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Early-life stress (ELS) has previously been identified as a risk factor for cognitive decline, but this work has predominantly focused on clinical groups and indexed traditional cognitive domains. It, therefore, remains unclear whether ELS is related to cognitive function in healthy community-dwelling older adults, as well as whether any effects of ELS also extend to social cognition. To test each of these questions, the Childhood Trauma Questionnaire (CTQ) was administered to 484 older adults along with a comprehensive neuropsychological test battery and a well-validated test of social cognitive function. The results revealed no differences in global cognition according to overall experiences of ELS. However, a closer examination into the different ELS subscales showed that global cognition was poorer in those who had experienced physical neglect (relative to those who had not). Social cognitive function did not differ according to experiences to ELS. These results indicate that the relationship between ELS and cognition in older age may be dependent on the nature of the trauma experienced.
Mastoiditis is an otological emergency, and cross-sectional imaging has a role in the diagnosis of complications and surgical planning. Advances in imaging technology are becoming increasingly sophisticated and, by the same token, the ability to accurately interpret findings is essential.
This paper reviews common and rare complications of mastoiditis using case-led examples. A radiologist-derived systematic checklist is proposed, to assist the ENT surgeon with interpreting cross-sectional imaging in emergency mastoiditis cases when the opinion of a head and neck radiologist may be difficult to obtain.
A 16-point checklist (the ‘mastoid 16’) was used on a case-led basis to review the radiological features of both common and rare complications of mastoiditis; this is complemented with imaging examples.
Acute mastoiditis has a range of serious complications that may be amenable to treatment, once diagnosed using appropriate imaging. The proposed checklist provides a systematic approach to identifying complications of mastoiditis.
Describe the epidemiological and molecular characteristics of an outbreak of Klebsiella pneumoniae carbapenemase (KPC)–producing organisms and the novel use of a cohorting unit for its control.
A 566-room academic teaching facility in Milwaukee, Wisconsin.
Solid-organ transplant recipients.
Infection control bundles were used throughout the time of observation. All KPC cases were intermittently housed in a cohorting unit with dedicated nurses and nursing aids. The rooms used in the cohorting unit had anterooms where clean supplies and linens were placed. Spread of KPC-producing organisms was determined using rectal surveillance cultures on admission and weekly thereafter among all consecutive patients admitted to the involved units. KPC-positive strains underwent pulsed-field gel electrophoresis and whole-genome sequencing.
A total of 8 KPC cases (5 identified by surveillance) were identified from April 2016 to April 2017. After the index patient, 3 patients acquired KPC-producing organisms despite implementation of an infection control bundle. This prompted the use of a cohorting unit, which immediately halted transmission, and the single remaining KPC case was transferred out of the cohorting unit. However, additional KPC cases were identified within 2 months. Once the cohorting unit was reopened, no additional KPC cases occurred. The KPC-positive species identified during this outbreak included Klebsiella pneumoniae, Enterobacter cloacae complex, and Escherichia coli. blaKPC was identified on at least 2 plasmid backbones.
A complex KPC outbreak involving both clonal and plasmid-mediated dissemination was controlled using weekly surveillances and a cohorting unit.
Colorectal cancer (CRC) is the third most common cancer globally. CRC risk is increased by obesity, and by its lifestyle determinants notably physical inactivity and poor nutrition. Obesity results in increased inflammation and oxidative stress which cause genomic damage and contribute to mitochondrial dysregulation and CRC risk. The mitochondrial dysfunction associated with obesity includes abnormal mitochondrial size, morphology and reduced autophagy, mitochondrial biogenesis and expression of key mitochondrial regulators. Although there is strong evidence that increased adiposity increases CRC risk, evidence for the effects of intentional weight loss on CRC risk is much more limited. In model systems, energy depletion leads to enhanced mitochondrial integrity, capacity, function and biogenesis but the effects of obesity and weight loss on mitochondria in the human colon are not known. We are using weight loss following bariatric surgery to investigate the effects of altered adiposity on mitochondrial structure and function in human colonocytes. In summary, there is strong and consistent evidence in model systems and more limited evidence in human subjects that over-feeding and/or obesity result in mitochondrial dysfunction and that weight loss might mitigate or reverse some of these effects.
Bowel cancer risk is strongly influenced by lifestyle factors including diet and physical activity. Several studies have investigated the effects of adherence to the World Cancer Research Fund (WCRF)/American Institute for Cancer Research (AICR) cancer prevention recommendations on outcomes such as all-cause and cancer-specific mortality, but the relationships with molecular mechanisms that underlie the effects on bowel cancer risk are unknown. This study aimed to investigate the relationships between adherence to the WCRF/AICR cancer prevention recommendations and wingless/integrated (WNT)-pathway-related markers of bowel cancer risk, including the expression of WNT pathway genes and regulatory microRNA (miRNA), secreted frizzled-related protein 1 (SFRP1) methylation and colonic crypt proliferative state in colorectal mucosal biopsies. Dietary and lifestyle data from seventy-five healthy participants recruited as part of the DISC Study were used. A scoring system was devised including seven of the cancer prevention recommendations and smoking status. The effects of total adherence score and scores for individual recommendations on the measured outcomes were assessed using Spearman’s rank correlation analysis and unpaired t tests, respectively. Total adherence score correlated negatively with expression of Myc proto-oncogene (c-MYC) (P=0·039) and WNT11 (P=0·025), and high adherers had significantly reduced expression of cyclin D1 (CCND1) (P=0·042), WNT11 (P=0·012) and c-MYC (P=0·048). Expression of axis inhibition protein 2 (AXIN2), glycogen synthase kinase (GSK3β), catenin β1 (CTNNB1) and WNT11 and of the oncogenic miRNA miR-17 and colonic crypt kinetics correlated significantly with scores for individual recommendations, including body fatness, red meat intake, plant food intake and smoking status. The findings from this study provide evidence for positive effects of adherence to the WCRF/AICR cancer prevention recommendations on WNT-pathway-related markers of bowel cancer risk.
n-3 Fatty acids are associated with better cardiovascular and cognitive health. However, the concentration of EPA, DPA and DHA in different plasma lipid pools differs and factors influencing this heterogeneity are poorly understood. Our aim was to evaluate the association of oily fish intake, sex, age, BMI and APOE genotype with concentrations of EPA, DPA and DHA in plasma phosphatidylcholine (PC), NEFA, cholesteryl esters (CE) and TAG. Healthy adults (148 male, 158 female, age 20–71 years) were recruited according to APOE genotype, sex and age. The fatty acid composition was determined by GC. Oily fish intake was positively associated with EPA in PC, CE and TAG, DPA in TAG, and DHA in all fractions (P≤0·008). There was a positive association between age and EPA in PC, CE and TAG, DPA in NEFA and CE, and DHA in PC and CE (P≤0·034). DPA was higher in TAG in males than females (P<0·001). There was a positive association between BMI and DPA and DHA in TAG (P<0·006 and 0·02, respectively). APOE genotype×sex interactions were observed: the APOE4 allele associated with higher EPA in males (P=0·002), and there was also evidence for higher DPA and DHA (P≤0·032). In conclusion, EPA, DPA and DHA in plasma lipids are associated with oily fish intake, sex, age, BMI and APOE genotype. Such insights may be used to better understand the link between plasma fatty acid profiles and dietary exposure and may influence intake recommendations across population subgroups.
We hypothesized that a computerized clinical decision support tool for Clostridium difficile testing would reduce unnecessary inpatient tests, resulting in fewer laboratory-identified events. Census-adjusted interrupted time-series analyses demonstrated significant reductions of 41% fewer tests and 31% fewer hospital-onset C. difficile infection laboratory-identified events following this intervention.
We sought to evaluate the role healthcare providers play in carbapenem-resistant Enterobacteriaceae (CRE) acquisition among hospitalized patients.
A 1:4 case-control study with incidence density sampling.
Academic healthcare center with regular CRE perirectal screening in high-risk units.
We included case patients with ≥1 negative CRE test followed by positive culture with a length of stay (LOS) >9 days. For controls, we included patients with ≥2 negative CRE tests and assignment to the same unit set as case patients with a LOS >9 days.
Controls were time-matched to each case patient. Case exposure was evaluated between days 2 and 9 before positive culture and control evaluation was based on maximizing overlap with the case window. Exposure sources were all CRE-colonized or -infected patients. Nonphysician providers were compared between study patients and sources during their evaluation windows. Dichotomous and continuous exposures were developed from the number of source-shared providers and were used in univariate and multivariate regression.
In total, 121 cases and 484 controls were included. Multivariate analysis showed odds of dichotomous exposure (≥1 source-shared provider) of 2.27 (95% confidence interval [CI], 1.25–4.15; P=.006) for case patients compared to controls. Multivariate continuous exposure showed odds of 1.02 (95% CI, 1.01–1.03; P=.009) for case patients compared to controls.
Patients who acquire CRE during hospitalization are more likely to receive care from a provider caring for a patient with CRE than those patients who do not acquire CRE. These data support the importance of hand hygiene and cohorting measures for CRE patients to reduce transmission risk.
Traditionally, personalised nutrition was delivered at an individual level. However, the concept of delivering tailored dietary advice at a group level through the identification of metabotypes or groups of metabolically similar individuals has emerged. Although this approach to personalised nutrition looks promising, further work is needed to examine this concept across a wider population group. Therefore, the objectives of this study are to: (1) identify metabotypes in a European population and (2) develop targeted dietary advice solutions for these metabotypes. Using data from the Food4Me study (n 1607), k-means cluster analysis revealed the presence of three metabolically distinct clusters based on twenty-seven metabolic markers including cholesterol, individual fatty acids and carotenoids. Cluster 2 was identified as a metabolically healthy metabotype as these individuals had the highest Omega-3 Index (6·56 (sd 1·29) %), carotenoids (2·15 (sd 0·71) µm) and lowest total saturated fat levels. On the basis of its fatty acid profile, cluster 1 was characterised as a metabolically unhealthy cluster. Targeted dietary advice solutions were developed per cluster using a decision tree approach. Testing of the approach was performed by comparison with the personalised dietary advice, delivered by nutritionists to Food4Me study participants (n 180). Excellent agreement was observed between the targeted and individualised approaches with an average match of 82 % at the level of delivery of the same dietary message. Future work should ascertain whether this proposed method could be utilised in a healthcare setting, for the rapid and efficient delivery of tailored dietary advice solutions.
Individual response to dietary interventions can be highly variable. The phenotypic characteristics of those who will respond positively to personalised dietary advice are largely unknown. The objective of this study was to compare the phenotypic profiles of differential responders to personalised dietary intervention, with a focus on total circulating cholesterol. Subjects from the Food4Me multi-centre study were classified as responders or non-responders to dietary advice on the basis of the change in cholesterol level from baseline to month 6, with lower and upper quartiles defined as responder and non-responder groups, respectively. There were no significant differences between demographic and anthropometric profiles of the groups. Furthermore, with the exception of alcohol, there was no significant difference in reported dietary intake, at baseline. However, there were marked differences in baseline fatty acid profiles. The responder group had significantly higher levels of stearic acid (18 : 0, P=0·034) and lower levels of palmitic acid (16 : 0, P=0·009). Total MUFA (P=0·016) and total PUFA (P=0·008) also differed between the groups. In a step-wise logistic regression model, age, baseline total cholesterol, glucose, five fatty acids and alcohol intakes were selected as factors that successfully discriminated responders from non-responders, with sensitivity of 82 % and specificity of 83 %. The successful delivery of personalised dietary advice may depend on our ability to identify phenotypes that are responsive. The results demonstrate the potential use of metabolic profiles in identifying response to an intervention and could play an important role in the development of precision nutrition.
To characterise clusters of individuals based on adherence to dietary recommendations and to determine whether changes in Healthy Eating Index (HEI) scores in response to a personalised nutrition (PN) intervention varied between clusters.
Food4Me study participants were clustered according to whether their baseline dietary intakes met European dietary recommendations. Changes in HEI scores between baseline and month 6 were compared between clusters and stratified by whether individuals received generalised or PN advice.
Individuals in cluster 1 (C1) met all recommended intakes except for red meat, those in cluster 2 (C2) met two recommendations, and those in cluster 3 (C3) and cluster 4 (C4) met one recommendation each. C1 had higher intakes of white fish, beans and lentils and low-fat dairy products and lower percentage energy intake from SFA (P<0·05). C2 consumed less chips and pizza and fried foods than C3 and C4 (P<0·05). C1 were lighter, had lower BMI and waist circumference than C3 and were more physically active than C4 (P<0·05). More individuals in C4 were smokers and wanted to lose weight than in C1 (P<0·05). Individuals who received PN advice in C4 reported greater improvements in HEI compared with C3 and C1 (P<0·05).
The cluster where the fewest recommendations were met (C4) reported greater improvements in HEI following a 6-month trial of PN whereas there was no difference between clusters for those randomised to the Control, non-personalised dietary intervention.
To characterise participants who dropped out of the Food4Me Proof-of-Principle study.
The Food4Me study was an Internet-based, 6-month, four-arm, randomised controlled trial. The control group received generalised dietary and lifestyle recommendations, whereas participants randomised to three different levels of personalised nutrition (PN) received advice based on dietary, phenotypic and/or genotypic data, respectively (with either more or less frequent feedback).
Seven recruitment sites: UK, Ireland, The Netherlands, Germany, Spain, Poland and Greece.
Adults aged 18–79 years (n 1607).
A total of 337 (21 %) participants dropped out during the intervention. At baseline, dropouts had higher BMI (0·5 kg/m2; P<0·001). Attrition did not differ significantly between individuals receiving generalised dietary guidelines (Control) and those randomised to PN. Participants were more likely to drop out (OR; 95 % CI) if they received more frequent feedback (1·81; 1·36, 2·41; P<0·001), were female (1·38; 1·06, 1·78; P=0·015), less than 45 years old (2·57; 1·95, 3·39; P<0·001) and obese (2·25; 1·47, 3·43; P<0·001). Attrition was more likely in participants who reported an interest in losing weight (1·53; 1·19, 1·97; P<0·001) or skipping meals (1·75; 1·16, 2·65; P=0·008), and less likely if participants claimed to eat healthily frequently (0·62; 0·45, 0·86; P=0·003).
Attrition did not differ between participants receiving generalised or PN advice but more frequent feedback was related to attrition for those randomised to PN interventions. Better strategies are required to minimise dropouts among younger and obese individuals participating in PN interventions and more frequent feedback may be an unnecessary burden.
A number of socio-economic, biological and lifestyle characteristics change with advancing age and place very old adults at increased risk of micronutrient deficiencies. The aim of this study was to assess vitamin and mineral intakes and respective food sources in 793 75-year-olds (302 men and 491 women) in the North-East of England, participating in the Newcastle 85+ Study. Micronutrient intakes were estimated using a multiple-pass recall tool (2×24 h recalls). Determinants of micronutrient intake were assessed with multinomial logistic regression. Median vitamin D, Ca and Mg intakes were 2·0 (interquartile range (IQR) 1·2–6·5) µg/d, 731 (IQR 554–916) mg/d and 215 (IQR 166–266) mg/d, respectively. Fe intake was 8·7 (IQR 6·7–11·6) mg/d, and Se intake was 39·0 (IQR 27·3–55·5) µg/d. Cereals and cereal products were the top contributors to intakes of folate (31·5 %), Fe (49·2 %) and Se (46·7 %) and the second highest contributors to intakes of vitamin D (23·8 %), Ca (27·5 %) and K (15·8 %). More than 95 % (n 756) of the participants had vitamin D intakes below the UK’s Reference Nutrient Intake (10 µg/d). In all, >20 % of the participants were below the Lower Reference Nutrient Intake for Mg (n 175), K (n 238) and Se (n 418) (comparisons with dietary reference values (DRV) do not include supplements). As most DRV are not age specific and have been extrapolated from younger populations, results should be interpreted with caution. Participants with higher education, from higher social class and who were more physically active had more nutrient-dense diets. More studies are needed to inform the development of age-specific DRV for micronutrients for the very old.
Very old people (referred to as those aged 85 years and over) are the fastest growing age segment of many Western societies owing to the steady rise of life expectancy and decrease in later life mortality. In the UK, there are now more than 1·5 million very old people (2·5 % of total population) and the number is projected to rise to 3·3 million or 5 % over the next 20 years. Reduced mobility and independence, financial constraints, higher rates of hospitalisation, chronic diseases and disabilities, changes in body composition, taste perception, digestion and absorption of food all potentially influence either nutrient intake or needs at this stage of life. The nutritional needs of the very old have been identified as a research priority by the British Nutrition Foundation's Task Force report, Healthy Ageing: The Role of Nutrition and Lifestyle. However, very little is known about the dietary habits and nutritional status of the very old. The Newcastle 85+ study, a cohort of more than 1000 85-year olds from the North East of England and the Life and Living in Advanced Age study (New Zealand), a bicultural cohort study of advanced ageing of more than 900 participants from the Bay of Plenty and Rotorua regions of New Zealand are two unique cohort studies of ageing, which aim to assess the spectrum of health in the very old as well as examine the associations of health trajectories and outcomes with biological, clinical and social factors as each cohort ages. The nutrition domain included in both studies will help to fill the evidence gap by identifying eating patterns, and measures of nutritional status associated with better, or worse, health and wellbeing. This review will explore some of this ongoing work.
Food and nutrient intake data are scarce in very old adults (85 years and older) – one of the fastest growing age segments of Western societies, including the UK. Our primary objective was to assess energy and macronutrient intakes and respective food sources in 793 85-year-olds (302 men and 491 women) living in North-East England and participating in the Newcastle 85+ cohort Study. Dietary information was collected using a repeated multiple-pass recall (2×24 h recalls). Energy, macronutrient and NSP intakes were estimated, and the contribution (%) of food groups to nutrient intake was calculated. The median energy intake was 6·65 (interquartile ranges (IQR) 5·49–8·16) MJ/d – 46·8 % was from carbohydrates, 36·8 % from fats and 15·7 % from proteins. NSP intake was 10·2 g/d (IQR 7·3–13·7). NSP intake was higher in non-institutionalised, more educated, from higher social class and more physically active 85-year-olds. Cereals and cereal products were the top contributors to intakes of energy and most macronutrients (carbohydrates, non-milk extrinsic sugars, NSP and fat), followed by meat and meat products. The median intakes of energy and NSP were much lower than the estimated average requirement for energy (9·6 MJ/d for men and 7·7 MJ/d for women) and the dietary reference value (DRV) for NSP (≥18 g/d). The median SFA intake was higher than the DRV (≤11 % of dietary energy). This study highlights the paucity of data on dietary intake and the uncertainties about DRV for this age group.
Clinical research studies of behavioral variant frontotemporal dementia (bvFTD) often use Alzheimer disease (AD) as a comparison group for control of dementia variables, using tests of cognitive function to match the groups. These two dementia syndromes, however, are very different in clinical manifestations, and the comparable severity of these dementias may not be reflected by commonly used cognitive scales such as the Mini-Mental State Examination (MMSE).
We evaluated different measures of dementia severity and symptoms among 20 people with bvFTD compared to 24 with early-onset AD.
Despite similar ages, disease-duration, education, and cognitive performance on two tests of cognitive function, the MMSE and the Montreal Cognitive Assessment (MoCA), the bvFTD participants, compared to the AD participants, were significantly more impaired on other measures of disease severity, including function (Functional Assessment Questionnaire (FAQ)), neuropsychiatric symptoms (Neuropsychiatric Inventory (NPI)), and global dementia stage (Clinical Dementia Rating Scales (CDRs)). However, when we adjusted for the frontotemporal lobar degeneration-CDR (FTLD-CDR) in the analyses, the two dementia groups were comparable across all measures despite significant differences on the cognitive scales.
We found tests of cognitive functions (MMSE and MoCA) to be insufficient measures for ensuring comparability between bvFTD and AD groups. In clinical studies, the FTLD-CDR, which includes additional language and behavior items, may be a better overall way to match bvFTD and AD groups on dementia severity.