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Giant coronary artery aneurysms and myocardial fibrosis after Kawasaki disease may lead to devastating cardiovascular outcomes. We characterised the vascular and myocardial outcomes in five selected Kawasaki disease patients with a history of giant coronary artery aneurysms that completely regressed.
Methods:
Five patients were selected who had giant coronary artery aneurysm in early childhood that regressed when studied 12–33 years after Kawasaki disease onset. Coronary arteries were imaged by coronary CT angiography, and coronary artery calcium volume scores were determined. We used endocardial strain measurements from CT imaging to assess myocardial regional wall function. Calprotectin and galectin-3 (gal-3) as biomarkers of inflammation and myocardial fibrosis were measured by enzyme-linked immunosorbent assay.
Results:
The five selected patients with regressed giant coronary artery aneurysms had calcium scores of zero, normal levels of calprotectin and gal-3, and normal appearance of the coronary arteries by coronary computed tomography angiography. CT strain demonstrated normal peak systolic and diastolic strain patterns in four of five patients. In one patient with a myocardial infarction at the time of Kawasaki disease diagnosis at the age of 10 months, CT strain showed altered global longitudinal strain, reduced segmental peak strain, and reduced diastolic relaxation patterns in multiple left ventricle segments.
Conclusions:
These patients illustrate that regression of giant aneurysms after Kawasaki disease is possible with no detectable calcium, normal biomarkers of inflammation and fibrosis, and normal myocardial function. Individuals with regressed giant coronary artery aneurysm still require longitudinal surveillance to assess the durability of this favourable outcome.
Diagnosis of acute ischemia typically relies on evidence of ischemic lesions on magnetic resonance imaging (MRI), a limited diagnostic resource. We aimed to determine associations of clinical variables and acute infarcts on MRI in patients with suspected low-risk transient ischemic attack (TIA) and minor stroke and to assess their predictive ability.
Methods:
We conducted a post-hoc analysis of the Diagnosis of Uncertain-Origin Benign Transient Neurological Symptoms (DOUBT) study, a prospective, multicenter cohort study investigating the frequency of acute infarcts in patients with low-risk neurological symptoms. Primary outcome parameter was defined as diffusion-weighted imaging (DWI)-positive lesions on MRI. Logistic regression analysis was performed to evaluate associations of clinical characteristics with MRI-DWI-positivity. Model performance was evaluated by Harrel’s c-statistic.
Results:
In 1028 patients, age (Odds Ratio (OR) 1.03, 95% Confidence Interval (CI) 1.01–1.05), motor (OR 2.18, 95%CI 1.27–3.65) or speech symptoms (OR 2.53, 95%CI 1.28–4.80), and no previous identical event (OR 1.75, 95%CI 1.07–2.99) were positively associated with MRI-DWI-positivity. Female sex (OR 0.47, 95%CI 0.32–0.68), dizziness and gait instability (OR 0.34, 95%CI 0.14–0.69), normal exam (OR 0.55, 95%CI 0.35–0.85) and resolved symptoms (OR 0.49, 95%CI 0.30–0.78) were negatively associated. Symptom duration and any additional symptoms/symptom combinations were not associated. Predictive ability of the model was moderate (c-statistic 0.72, 95%CI 0.69–0.77).
Conclusion:
Detailed clinical information is helpful in assessing the risk of ischemia in patients with low-risk neurological events, but a predictive model had only moderate discriminative ability. Patients with clinically suspected low-risk TIA or minor stroke require MRI to confirm the diagnosis of cerebral ischemia.
To assess whether measurement and feedback of chlorhexidine gluconate (CHG) skin concentrations can improve CHG bathing practice across multiple intensive care units (ICUs).
Design:
A before-and-after quality improvement study measuring patient CHG skin concentrations during 6 point-prevalence surveys (3 surveys each during baseline and intervention periods).
Setting:
The study was conducted across 7 geographically diverse ICUs with routine CHG bathing.
Participants:
Adult patients in the medical ICU.
Methods:
CHG skin concentrations were measured at the neck, axilla, and inguinal region using a semiquantitative colorimetric assay. Aggregate unit-level CHG skin concentration measurements from the baseline period and each intervention period survey were reported back to ICU leadership, which then used routine education and quality improvement activities to improve CHG bathing practice. We used multilevel linear models to assess the impact of intervention on CHG skin concentrations.
Results:
We enrolled 681 (93%) of 736 eligible patients; 92% received a CHG bath prior to survey. At baseline, CHG skin concentrations were lowest on the neck, compared to axillary or inguinal regions (P < .001). CHG was not detected on 33% of necks, 19% of axillae, and 18% of inguinal regions (P < .001 for differences in body sites). During the intervention period, ICUs that used CHG-impregnated cloths had a 3-fold increase in patient CHG skin concentrations as compared to baseline (P < .001).
Conclusions:
Routine CHG bathing performance in the ICU varied across multiple hospitals. Measurement and feedback of CHG skin concentrations can be an important tool to improve CHG bathing practice.
The U.S. Department of Agriculture–Agricultural Research Service (USDA-ARS) has been a leader in weed science research covering topics ranging from the development and use of integrated weed management (IWM) tactics to basic mechanistic studies, including biotic resistance of desirable plant communities and herbicide resistance. ARS weed scientists have worked in agricultural and natural ecosystems, including agronomic and horticultural crops, pastures, forests, wild lands, aquatic habitats, wetlands, and riparian areas. Through strong partnerships with academia, state agencies, private industry, and numerous federal programs, ARS weed scientists have made contributions to discoveries in the newest fields of robotics and genetics, as well as the traditional and fundamental subjects of weed–crop competition and physiology and integration of weed control tactics and practices. Weed science at ARS is often overshadowed by other research topics; thus, few are aware of the long history of ARS weed science and its important contributions. This review is the result of a symposium held at the Weed Science Society of America’s 62nd Annual Meeting in 2022 that included 10 separate presentations in a virtual Weed Science Webinar Series. The overarching themes of management tactics (IWM, biological control, and automation), basic mechanisms (competition, invasive plant genetics, and herbicide resistance), and ecosystem impacts (invasive plant spread, climate change, conservation, and restoration) represent core ARS weed science research that is dynamic and efficacious and has been a significant component of the agency’s national and international efforts. This review highlights current studies and future directions that exemplify the science and collaborative relationships both within and outside ARS. Given the constraints of weeds and invasive plants on all aspects of food, feed, and fiber systems, there is an acknowledged need to face new challenges, including agriculture and natural resources sustainability, economic resilience and reliability, and societal health and well-being.
Antimicrobial stewardship has special challenges in particular populations and facilities, including pediatrics. We sought to augment the information available to antimicrobial stewardship programs (ASPs) by created a cumulative statewide antibiogram for neonatal and pediatric populations.
Methods:
In the Antimicrobial Stewardship Collaborative of South Carolina (ASC-SC), we created statewide antibiograms, including a separate antibiogram accounting for the pediatric and neonatal intensive care unit (NICU) populations. We collated data from the 4 pediatric and 3 NICU facilities in the state to provide a cumulative statewide antibiogram.
Results:
Methicillin-susceptible Staphylococcus aureus was more prevalent than methicillin-resistant Staphylococcus aureus. Pseudomonas aeruginosa, Citrobacter koserii, and Acinetobacter baumannii were isolated in only 1 NICU.
Conclusions:
These antibiograms should improve empiric prescribing in both the inpatient and outpatient setting, providing data in some areas that historically do not have pediatric antibiogram to inform prescribing. The antibiogram alone is not sufficient independently to improve prescribing but is one important aspect of stewardship in the pediatric population of South Carolina.
Lumateperone (LUMA) is an FDA-approved antipsychotic to treat schizophrenia and depressive episodes associated with bipolar I or bipolar II disorder. An open-label study (Study 303) evaluated the safety and tolerability of LUMA in outpatients with stable schizophrenia who switched from previous antipsychotic (AP) treatment. This post hoc analysis of Study 303 investigated the safety and tolerability of LUMA stratified by previous AP in patients who switched to LUMA treatment for 6 weeks.
Methods
Adult outpatients (≥18 years) with stable schizophrenia were switched from previous AP to LUMA 42 mg once daily for 6 weeks followed by switching to another approved AP for 2 weeks follow-up. Post hoc analyses were stratified by most common previous AP: risperidone or paliperidone (RIS/PAL); quetiapine (QET); aripiprazole or brexpiprazole (ARI/BRE); olanzapine (OLA). Safety analyses included adverse events (AE), vital signs, and laboratory tests. Efficacy was assessed using the Positive and Negative Syndrome Scale (PANSS) and the Clinical Global Impressions-Severity (CGI-S) scale.
Results
The safety population comprised 301 patients, of which 235 (78.1%) were previously treated with RIS/PAL (n=95), QET (n=60), ARI/BRE (n=43), or OLA (n=37). Rates of treatment-emergent AEs (TEAEs) while on LUMA were similar between previous AP groups (44.2%-55.8%). TEAEs with incidences of ≥5% in any AP group were dry mouth, somnolence, sedation, headache, diarrhea, cough, and insomnia. Most TEAEs were mild or moderate in severity for all groups. Rates of serious TEAEs were low and similar between groups (0%–7.0%).
Statistically significant (P<.05) decreases from baseline were observed in the OLA group that switched to LUMA in total cholesterol and low-density lipoprotein cholesterol with significant decreases thereafter on LUMA. Statistically significant decreases in prolactin levels were observed in both the RIS/PAL (P<.0001) and OLA (P<.05) groups. Patients switched from RIS/PAL to LUMA showed significant (P<.05) decreases for body mass index, waist circumference, and weight. At follow-up, 2 weeks after patients switched back from LUMA to another AP, none of the decreases in laboratory parameters or body morphology observed while on LUMA maintained significance.
Those switching from QET had significant improvements from baseline at Day 42 in PANSS Total score (mean change from baseline −3.47; 95% confidence interval [CI] −5.27, −1.68; P<.001) and CGI-S Total score (mean change from baseline −0.24; 95% CI, −0.38, −0.10; P<.01).
Conclusion
In outpatients with stable schizophrenia, LUMA 42 mg treatment was well tolerated in patients switching from a variety of previous APs. Patients switching from RIS/PAL or OLA to LUMA had significant improvements in cardiometabolic and prolactin parameters. These data further support the favorable safety, tolerability, and efficacy of LUMA in patients with schizophrenia.
Risk of suicide-related behaviors is elevated among military personnel transitioning to civilian life. An earlier report showed that high-risk U.S. Army soldiers could be identified shortly before this transition with a machine learning model that included predictors from administrative systems, self-report surveys, and geospatial data. Based on this result, a Veterans Affairs and Army initiative was launched to evaluate a suicide-prevention intervention for high-risk transitioning soldiers. To make targeting practical, though, a streamlined model and risk calculator were needed that used only a short series of self-report survey questions.
Methods
We revised the original model in a sample of n = 8335 observations from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in one of three Army STARRS 2011–2014 baseline surveys while in service and in one or more subsequent panel surveys (LS1: 2016–2018, LS2: 2018–2019) after leaving service. We trained ensemble machine learning models with constrained numbers of item-level survey predictors in a 70% training sample. The outcome was self-reported post-transition suicide attempts (SA). The models were validated in the 30% test sample.
Results
Twelve-month post-transition SA prevalence was 1.0% (s.e. = 0.1). The best constrained model, with only 17 predictors, had a test sample ROC-AUC of 0.85 (s.e. = 0.03). The 10–30% of respondents with the highest predicted risk included 44.9–92.5% of 12-month SAs.
Conclusions
An accurate SA risk calculator based on a short self-report survey can target transitioning soldiers shortly before leaving service for intervention to prevent post-transition SA.
Cognitive impairments are well-established features of psychotic disorders and are present when individuals are at ultra-high risk for psychosis. However, few interventions target cognitive functioning in this population.
Aims
To investigate whether omega-3 polyunsaturated fatty acid (n−3 PUFA) supplementation improves cognitive functioning among individuals at ultra-high risk for psychosis.
Method
Data (N = 225) from an international, multi-site, randomised controlled trial (NEURAPRO) were analysed. Participants were given omega-3 supplementation (eicosapentaenoic acid and docosahexaenoic acid) or placebo over 6 months. Cognitive functioning was assessed with the Brief Assessment of Cognition in Schizophrenia (BACS). Mixed two-way analyses of variance were computed to compare the change in cognitive performance between omega-3 supplementation and placebo over 6 months. An additional biomarker analysis explored whether change in erythrocyte n−3 PUFA levels predicted change in cognitive performance.
Results
The placebo group showed a modest greater improvement over time than the omega-3 supplementation group for motor speed (ηp2 = 0.09) and BACS composite score (ηp2 = 0.21). After repeating the analyses without individuals who transitioned, motor speed was no longer significant (ηp2 = 0.02), but the composite score remained significant (ηp2 = 0.02). Change in erythrocyte n-3 PUFA levels did not predict change in cognitive performance over 6 months.
Conclusions
We found no evidence to support the use of omega-3 supplementation to improve cognitive functioning in ultra-high risk individuals. The biomarker analysis suggests that this finding is unlikely to be attributed to poor adherence or consumption of non-trial n−3 PUFAs.
Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA).
Methods
A 2018–2020 national sample of n = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment. Using baseline self-report data along with administrative and geospatial data, an ensemble machine learning method was used to develop a model for 3-month treatment response defined by the Quick Inventory of Depression Symptomatology Self-Report and a modified Sheehan Disability Scale. The model was developed in a 70% training sample and tested in the remaining 30% test sample.
Results
In total, 35.7% of patients responded to treatment. The prediction model had an area under the ROC curve (s.e.) of 0.66 (0.04) in the test sample. A strong gradient in probability (s.e.) of treatment response was found across three subsamples of the test sample using training sample thresholds for high [45.6% (5.5)], intermediate [34.5% (7.6)], and low [11.1% (4.9)] probabilities of response. Baseline symptom severity, comorbidity, treatment characteristics (expectations, history, and aspects of current treatment), and protective/resilience factors were the most important predictors.
Conclusions
Although these results are promising, parallel models to predict response to alternative treatments based on data collected before initiating treatment would be needed for such models to help guide treatment selection.
The Hierarchical Taxonomy of Psychopathology (HiTOP) has emerged out of the quantitative approach to psychiatric nosology. This approach identifies psychopathology constructs based on patterns of co-variation among signs and symptoms. The initial HiTOP model, which was published in 2017, is based on a large literature that spans decades of research. HiTOP is a living model that undergoes revision as new data become available. Here we discuss advantages and practical considerations of using this system in psychiatric practice and research. We especially highlight limitations of HiTOP and ongoing efforts to address them. We describe differences and similarities between HiTOP and existing diagnostic systems. Next, we review the types of evidence that informed development of HiTOP, including populations in which it has been studied and data on its validity. The paper also describes how HiTOP can facilitate research on genetic and environmental causes of psychopathology as well as the search for neurobiologic mechanisms and novel treatments. Furthermore, we consider implications for public health programs and prevention of mental disorders. We also review data on clinical utility and illustrate clinical application of HiTOP. Importantly, the model is based on measures and practices that are already used widely in clinical settings. HiTOP offers a way to organize and formalize these techniques. This model already can contribute to progress in psychiatry and complement traditional nosologies. Moreover, HiTOP seeks to facilitate research on linkages between phenotypes and biological processes, which may enable construction of a system that encompasses both biomarkers and precise clinical description.
The transition from military service to civilian life is a high-risk period for suicide attempts (SAs). Although stressful life events (SLEs) faced by transitioning soldiers are thought to be implicated, systematic prospective evidence is lacking.
Methods
Participants in the Army Study to Assess Risk and Resilience in Servicemembers (STARRS) completed baseline self-report surveys while on active duty in 2011–2014. Two self-report follow-up Longitudinal Surveys (LS1: 2016–2018; LS2: 2018–2019) were subsequently administered to probability subsamples of these baseline respondents. As detailed in a previous report, a SA risk index based on survey, administrative, and geospatial data collected before separation/deactivation identified 15% of the LS respondents who had separated/deactivated as being high-risk for self-reported post-separation/deactivation SAs. The current report presents an investigation of the extent to which self-reported SLEs occurring in the 12 months before each LS survey might have mediated/modified the association between this SA risk index and post-separation/deactivation SAs.
Results
The 15% of respondents identified as high-risk had a significantly elevated prevalence of some post-separation/deactivation SLEs. In addition, the associations of some SLEs with SAs were significantly stronger among predicted high-risk than lower-risk respondents. Demographic rate decomposition showed that 59.5% (s.e. = 10.2) of the overall association between the predicted high-risk index and subsequent SAs was linked to these SLEs.
Conclusions
It might be possible to prevent a substantial proportion of post-separation/deactivation SAs by providing high-risk soldiers with targeted preventive interventions for exposure/vulnerability to commonly occurring SLEs.
Fewer than half of patients with major depressive disorder (MDD) respond to psychotherapy. Pre-emptively informing patients of their likelihood of responding could be useful as part of a patient-centered treatment decision-support plan.
Methods
This prospective observational study examined a national sample of 807 patients beginning psychotherapy for MDD at the Veterans Health Administration. Patients completed a self-report survey at baseline and 3-months follow-up (data collected 2018–2020). We developed a machine learning (ML) model to predict psychotherapy response at 3 months using baseline survey, administrative, and geospatial variables in a 70% training sample. Model performance was then evaluated in the 30% test sample.
Results
32.0% of patients responded to treatment after 3 months. The best ML model had an AUC (SE) of 0.652 (0.038) in the test sample. Among the one-third of patients ranked by the model as most likely to respond, 50.0% in the test sample responded to psychotherapy. In comparison, among the remaining two-thirds of patients, <25% responded to psychotherapy. The model selected 43 predictors, of which nearly all were self-report variables.
Conclusions
Patients with MDD could pre-emptively be informed of their likelihood of responding to psychotherapy using a prediction tool based on self-report data. This tool could meaningfully help patients and providers in shared decision-making, although parallel information about the likelihood of responding to alternative treatments would be needed to inform decision-making across multiple treatments.
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
Aims
To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
Method
Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
Results
Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
Conclusions
AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Retrospective self-report is typically used for diagnosing previous pediatric traumatic brain injury (TBI). A new semi-structured interview instrument (New Mexico Assessment of Pediatric TBI; NewMAP TBI) investigated test–retest reliability for TBI characteristics in both the TBI that qualified for study inclusion and for lifetime history of TBI.
Method:
One-hundred and eight-four mTBI (aged 8–18), 156 matched healthy controls (HC), and their parents completed the NewMAP TBI within 11 days (subacute; SA) and 4 months (early chronic; EC) of injury, with a subset returning at 1 year (late chronic; LC).
Results:
The test–retest reliability of common TBI characteristics [loss of consciousness (LOC), post-traumatic amnesia (PTA), retrograde amnesia, confusion/disorientation] and post-concussion symptoms (PCS) were examined across study visits. Aside from PTA, binary reporting (present/absent) for all TBI characteristics exhibited acceptable (≥0.60) test–retest reliability for both Qualifying and Remote TBIs across all three visits. In contrast, reliability for continuous data (exact duration) was generally unacceptable, with LOC and PCS meeting acceptable criteria at only half of the assessments. Transforming continuous self-report ratings into discrete categories based on injury severity resulted in acceptable reliability. Reliability was not strongly affected by the parent completing the NewMAP TBI.
Conclusions:
Categorical reporting of TBI characteristics in children and adolescents can aid clinicians in retrospectively obtaining reliable estimates of TBI severity up to a year post-injury. However, test–retest reliability is strongly impacted by the initial data distribution, selected statistical methods, and potentially by patient difficulty in distinguishing among conceptually similar medical concepts (i.e., PTA vs. confusion).
Current treatments for schizophrenia are often associated with increased rates of metabolic syndrome (MetSy). MetSy is defined as meeting 3 of the following 5 criteria: waist circumference >40in (men) or >35in (women), triglycerides =150mg/dL, high density lipoprotein cholesterol (HDL) <40mg/dL (men) or <50mg/dL (women), systolic blood pressure (BP) =130mmHg or diastolic BP =85mmHg, fasting glucose =100mg/dL. Patients with MetSy have an elevated risk of developing type II diabetes and increased mortality due to cardiovascular disease. Lumateperone (lumateperone tosylate, ITI−007), a mechanistically novel antipsychotic that simultaneously modulates serotonin, dopamine, and glutamate neurotransmission, is FDA approved for the treatment of schizophrenia. This distinct pharmacological profile has been associated with favorable tolerability and a low risk of adverse metabolic effects in clinical trials. This post hoc analysis of 2 randomized, double-blind, placebo-controlled studies of patients with an acute exacerbation of schizophrenia compared rates of MetSy with lumateperone and risperidone. Data from an open-label long-term trial of lumateperone were also evaluated.
Method
The incidence and shift in MetSy were analyzed in data pooled from 2 short-term (4 or 6 week) placebo- and active-controlled (risperidone 4mg) studies of lumateperone 42mg (Studies 005 and 302). The pooled lumateperone data were compared with data for risperidone. Data from an open-label 1-year trial (Study 303) evaluated MetSy in patients with stable schizophrenia switched from prior antipsychotic (PA) treatment to lumateperone 42mg.
Results
In the acute studies (n=256 lumateperone 42mg, n=255 risperidone 4mg), rates of MetSy were similar between groups at baseline (16% lumateperone, 19% risperidone). At the end of treatment (EOT), MetSy was less common with lumateperone than with risperidone (13% vs 25%). More lumateperone patients (46%) compared with risperidone (25%) patients improved from having MetSy at baseline to no longer meeting MetSy criteria at EOT. Conversely, more patients on risperidone than on lumateperone developed MetSy during treatment (13% vs 5%). Differences in MetSy conversion rates were driven by changes in triglycerides and glucose. In the long-term study (n=602 lumateperone 42mg), 33% of patients had MetSy at PA baseline. Thirty-six percent of patients (36%) with MetSy at PA baseline improved to no longer meeting criteria at EOT. Fewer than half that percentage shifted from not meeting MetSy criteria to having MetSy (15%).
Conclusions
In this post hoc analysis, lumateperone 42mg patients had reduced rates of MetSy compared with risperidone patients. In the long-term study, patients with MetSy on PA switched to lumateperone 42mg had a reduction in the risk of MetSy. These results suggest that lumateperone 42mg is a promising new treatment for schizophrenia with a favorable metabolic profile.
The first demonstration of laser action in ruby was made in 1960 by T. H. Maiman of Hughes Research Laboratories, USA. Many laboratories worldwide began the search for lasers using different materials, operating at different wavelengths. In the UK, academia, industry and the central laboratories took up the challenge from the earliest days to develop these systems for a broad range of applications. This historical review looks at the contribution the UK has made to the advancement of the technology, the development of systems and components and their exploitation over the last 60 years.
Cognitive and behavioral impairment are common in children living with perinatally acquired HIV (pHIV) and children exposed to HIV in utero but uninfected (HEU).
Methods
We sought to determine the prevalence of adverse behavioral symptomatology using a Thai-translated and validated version of the SNAP-IV questionnaire and assess cognitive function utilizing the Children's Color Trails Test, Delis-Kaplan Executive Function System, and the Wechsler Intelligence Scales, in our cohort of Thai adolescents (10–20 years old) with well-controlled pHIV compared to HEU and HIV-unexposed, uninfected youth. We then evaluated the interaction between HIV status, behavioral impairment, and executive function outcomes independent of demographic variables.
Results
After controlling for demographic factors of age and household income, adolescents with pHIV had higher inattentive symptomatology and poorer neuropsychological test scores compared to uninfected controls. Significant interactions were found between inattention and executive function across multiple neurocognitive tests.
Conclusions
Behavioral impairment and poor executive functioning are present in adolescents with well-controlled pHIV compared to HIV-uninfected matched peers. The SNAP-IV questionnaire may be a useful tool to identify those with attentional impairment who may benefit from further cognitive testing in resource-limited settings.
Understanding place-based contributors to health requires geographically and culturally diverse study populations, but sharing location data is a significant challenge to multisite studies. Here, we describe a standardized and reproducible method to perform geospatial analyses for multisite studies. Using census tract-level information, we created software for geocoding and geospatial data linkage that was distributed to a consortium of birth cohorts located throughout the USA. Individual sites performed geospatial linkages and returned tract-level information for 8810 children to a central site for analyses. Our generalizable approach demonstrates the feasibility of geospatial analyses across study sites to promote collaborative translational research.
This study aimed to examine the predictors of cognitive performance in patients with pediatric mild traumatic brain injury (pmTBI) and to determine whether group differences in cognitive performance on a computerized test battery could be observed between pmTBI patients and healthy controls (HC) in the sub-acute (SA) and the early chronic (EC) phases of injury.
Method:
203 pmTBI patients recruited from emergency settings and 159 age- and sex-matched HC aged 8–18 rated their ongoing post-concussive symptoms (PCS) on the Post-Concussion Symptom Inventory and completed the Cogstate brief battery in the SA (1–11 days) phase of injury. A subset (156 pmTBI patients; 144 HC) completed testing in the EC (~4 months) phase.
Results:
Within the SA phase, a group difference was only observed for the visual learning task (One-Card Learning), with pmTBI patients being less accurate relative to HC. Follow-up analyses indicated higher ongoing PCS and higher 5P clinical risk scores were significant predictors of lower One-Card Learning accuracy within SA phase, while premorbid variables (estimates of intellectual functioning, parental education, and presence of learning disabilities or attention-deficit/hyperactivity disorder) were not.
Conclusions:
The absence of group differences at EC phase is supportive of cognitive recovery by 4 months post-injury. While the severity of ongoing PCS and the 5P score were better overall predictors of cognitive performance on the Cogstate at SA relative to premorbid variables, the full regression model explained only 4.1% of the variance, highlighting the need for future work on predictors of cognitive outcomes.