Long-term air pollution and traffic noise exposures and mild cognitive impairment in older adults : a cross-sectional analysis of the Heinz Nixdorf recall study

Background: Mild cognitive impairment (MCI) describes the intermediate state between normal cognitive aging and dementia. Adverse effects of air pollution (AP) on cognitive functions have been proposed, but investigations of simultaneous exposure to noise are scarce. Objectives: We analyzed the cross-sectional associations of long-term exposure to AP and traffic noise with overall MCI and amnestic (aMCI) and nonamnestic (naMCI) MCI. Methods: At the second examination of the population-based Heinz Nixdorf Recall study, cognitive assessment was completed in 4,086 participants who were 50–80 years old. Of these, 592 participants were diagnosed as having MCI (aMCI, n = 309; naMCI, n = 283) according to previously published criteria using five neuropsychological subtests. We assessed long-term residential concentrations for size-fractioned particulate matter (PM) and nitrogen oxides with land use regression, and for traffic noise [weighted 24-hr (LDEN) and night-time (LNIGHT) means]. Logistic regression models adjusted for individual risk factors were calculated to estimate the association of environmental exposures with MCI in single- and two-exposure models. Results: Most air pollutants and traffic noise were associated with overall MCI and aMCI. For example, an interquartile range increase in PM2.5 and a 10 A-weighted decibel [dB(A)] increase in LDEN were associated with overall MCI as follows [odds ratio (95% confidence interval)]: 1.16 (1.05, 1.27) and 1.40 (1.03, 1.91), respectively, and with aMCI as follows: 1.22 (1.08, 1.38) and 1.53 (1.05, 2.24), respectively. In two-exposure models, AP and noise associations were attenuated [e.g., for aMCI, PM2.5 1.13 (0.98, 1.30) and LDEN 1.46 (1.11, 1.92)]. Conclusions: Long-term exposures to air pollution and traffic noise were positively associated with MCI, mainly with the amnestic subtype

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase 1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age  6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score  652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc = 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N = 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in Asia and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701

Elemente der Kreislaufwirtschaft

Available from TIB Hannover: RR 4480(05) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Outcome and periprocedural time management in referred directly admitted stroke patients treated with thrombectomy

Background: After thrombectomy has shown to be effective in acute stroke patients with large vessel occlusion, the potential benefit of secondary referral for such an intervention needs to be validated. Aims: We aimed to compare consecutive stoke patients directly admitted and treated with thrombectomy at a neurointerventional centre with patients secondarily referred for such a procedure from hospitals with a stroke unit. Methods: Periprocedure times and mortality in 300 patients primarily treated in eight neurointerventional centres were compared with 343 patients referred from nine other hospitals in a prospective multicentre study of a German neurovascular network. Data on functional outcome at 3 months was available in 430 (76.4%) patients. Results: In-hospital mortality (14.8% versus 11.7%, p = 0.26) and 3 months mortality (21.9% versus 24.1%, p = 0.53) were not statistically different in both patient groups despite a significant shorter symptom to groin puncture time in directly admitted patients, which was mainly caused by a longer interfacility transfer time. We found a nonsignificant trend for better functional outcome at 3 months in directly admitted patients (modified Rankin Scale 0–2, 44.0% versus 35.7%, p = 0.08). Conclusions: Our results show that a drip-and-ship thrombectomy concept can be effectively organized in a metropolitan stroke network. Every effort should be made to speed up the emergency interfacility transfer to a neurointerventional centre in stroke patients eligible for thrombectomy after initial brain imaging

Sociodemographic data and APOE-ε4 augmentation for MRI-based detection of amnestic mild cognitive impairment using deep learning systems.

Detection and diagnosis of early and subclinical stages of Alzheimer's Disease (AD) play an essential role in the implementation of intervention and prevention strategies. Neuroimaging techniques predominantly provide insight into anatomic structure changes associated with AD. Deep learning methods have been extensively applied towards creating and evaluating models capable of differentiating between cognitively unimpaired, patients with Mild Cognitive Impairment (MCI) and AD dementia. Several published approaches apply information fusion techniques, providing ways of combining several input sources in the medical domain, which contributes to knowledge of broader and enriched quality. The aim of this paper is to fuse sociodemographic data such as age, marital status, education and gender, and genetic data (presence of an apolipoprotein E (APOE)-ε4 allele) with Magnetic Resonance Imaging (MRI) scans. This enables enriched multi-modal features, that adequately represent the MRI scan visually and is adopted for creating and modeling classification systems capable of detecting amnestic MCI (aMCI). To fully utilize the potential of deep convolutional neural networks, two extra color layers denoting contrast intensified and blurred image adaptations are virtually augmented to each MRI scan, completing the Red-Green-Blue (RGB) color channels. Deep convolutional activation features (DeCAF) are extracted from the average pooling layer of the deep learning system Inception_v3. These features from the fused MRI scans are used as visual representation for the Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN) classification model. The proposed approach is evaluated on a sub-study containing 120 participants (aMCI = 61 and cognitively unimpaired = 59) of the Heinz Nixdorf Recall (HNR) Study with a baseline model accuracy of 76%. Further evaluation was conducted on the ADNI Phase 1 dataset with 624 participants (aMCI = 397 and cognitively unimpaired = 227) with a baseline model accuracy of 66.27%. Experimental results show that the proposed approach achieves 90% accuracy and 0.90 F1-Score at classification of aMCI vs. cognitively unimpaired participants on the HNR Study dataset, and 77% accuracy and 0.83 F1-Score on the ADNI dataset

Long-term air pollution and traffic noise exposures and cognitive function:A cross-sectional analysis of the Heinz Nixdorf Recall study

Investigations of adverse effects of air pollution (AP) and ambient noise on cognitive functions are apparently scarce, and findings seem to be inconsistent. The aim of this study was to examine the associations of long-term exposure to AP and traffic noise with cognitive performance. At the second examination of the population-based Heinz Nixdorf Recall study (2006-2008), cognitive performance was evaluated in 4086 participants. Long-term residential exposure to size-specific particulate matter (PM) and nitrogen oxides (NOx) with land use regression, to and traffic noise (weighted 24-h (L-DEN) and nighttime (L-NIGHT) means), was assessed according to the European Union (EU) Directive 2002/49/EC. Multiple regression models were calculated for the relationship of environmental exposures with a global cognitive score (GCS) and in five cognitive subtests, using single- and two-exposure models. In fully adjusted models, several AP metrics were negatively associated with four of five subtests and with GCS. For example, an interquartile range increase in PM2.5 was correlated with verbal fluency, labyrinth test, and immediate and delayed verbal recall. A 10 dB(A) elevation in L-DEN and L-NIGHT was associated with GCS. Similar but not significant associations were found for the cognitive subtests. In two-exposure models including noise and air pollution simultaneously, the associations did not change markedly for air pollution, but attenuated numerically for noise. Long-term exposures to AP and traffic noise are negatively correlated with subtests related to memory and executive functions. There appears to be little evidence for mutual confounding