up), PIP mothers were significantly less depressed compared to the SC mothers. Children in PIP were significantly less likely to be stunted (24.3 vs 18.1 %, p = 0.013), to have better vocabularies, and were less likely to be hospitalized than children in the SC condition. These data suggest home visits may need to continue for several years post-birth. Sustainable, scalable perinatal intervention models are needed in LMIC.

Prevention of mother-to-child transmission services are integrated into antenatal care in South Africa, but post-birth care is at HIV clinics. Almost all Mothers Living with HIV (MLH) in 24 township neighborhoods (N = 324) reported engagement in HIV care from pregnancy to 36 months post-birth. Less than half re-engaged in HIV care at 6 months (45%), 52.5% at 18 months, and 62.5% at 36 months. Most were prescribed antiretroviral drugs if re-engaged in care, yet only about half (53%) are on antiretroviral drugs at 36 months post-birth. Implementation of Option B+ will require substantially better engagement in care.

BackgroundSelf-monitoring by mobile phone applications offers new opportunities to engage patients in self-management. Self-monitoring has not been examined thoroughly as a self-directed intervention strategy for self-management of multiple behaviors and states by people living with HIV (PLH).MethodsPLH (n = 50), primarily African American and Latino, were recruited from 2 AIDS services organizations and randomly assigned to daily smartphone (n = 34) or biweekly Web-survey only (n = 16) self-monitoring for 6 weeks. Smartphone self-monitoring included responding to brief surveys on medication adherence, mental health, substance use, and sexual risk behaviors, and brief text diaries on stressful events. Qualitative analyses examine biweekly open-ended user-experience interviews regarding perceived benefits and barriers of self-monitoring, and to elaborate a theoretical model for potential efficacy of self-monitoring to support self-management for multiple domains.ResultsSelf-monitoring functions include reflection for self-awareness, cues to action (reminders), reinforcements from self-tracking, and their potential effects on risk perceptions, motivations, skills, and behavioral activation states. Participants also reported therapeutic benefits related to self-expression for catharsis, nonjudgmental disclosure, and in-the-moment support. About one-third of participants reported that surveys were too long, frequent, or tedious. Some smartphone group participants suggested that daily self-monitoring was more beneficial than biweekly due to frequency and in-the-moment availability. About twice as many daily self-monitoring group participants reported increased awareness and behavior change support from self-monitoring compared with biweekly Web-survey only participants.ConclusionsSelf-monitoring is a potentially efficacious disruptive innovation for supporting self-management by PLH and for complementing other interventions, but more research is needed to confirm efficacy, adoption, and sustainability.

BackgroundSelf-monitoring by mobile phone applications offers new opportunities to engage patients in self-management. Self-monitoring has not been examined thoroughly as a self-directed intervention strategy for self-management of multiple behaviors and states by people living with HIV (PLH).MethodsPLH (n = 50), primarily African American and Latino, were recruited from 2 AIDS services organizations and randomly assigned to daily smartphone (n = 34) or biweekly Web-survey only (n = 16) self-monitoring for 6 weeks. Smartphone self-monitoring included responding to brief surveys on medication adherence, mental health, substance use, and sexual risk behaviors, and brief text diaries on stressful events. Qualitative analyses examine biweekly open-ended user-experience interviews regarding perceived benefits and barriers of self-monitoring, and to elaborate a theoretical model for potential efficacy of self-monitoring to support self-management for multiple domains.ResultsSelf-monitoring functions include reflection for self-awareness, cues to action (reminders), reinforcements from self-tracking, and their potential effects on risk perceptions, motivations, skills, and behavioral activation states. Participants also reported therapeutic benefits related to self-expression for catharsis, nonjudgmental disclosure, and in-the-moment support. About one-third of participants reported that surveys were too long, frequent, or tedious. Some smartphone group participants suggested that daily self-monitoring was more beneficial than biweekly due to frequency and in-the-moment availability. About twice as many daily self-monitoring group participants reported increased awareness and behavior change support from self-monitoring compared with biweekly Web-survey only participants.ConclusionsSelf-monitoring is a potentially efficacious disruptive innovation for supporting self-management by PLH and for complementing other interventions, but more research is needed to confirm efficacy, adoption, and sustainability.