260 research outputs found

    Comparative effectiveness of treatment options for subacromial shoulder conditions:a systematic review and network meta-analysis

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    Background: There are currently many treatment options for patients with subacromial shoulder conditions (SSCs). Clinical decision-making regarding the best treatment option is often difficult. This study aims to evaluate the comparative effectiveness of treatment options for relieving pain and improving function in patients with SSCs. Methods: Eight databases [including MEDLINE, Embase, CINAHL, AMED, PEDro, Cochrane Database of Systematic Reviews and World Health Organization (WHO) International Clinical Trials Registry] were searched from inception until April 2020. Randomised clinical/controlled trials of adult patients investigating the effects of nonsurgical (e.g. corticosteroid injections, therapeutic exercise, shockwave therapy) and surgical treatment for SSCs, compared with each other, placebo, usual care or no treatment, were retrieved. Pairs of reviewers screened studies independently, quality appraised eligible studies using the Cochrane risk of bias tool, extracted and checked data for accuracy. Primary outcomes were pain and disability in the short term (⩽3 months) and long term (⩾6 months). Direct and indirect evidence of treatment effectiveness was synthesised using random-effects network meta-analysis. Results: The review identified 177 eligible trials. Summary estimates (based on 99 trials providing suitable data, 6764 patients, 20 treatment options) showed small to moderate effects for several treatments, but no significant differences on pain or function between many active treatment comparisons. The primary analysis indicated that exercise and laser therapy may provide comparative benefit in terms of both pain and function at different follow-up time-points, with larger effects found for laser in the short term at 2–6 weeks, although direct evidence was provided by one trial only, and for exercise in the longer term [standardised mean difference (SMD) 0.39, 95% confidence interval (CI) 0.18, 0.59 at 3–6 months] compared with control. Sensitivity analyses excluding studies at increased risk of bias confirmed only the comparative effects of exercise as being robust for both pain and function up until 3-month follow-up. Conclusion: Current evidence shows small to moderate effect sizes for most treatment options for SSCs. Six treatments had a high probability of being most effective, in the short term, for pain and function [acupuncture, manual therapy, exercise, exercise plus manual therapy, laser therapy and Microcurrent (MENS) (TENS)], but with low certainty for most treatment options. After accounting for risk of bias, there is evidence of moderate certainty for the comparative effects of exercise on function in patients with SSCs. Future large, high-quality pragmatic randomised trials or meta-analyses are needed to better understand whether specific subgroups of patients respond better to some treatments than others

    Risk of bias assessments in individual participant data meta-analyses of test accuracy and prediction models: a review shows improvements are needed

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    Objectives: Risk of bias assessments are important in meta-analyses of both aggregate and individual participant data (IPD). There is limited evidence on whether and how risk of bias of included studies or datasets in IPD meta-analyses (IPDMAs) is assessed. We review how risk of bias is currently assessed, reported, and incorporated in IPDMAs of test accuracy and clinical prediction model studies and provide recommendations for improvement. Study Design and Setting: We searched PubMed (January 2018–May 2020) to identify IPDMAs of test accuracy and prediction models, then elicited whether each IPDMA assessed risk of bias of included studies and, if so, how assessments were reported and subsequently incorporated into the IPDMAs. Results: Forty-nine IPDMAs were included. Nineteen of 27 (70%) test accuracy IPDMAs assessed risk of bias, compared to 5 of 22 (23%) prediction model IPDMAs. Seventeen of 19 (89%) test accuracy IPDMAs used Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2), but no tool was used consistently among prediction model IPDMAs. Of IPDMAs assessing risk of bias, 7 (37%) test accuracy IPDMAs and 1 (20%) prediction model IPDMA provided details on the information sources (e.g., the original manuscript, IPD, primary investigators) used to inform judgments, and 4 (21%) test accuracy IPDMAs and 1 (20%) prediction model IPDMA provided information or whether assessments were done before or after obtaining the IPD of the included studies or datasets. Of all included IPDMAs, only seven test accuracy IPDMAs (26%) and one prediction model IPDMA (5%) incorporated risk of bias assessments into their meta-analyses. For future IPDMA projects, we provide guidance on how to adapt tools such as Prediction model Risk Of Bias ASsessment Tool (for prediction models) and QUADAS-2 (for test accuracy) to assess risk of bias of included primary studies and their IPD. Conclusion: Risk of bias assessments and their reporting need to be improved in IPDMAs of test accuracy and, especially, prediction model studies. Using recommended tools, both before and after IPD are obtained, will address this

    Network anatomy in logopenic variant of primary progressive aphasia

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    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

    Determinants of cognitive and brain resilience to tau pathology: a longitudinal analysis

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    Mechanisms of resilience against tau pathology in individuals across the Alzheimer's disease spectrum are insufficiently understood. Longitudinal data are necessary to reveal which factors relate to preserved cognition (i.e. cognitive resilience) and brain structure (i.e. brain resilience) despite abundant tau pathology, and to clarify whether these associations are cross-sectional or longitudinal. We employed a longitudinal study design to investigate the role of several demographic, biological and brain structural factors in yielding cognitive and brain resilience to tau pathology as measured with PET. In this multicenter study, we included 366 amyloid-β-positive individuals with mild cognitive impairment or Alzheimer's disease-dementia with baseline [18F]flortaucipir-PET and longitudinal cognitive assessments. A subset (n = 200) additionally underwent longitudinal structural MRI. We used linear mixed-effects models with global cognition and cortical thickness as dependent variables to investigate determinants of cognitive resilience and brain resilience, respectively. Models assessed whether age, sex, years of education, APOE-ε4 status, intracranial volume (and cortical thickness for cognitive resilience models) modified the association of tau pathology with cognitive decline or cortical thinning. We found that the association between higher baseline tau-PET levels (quantified in a temporal meta-region of interest) and rate of cognitive decline (measured with repeated Mini-Mental State Examination) was adversely modified by older age (Stβinteraction = -0.062, P = 0.032), higher education level (Stβinteraction = -0.072, P = 0.011) and higher intracranial volume (Stβinteraction = -0.07, P = 0.016). Younger age, higher education and greater cortical thickness were associated with better cognitive performance at baseline. Greater cortical thickness was furthermore associated with slower cognitive decline independent of tau burden. Higher education also modified the negative impact of tau-PET on cortical thinning, while older age was associated with higher baseline cortical thickness and slower rate of cortical thinning independent of tau. Our analyses revealed no (cross-sectional or longitudinal) associations for sex and APOE-ε4 status on cognition and cortical thickness. In this longitudinal study of clinically impaired individuals with underlying Alzheimer's disease neuropathological changes, we identified education as the most robust determinant of both cognitive and brain resilience against tau pathology. The observed interaction with tau burden on cognitive decline suggests that education may be protective against cognitive decline and brain atrophy at lower levels of tau pathology, with a potential depletion of resilience resources with advancing pathology. Finally, we did not find major contributions of sex to brain nor cognitive resilience, suggesting that previous links between sex and resilience might be mainly driven by cross-sectional differences

    Risk of bias assessments in individual participant data meta-analyses of test accuracy and prediction models:a review shows improvements are needed

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    OBJECTIVES: Risk of bias assessments are important in meta-analyses of both aggregate and individual participant data (IPD). There is limited evidence on whether and how risk of bias of included studies or datasets in IPD meta-analyses (IPDMAs) is assessed. We review how risk of bias is currently assessed, reported, and incorporated in IPDMAs of test accuracy and clinical prediction model studies and provide recommendations for improvement.STUDY DESIGN AND SETTING: We searched PubMed (January 2018-May 2020) to identify IPDMAs of test accuracy and prediction models, then elicited whether each IPDMA assessed risk of bias of included studies and, if so, how assessments were reported and subsequently incorporated into the IPDMAs.RESULTS: Forty-nine IPDMAs were included. Nineteen of 27 (70%) test accuracy IPDMAs assessed risk of bias, compared to 5 of 22 (23%) prediction model IPDMAs. Seventeen of 19 (89%) test accuracy IPDMAs used Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2), but no tool was used consistently among prediction model IPDMAs. Of IPDMAs assessing risk of bias, 7 (37%) test accuracy IPDMAs and 1 (20%) prediction model IPDMA provided details on the information sources (e.g., the original manuscript, IPD, primary investigators) used to inform judgments, and 4 (21%) test accuracy IPDMAs and 1 (20%) prediction model IPDMA provided information or whether assessments were done before or after obtaining the IPD of the included studies or datasets. Of all included IPDMAs, only seven test accuracy IPDMAs (26%) and one prediction model IPDMA (5%) incorporated risk of bias assessments into their meta-analyses. For future IPDMA projects, we provide guidance on how to adapt tools such as Prediction model Risk Of Bias ASsessment Tool (for prediction models) and QUADAS-2 (for test accuracy) to assess risk of bias of included primary studies and their IPD.CONCLUSION: Risk of bias assessments and their reporting need to be improved in IPDMAs of test accuracy and, especially, prediction model studies. Using recommended tools, both before and after IPD are obtained, will address this.</p

    The insulin-like growth factor I receptor regulates glucose transport by astrocytes

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    Previous findings indicate that reducing brain insulin-like growth factor I receptor (IGF-IR) activity promotes ample neuroprotection. We now examined a possible action of IGF-IR on brain glucose transport to explain its wide protective activity, as energy availability is crucial for healthy tissue function. Using 18FGlucose PET we found that shRNA interference of IGF-IR in mouse somatosensory cortex significantly increased glucose uptake upon sensory stimulation. In vivo microscopy using astrocyte specific staining showed that after IGF-IR shRNA injection in somatosensory cortex, astrocytes displayed greater increases in glucose uptake as compared to astrocytes in the scramble-injected side. Further, mice with the IGF-IR knock down in astrocytes showed increased glucose uptake in somatosensory cortex upon sensory stimulation. Analysis of underlying mechanisms indicated that IGF-IR interacts with glucose transporter 1 (GLUT1), the main facilitative glucose transporter in astrocytes, through a mechanism involving interactions with the scaffolding protein GIPC and the multicargo transporter LRP1 to retain GLUT1 inside the cell. These findings identify IGF-IR as a key modulator of brain glucose metabolism through its inhibitory action on astrocytic GLUT1 activity. GLIA 201

    Plasma phosphorylated tau 217 and phosphorylated tau 181 as biomarkers in Alzheimer's disease and frontotemporal lobar degeneration: a retrospective diagnostic performance study

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    Background: Plasma tau phosphorylated at threonine 217 (p-tau217) and plasma tau phosphorylated at threonine 181 (p-tau181) are associated with Alzheimer's disease tau pathology. We compared the diagnostic value of both biomarkers in cognitively unimpaired participants and patients with a clinical diagnosis of mild cognitive impairment, Alzheimer's disease syndromes, or frontotemporal lobar degeneration (FTLD) syndromes. / Methods: In this retrospective multicohort diagnostic performance study, we analysed plasma samples, obtained from patients aged 18–99 years old who had been diagnosed with Alzheimer's disease syndromes (Alzheimer's disease dementia, logopenic variant primary progressive aphasia, or posterior cortical atrophy), FTLD syndromes (corticobasal syndrome, progressive supranuclear palsy, behavioural variant frontotemporal dementia, non-fluent variant primary progressive aphasia, or semantic variant primary progressive aphasia), or mild cognitive impairment; the participants were from the University of California San Francisco (UCSF) Memory and Aging Center, San Francisco, CA, USA, and the Advancing Research and Treatment for Frontotemporal Lobar Degeneration Consortium (ARTFL; 17 sites in the USA and two in Canada). Participants from both cohorts were carefully characterised, including assessments of CSF p-tau181, amyloid-PET or tau-PET (or both), and clinical and cognitive evaluations. Plasma p-tau181 and p-tau217 were measured using electrochemiluminescence-based assays, which differed only in the biotinylated antibody epitope specificity. Receiver operating characteristic analyses were used to determine diagnostic accuracy of both plasma markers using clinical diagnosis, neuropathological findings, and amyloid-PET and tau-PET measures as gold standards. Difference between two area under the curve (AUC) analyses were tested with the Delong test. / Findings: Data were collected from 593 participants (443 from UCSF and 150 from ARTFL, mean age 64 years [SD 13], 294 [50%] women) between July 1 and Nov 30, 2020. Plasma p-tau217 and p-tau181 were correlated (r=0·90, p<0·0001). Both p-tau217 and p-tau181 concentrations were increased in people with Alzheimer's disease syndromes (n=75, mean age 65 years [SD 10]) relative to cognitively unimpaired controls (n=118, mean age 61 years [SD 18]; AUC=0·98 [95% CI 0·95–1·00] for p-tau217, AUC=0·97 [0·94–0·99] for p-tau181; pdiff=0·31) and in pathology-confirmed Alzheimer's disease (n=15, mean age 73 years [SD 12]) versus pathologically confirmed FTLD (n=68, mean age 67 years [SD 8]; AUC=0·96 [0·92–1·00] for p-tau217, AUC=0·91 [0·82–1·00] for p-tau181; pdiff=0·22). P-tau217 outperformed p-tau181 in differentiating patients with Alzheimer's disease syndromes (n=75) from those with FTLD syndromes (n=274, mean age 67 years [SD 9]; AUC=0·93 [0·91–0·96] for p-tau217, AUC=0·91 [0·88–0·94] for p-tau181; pdiff=0·01). P-tau217 was a stronger indicator of amyloid-PET positivity (n=146, AUC=0·91 [0·88–0·94]) than was p-tau181 (n=214, AUC=0·89 [0·86–0·93]; pdiff=0·049). Tau-PET binding in the temporal cortex was more strongly associated with p-tau217 than p-tau181 (r=0·80 vs r=0·72; pdiff<0·0001, n=230). / Interpretation: Both p-tau217 and p-tau181 had excellent diagnostic performance for differentiating patients with Alzheimer's disease syndromes from other neurodegenerative disorders. There was some evidence in favour of p-tau217 compared with p-tau181 for differential diagnosis of Alzheimer's disease syndromes versus FTLD syndromes, as an indication of amyloid-PET-positivity, and for stronger correlations with tau-PET signal. Pending replication in independent, diverse, and older cohorts, plasma p-tau217 and p-tau181 could be useful screening tools to identify individuals with underlying amyloid and Alzheimer's disease tau pathology. / Funding: US National Institutes of Health, State of California Department of Health Services, Rainwater Charitable Foundation, Michael J Fox foundation, Association for Frontotemporal Degeneration, Alzheimer's Association
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