Background and Purpose—: Stroke is a common long-term condition with an increasing incidence as the population ages. This study evaluates temporal changes in the prevalence of cognitive impairment after first-ever stroke stratified by sociodemography, vascular risk factors, and stroke subtypes, up to 15 years after stroke. Methods—: Data were collected between 1995 and 2010 (n=4212) from the community-based South London Stroke Register covering an inner-city multiethnic population of 271 817 inhabitants. Patients were assessed for cognitive function using Abbreviated Mental Test or Mini-Mental State Examination at the onset, 3 months, and annually thereafter. All estimates were age adjusted to the European standard. Results—: The overall prevalence of cognitive impairment 3 months after stroke and at annual follow-up remained relatively unchanged at 22% (24% [95% CI, 21.2–27.8] at 3 months; 22% [17.4–26.8] at 5 years to 21% [3.6–63.8] at 14 years). In multivariate analyses, the poststroke prevalence ratio of cognitive impairment increased with older age (2% [1–3] for each year of age), ethnicity (2.2 [1.65–2.89]-fold higher among black group) and socioeconomic status (42% [8–86] increased among manual workers). A significant, progressive trend of cognitive impairment was observed among patients with small vessel occlusion and lacunar infarction (average annual percentage change: 10% [7.9–12.8] and 2% [0.3–2.7], respectively, up to 5 years after stroke). Conclusions—: The prevalence of cognitive impairment after stroke remains persistently high over time, with variations being predominantly explained by sociodemographic characteristics. Given population growth and ageing demographics, effective preventive strategies and poststroke surveillance are needed to manage survivors with cognitive impairment.

History and severity of atopic dermatitis (AD) are risk factors for peanut allergy. Recent evidence suggests that children can become sensitized to food allergens through an impaired skin barrier. Household peanut consumption, which correlates strongly with peanut protein levels in household dust, is a risk factor for peanut allergy. We sought to assess whether environmental peanut exposure (EPE) is a risk for peanut sensitization and allergy and whether markers of an impaired skin barrier modify this risk. Peanut protein in household dust (in micrograms per gram) was assessed in highly atopic children (age, 3-15 months) recruited to the Consortium of Food Allergy Research Observational Study. History and severity of AD, peanut sensitization, and likely allergy (peanut-specific IgE, ≥5 kUA/mL) were assessed at recruitment into the Consortium of Food Allergy Research study. There was an exposure-response relationship between peanut protein levels in household dust and peanut skin prick test (SPT) sensitization and likely allergy. In the final multivariate model an increase in 4 log2 EPE units increased the odds of peanut SPT sensitization (1.71-fold; 95% CI, 1.13- to 2.59-fold; P = .01) and likely peanut allergy (PA; 2.10-fold; 95% CI, 1.20- to 3.67-fold; P < .01). The effect of EPE on peanut SPT sensitization was augmented in children with a history of AD (OR, 1.97; 95% CI, 1.26-3.09; P < .01) and augmented even further in children with a history of severe AD (OR, 2.41; 95% CI, 1.30-4.47; P < .01); the effect of EPE on PA was also augmented in children with a history of AD (OR, 2.34; 95% CI, 1.31-4.18; P < .01). Exposure to peanut antigen in dust through an impaired skin barrier in atopically inflamed skin is a plausible route for peanut SPT sensitization and PA.

Most of the peanut-sensitized children do not have clinical peanut allergy. In equivocal cases, oral food challenges (OFCs) are required. However, OFCs are laborious and not without risk; thus, a test that could accurately diagnose peanut allergy and reduce the need for OFCs is desirable. To assess the performance of basophil activation test (BAT) as a diagnostic marker for peanut allergy. Peanut-allergic (n = 43), peanut-sensitized but tolerant (n = 36) and non-peanut-sensitized nonallergic (n = 25) children underwent skin prick test (SPT) and specific IgE (sIgE) to peanut and its components. BAT was performed using flow cytometry, and its diagnostic performance was evaluated in relation to allergy versus tolerance to peanut and validated in an independent population (n = 65). BAT in peanut-allergic children showed a peanut dose-dependent upregulation of CD63 and CD203c while there was no significant response to peanut in peanut-sensitized but tolerant (P < .001) and non-peanut-sensitized nonallergic children (P < .001). BAT optimal diagnostic cutoffs showed 97% accuracy, 95% positive predictive value, and 98% negative predictive value. BAT allowed reducing the number of required OFCs by two-thirds. BAT proved particularly useful in cases in which specialists could not accurately diagnose peanut allergy with SPT and sIgE to peanut and to Arah2. Using a 2-step diagnostic approach in which BAT was performed only after equivocal SPT or Arah2-sIgE, BAT had a major effect (97% reduction) on the number of OFCs required. BAT proved to be superior to other diagnostic tests in discriminating between peanut allergy and tolerance, particularly in difficult cases, and reduced the need for OFCs.

Filaggrin (FLG) loss-of-function mutations lead to an impaired skin barrier associated with peanut allergy. Household peanut consumption is associated with peanut allergy, and peanut allergen in household dust correlates with household peanut consumption. We sought to determine whether environmental peanut exposure increases the odds of peanut allergy and whether FLG mutations modulate these odds. Exposure to peanut antigen in dust within the first year of life was measured in a population-based birth cohort. Peanut sensitization and peanut allergy (defined by using oral food challenges or component-resolved diagnostics [CRD]) were assessed at 8 and 11 years. Genotyping was performed for 6 FLG mutations. After adjustment for infantile atopic dermatitis and preceding egg skin prick test (SPT) sensitization, we found a strong and significant interaction between natural log (ln [loge]) peanut dust levels and FLG mutations on peanut sensitization and peanut allergy. Among children with FLG mutations, for each ln unit increase in the house dust peanut protein level, there was a more than 6-fold increased odds of peanut SPT sensitization, CRD sensitization, or both in children at ages 8 years, 11 years, or both and a greater than 3-fold increased odds of peanut allergy compared with odds seen in children with wild-type FLG. There was no significant effect of exposure in children without FLG mutations. In children carrying an FLG mutation, the threshold level for peanut SPT sensitization was 0.92 μg of peanut protein per gram (95% CI, 0.70-1.22 μg/g), that for CRD sensitization was 1.03 μg/g (95% CI, 0.90-1.82 μg/g), and that for peanut allergy was 1.17 μg/g (95% CI, 0.01-163.83 μg/g). Early-life environmental peanut exposure is associated with an increased risk of peanut sensitization and allergy in children who carry an FLG mutation. These data support the hypothesis that peanut allergy develops through transcutaneous sensitization in children with an impaired skin barrier.

Background: Frontotemporal lobar degeneration (FTLD) is a clinically, genetically, and pathologically heterogeneous neurodegenerative disorder. Two subtypes commonly present with a language disorder: semantic dementia (SemD) and progressive nonfluent aphasia (PNFA). Methods: Patients meeting consensus criteria for PNFA and SemD who had volumetric MRI of sufficient quality to allow cortical thickness analysis were recruited from a tertiary referral clinic: 44 (11 pathologically confirmed) patients with SemD and 32 (4 pathologically confirmed) patients with PNFA and 29 age-matched and gender-matched healthy controls were recruited. Cortical thickness analysis was performed using the Freesurfer software tools. Results: Patients with SemD had significant cortical thinning in the left temporal lobe, particularly temporal pole, entorhinal cortex, and parahippocampal, fusiform, and inferior temporal gyri. A similar but less extensive pattern of loss was seen in the right temporal lobe and (with increasing severity) also in left orbitofrontal, inferior frontal, insular, and cingulate cortices. Patients with PNFA had involvement particularly of the left superior temporal lobe, inferior frontal lobe, and insula, and (with increasing severity) other areas in the left frontal, lateral temporal, and anterior parietal lobes. Similar patterns were seen in the pathologically confirmed cases. Patterns of cortical thinning differed between groups: SemD had significantly more cortical thinning in the temporal lobes bilaterally while PNFA had significantly more thinning in the frontal and parietal lobes. Conclusions: The language variants of frontotemporal lobar degeneration have distinctive and significantly different patterns of cortical thinning. Increasing disease severity is associated with spread of cortical thinning and the pattern of spread is consistent with progression of clinical deficits.