The role of APT imaging in gliomas grading: A systematic review and meta-analysis

Purpose: Gliomas are diagnosed and staged by conventional MRI. Although non-conventional sequences such as perfusion-weighted MRI may differentiate low-grade from high-grade gliomas, they are not reliable enough yet. The latter is of paramount importance for patient management. In this regard, we aim to evaluate the role of Amide Proton Transfer (APT) imaging in grading gliomas as a non-invasive tool to provide reliable differentiation across tumour grades. Methods: A systematic search of PubMed, Medline and Embase was conducted to identify relevant publications between 01/01/2008 and 15/09/2020. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to assess studies’ quality. A random-effects model standardized mean difference meta-analysis was performed to assess APT's ability to differentiate low-grade gliomas (LGGs) from high-grade gliomas (HGGs), WHO 2–4 grades, wild-type from mutated isocitrate dehydrogenase (IDH) gliomas, methylated from unmethylated O6-methylguanine-DNA methyltransferase (MGMT) gliomas. Area under the curve (AUC) of the Receiver Operating Characteristic (ROC) meta-analysis was employed to assess the diagnostic performance of APT. Results: 23 manuscripts met the inclusion criteria and reported the use of APT to differentiate glioma grades with histopathology as reference standard. APT-weighted signal intensity can differentiate LGGs from HGGs with an estimated size effect of (-1.61 standard deviations (SDs), p < 0.0001), grade 2 from grade 3 (-1.83 SDs, p = 0.005), grade 2 from grade 4 (-2.34 SDs, p < 0.0001) and IDH wild-type from IDH mutated (0.94 SDs, p = 0.003) gliomas. The combined AUC of 0.84 highlights the good diagnostic performance of APT-weighted imaging in differentiating LGGs from HGGs. Conclusions: APT imaging is an exciting prospect in differentiating LGGs from HGGs and with potential to predict the histopathological grade. However, more studies are required to optimize and improve its reliability

The association between plasma metabolites and sleep quality in the Southall and Brent Revisited Study (SABRE): A cross-sectional analysis

Background: Disordered metabolic processes have been associated with abnormal sleep patterns. However, the biological triggers and pathways are yet to be elucidated. / Methods: Participants were from the Southall and Brent REvisited (SABRE) cohort. Nuclear Magnetic Resonance spectroscopy provided 146 circulating plasma metabolites. Sleep questionnaires identified the presence or absence of: difficulty falling asleep (DFA), early morning waking (EMW), waking up tired (WUT) and snoring. Metabolites were compared between the sleep quality categories using the t-test, then filtered using a false discovery rate of 0.05. Generalized linear models with logit-link assessed the associations between filtered metabolites and sleep phenotypes. Adjustment was made for important demographic and health-related covariates. / Results: 2718 SABRE participants were included. After correcting for multiple testing, 3 metabolites remained for DFA, 59 for snoring and none for EMW and WUT. In fully-adjusted models, 1 standard deviation increase in serum histidine, leucine and valine associated with lower odds of DFA by 0.84-0.89 (95% confidence intervals [CIs]: 0.75-0.99). Branched chain amino acids (ORs 1.11-1.15, 95%CIs 1.01-1.26) were positively associated with snoring. Docosahexaenoic acid (DHA) (OR 0.89, 95% CI 0.82-0.96) and total cholesterol in low-density lipoprotein (LDL) (OR 0.89, 95% CI 0.82-0.96) and high-density lipoprotein (HDL) (ORs 0.90, 95% CIs 0.83-0.99) associated with lower odds of snoring. / Conclusion: Histidine, leucine and valine associated with lower odds of difficulty falling asleep, while docosahexaenoic acid and cholesterol LDL and HDL subfractions associated with lower odds of snoring. Identified metabolites could provide guidance on the metabolic pathways behind the adverse sleep quality

Childhood Bradycardia Associates With Atrioventricular Conduction Defects in Older Age: A Longitudinal Birth Cohort Study

Background: This study explored the association between childhood bradycardia and later‐life cardiac phenotype using longitudinal data from the 1946 National Survey of Health and Development (NSHD) birth cohort. // Methods and Results: Resting heart rate was recorded at 6 and 7 years of age to provide the bradycardia exposure defined as a childhood resting heart rate <75 bpm. Three outcomes were studied: (1) echocardiographic data at 60 to 64 years of age, consisting of ejection fraction, left ventricular mass index, myocardial contraction fraction index, and E/e′; (2) electrocardiographic evidence of atrioventricular or ventricular conduction defects by 60 to 64 years of age; and (3) all‐cause and cardiovascular mortality. Generalized linear models or Cox regression models were used, and adjustment was made for relevant demographic and health‐related covariates, and for multiple testing. Mixed generalized linear models and fractional polynomials were used as sensitivity analyses. One in 3 older adults with atrioventricular conduction defects had been bradycardic in childhood, with defects being serious (Mobitz type II second‐degree atrioventricular block or higher) in 12%. In fully adjusted models, childhood bradycardia was associated with 2.91 higher odds of atrioventricular conduction defects (95% CI, 1.59–5.31; P=0.0005). Associations persisted in random coefficients mixed generalized linear models (odds ratio, 2.50; 95% CI, 1.01–4.31). Fractional polynomials confirmed a linear association between the log odds of atrioventricular conduction defects at 60 to 64 years of age and resting heart rate at 7 years of age. There was no association between bradycardia in childhood and mortality outcomes or with echocardiographic parameters and ventricular conduction defects in older age. // Conclusions: Longitudinal birth cohort data indicate that childhood bradycardia trebles the odds of having atrioventricular conduction defects in older age, 88% of which are benign. In addition, it does not influence mortality or heart size and function. Future research should concentrate on identifying children at risk

The use of attention-deficit hyperactivity disorder medications in cardiac disease

Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder with onset usually in childhood characterized by inattention, impulsivity, and hyperactivity causing a functional impairment. Untreated ADHD, or treatment delay is associated with adverse outcomes and poor quality of life. Although conservative management strategies such as behavioral and psychological interventions are important, pharmacological treatment has a strong evidence base with improved outcomes. ADHD medications are broadly divided into stimulant and non-stimulant medications. Stimulant medications are generally more effective than non-stimulants. Cardiovascular safety of ADHD medication has been a matter of debate for decades. Treatment guidelines advise the careful consideration of risks and benefits in people with cardiovascular diseases such as congenital heart disease or cardiomyopathy. Although stimulants can increase systemic blood pressure and heart rate, no significant associations were found between their use and serious cardiovascular events. Concerns regarding QT effects and attendant sudden cardiac death risks deter clinicians from initiating much-needed ADHD medications in patients with heart disease. This overly cautious approach is potentially depriving low-risk individuals from significant benefits associated with timely ADHD drug treatment. This review discusses the cardiovascular risks reportedly associated with ADHD medications, the evidence base for their safe usage in persons with established cardiovascular disease, and highlights future research directions

Longitudinal birth cohort study finds that life-course frailty associates with later-life heart size and function.

A frailty index (FI) counts health deficit accumulation. Besides traditional risk factors, it is unknown whether the health deficit burden is related to the appearance of cardiovascular disease. In order to answer this question, the same multidimensional FI looking at 45-health deficits was serially calculated per participant at 4 time periods (0-16, 19-44, 45-54 and 60-64 years) using data from the 1946 Medical Research Council (MRC) British National Survey of Health and Development (NSHD)-the world's longest running longitudinal birth cohort with continuous follow-up. From these the mean and total FI for the life-course, and the step change in deficit accumulation from one time period to another was derived. Echocardiographic data at 60-64 years provided: ejection fraction (EF), left ventricular mass indexed to body surface area (LVmassi, BSA), myocardial contraction fraction indexed to BSA (MCFi) and E/e'. Generalized linear models assessed the association between FIs and echocardiographic parameters after adjustment for relevant covariates. 1375 participants were included. For each single new deficit accumulated at any one of the 4 time periods, LVmassi increased by 0.91-1.44% (p < 0.013), while MCFi decreased by 0.6-1.02% (p < 0.05). A unit increase in FI at age 45-54 and 60-64, decreased EF by 11-12% (p < 0.013). A single health deficit step change occurring between 60 and 64 years and one of the earlier time periods, translated into higher odds (2.1-78.5, p < 0.020) of elevated LV filling pressure. Thus, the accumulation of health deficits at any time period of the life-course associates with a maladaptive cardiac phenotype in older age, dominated by myocardial hypertrophy and poorer function

Meta-analysis of Penetrance and Systematic Review on Transition to Disease in Genetic Hypertrophic Cardiomyopathy

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is characterized by unexplained left ventricular hypertrophy (LVH) and is classically caused by pathogenic or likely pathogenic variants (P/LP) in genes encoding sarcomere proteins. Not all subclinical variant carriers will manifest clinically overt disease, as penetrance (proportion of G+ who develop disease) is variable, age-dependent, and not reliably predicted. METHODS: A systematic search of the literature was performed. We employed random effects generalized linear mixed model meta-analyses to contrast the cross-sectional prevalence and penetrance of sarcomere genes in two different contexts: clinically-based studies on patients and families with HCM versus population/community-based studies. Longitudinal family/clinical studies were additionally analyzed to investigate the rate of phenotypic conversion from subclinical to overt HCM during follow-up. FINDINGS: 455 full text manuscripts were assessed. In family/clinical studies, the prevalence of sarcomere variants in patients diagnosed with HCM was 34%. The penetrance across all genes in non-proband relatives carrying P/LP variants identified during cascade screening was 57% (95% confidence interval [CI] [52,63]) and the mean age of HCM diagnosis was 38 years (95% CI [36, 40]). Penetrance varied from ~32% for myosin light chain (MYL3) to ~55% for myosin binding protein C (MYBPC3), ~60% troponin T (TNNT2) and troponin I (TNNI3), and ~65% for myosin heavy chain (MYH7). Population-based genetic studies demonstrate that P/LP sarcomere variants are present in the background population, but at a low prevalence of <1%. The penetrance of HCM in incidentally identified P/LP variant carriers was also substantially lower; approximatively 11%, ranging from 0% in Atherosclerosis Risk in Communities to 18% in UK Biobank. In longitudinal family studies, the pooled phenotypic conversion across all genes was 15% over an average of ~8 years of follow up, starting from a mean age of ~16 years. However, short-term gene-specific phenotypic conversion varied between ~12% for MYBPC3 to ~23% for MYH7. CONCLUSIONS: The penetrance of P/LP variants is highly variable and influenced by currently undefined and context-dependent genetic and environmental factors. Additional longitudinal studies are needed to improve understanding of true lifetime penetrance in families and in the community, and to identify drivers of the transition from subclinical to overt HCM

Evaluating access to health and care services during lockdown by the COVID-19 survey in five UK national longitudinal studies.

OBJECTIVE: Access to health services and adequate care is influenced by sex, ethnicity, socioeconomic position (SEP) and the burden of comorbidities. Our study aimed to assess whether the COVID-19 pandemic further deepened these already existing health inequalities. DESIGN: Cross-sectional study. SETTING: Data were collected from five longitudinal age-homogenous British cohorts (born in 2000-2002, 1989-1990, 1970, 1958 and 1946). PARTICIPANTS: A web survey was sent to the cohorts. Anybody who responded to the survey was included, resulting in 14 891 eligible participants. MAIN OUTCOMES MEASURED: The survey provided data on cancelled surgical or medical appointments, and the number of care hours received in a week during the first UK COVID-19 national lockdown. INTERVENTIONS: Using binary or ordered logistic regression, we evaluated whether these outcomes differed by sex, ethnicity, SEP and having a chronic illness. Adjustment was made for study design, non-response weights, psychological distress, presence of children or adolescents in the household, COVID-19 infection, key worker status, and whether participants had received a shielding letter. Meta-analyses were performed across the cohorts, and meta-regression was used to evaluate the effect of age as a moderator. RESULTS: Women (OR 1.40, 95% CI 1.27 to 1.55) and those with a chronic illness (OR 1.84, 95% CI 1.65 to 2.05) experienced significantly more cancellations during lockdown (all p<0.0001). Ethnic minorities and those with a chronic illness required a higher number of care hours during the lockdown (both OR≈2.00, all p<0.002). SEP was not associated with cancellation or care hours. Age was not independently associated with either outcome in the meta-regression. CONCLUSION: The UK government's lockdown approach during the COVID-19 pandemic appears to have deepened existing health inequalities, impacting predominantly women, ethnic minorities and those with chronic illnesses. Public health authorities need to implement urgent policies to ensure equitable access to health and care for all in preparation for a fourthwave

Machine learning with neuroimaging data to identify autism spectrum disorder: a systematic review and meta-analysis

Purpose: Autism Spectrum Disorder (ASD) is diagnosed through observation or interview assessments, which is time-consuming, subjective, and with questionable validity and reliability. Thus, we aimed to evaluate the role of machine learning (ML) with neuroimaging data to provide a reliable classification of ASD. Methods: A systematic search of PubMed, Scopus, and Embase was conducted to identify relevant publications. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to assess the studies’ quality. A bivariate random-effects model meta-analysis was employed to evaluate the pooled sensitivity, the pooled specificity, and the diagnostic performance through the hierarchical summary receiver operating characteristic (HSROC) curve of ML with neuroimaging data in classifying ASD. Meta-regression was also performed. Results: Forty-four studies (5697 ASD and 6013 typically developing individuals [TD] in total) were included in the quantitative analysis. The pooled sensitivity for differentiating ASD from TD individuals was 86.25 95% confidence interval [CI] (81.24, 90.08), while the pooled specificity was 83.31 95% CI (78.12, 87.48) with a combined area under the HSROC (AUC) of 0.889. Higgins I2 (> 90%) and Cochran’s Q (p < 0.0001) suggest a high degree of heterogeneity. In the bivariate model meta-regression, a higher pooled specificity was observed in studies not using a brain atlas (90.91 95% CI [80.67, 96.00], p = 0.032). In addition, a greater pooled sensitivity was seen in studies recruiting both males and females (89.04 95% CI [83.84, 92.72], p = 0.021), and combining imaging modalities (94.12 95% [85.43, 97.76], p = 0.036). Conclusion: ML with neuroimaging data is an exciting prospect in detecting individuals with ASD but further studies are required to improve its reliability for usage in clinical practice

Inequality in access to health and care services during lockdown – Findings from the COVID-19 survey in five UK national longitudinal studies

Background: Access to health services and adequate care is influenced by sex, ethnicity, socio-economic position (SEP) and burden of co-morbidities. However, it is unknown whether the COVID-19 pandemic further deepened these already existing health inequalities. / Methods: Participants were from five longitudinal age-homogenous British cohorts (born in 2001, 1990, 1970, 1958 and 1946). A web and telephone-based survey provided data on cancelled surgical or medical appointments, and the number of care hours received during the UK COVID-19 national lockdown. Using binary or ordered logistic regression, we evaluated whether these outcomes differed by sex, ethnicity, SEP and having a chronic illness. Adjustment was made for study-design, non-response weights, psychological distress, presence of children or adolescents in the household, keyworker status, and whether participants had received a shielding letter. Meta-analyses were performed across the cohorts and meta-regression evaluated the effect of age as a moderator. / Findings: 14891 participants were included. Females (OR 1·40, 95% confidence interval [1·27,1·55]) and those with a chronic illness (OR 1·84 [1·65-2·05]) experienced significantly more cancellations during lockdown (all p<0·0001). Ethnic minorities and those with a chronic illness required a higher number of care hours during the lockdown (both OR ≈2·00, all p<0·002). Age was not independently associated with either outcome in meta-regression. SEP was not associated with cancellation or care hours. / Interpretation: The UK government’s lockdown approach during the COVID-19 pandemic appears to have deepened existing health inequalities, impacting predominantly females, ethnic-minorities and those with chronic illnesses. Public health authorities need to implement urgent policies to ensure equitable access to health and care for all in preparation for a second wave

The atrial and ventricular myocardial proteome of endstage lamin heart disease

Lamins A/C (encoded by LMNA gene) can lead to dilated cardiomyopathy (DCM). This pilot study sought to explore the postgenomic phenotype of end-stage lamin heart disease. Consecutive patients with end-stage lamin heart disease (LMNA-group, n = 7) and ischaemic DCM (ICM-group, n = 7) undergoing heart transplantation were prospectively enrolled. Samples were obtained from left atrium (LA), left ventricle (LV), right atrium (RA), right ventricle (RV) and interventricular septum (IVS), avoiding the infarcted myocardial segments in the ICM-group. Samples were analysed using a discovery 'shotgun' proteomics approach. We found that 990 proteins were differentially abundant between LMNA and ICM samples with the LA being most perturbed (16-fold more than the LV). Abundance of lamin A/C protein was reduced, but lamin B increased in LMNA LA/RA tissue compared to ICM, but not in LV/RV. Carbonic anhydrase 3 (CA3) was over-abundant across all LMNA tissue samples (LA, LV, RA, RV, and IVS) when compared to ICM. Transthyretin was more abundant in the LV/RV of LMNA compared to ICM, while sarcomeric proteins such as titin and cardiac alpha-cardiac myosin heavy chain were generally less abundant in RA/LA of LMNA. Protein expression profiling and enrichment analysis pointed towards sarcopenia, extracellular matrix remodeling, deficient myocardial energetics, redox imbalances, and abnormal calcium handling in LMNA samples. Compared to ICM, end-stage lamin heart disease is a biventricular but especially a biatrial disease appearing to have an abundance of lamin B, CA3 and transthyretin, potentially hinting to compensatory responses