Uric Acid Predicts Long-Term Cardiovascular Risk in Type 2 Diabetes but Does Not Mediate the Benefits of Fenofibrate: the FIELD Study

Aim To explore the relationship between baseline uric acid (UA) levels and long-term cardiovascular events in adults with type 2 diabetes (T2D) and to determine whether the cardioprotective effects of fenofibrate are partly mediated through its UA-lowering effects. Methods Data from the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial were utilized, comprising 9795 adults with T2D randomly allocated to treatment with fenofibrate or matching placebo. Plasma UA was measured before and after a 6-week, active fenofibrate run-in phase in all participants. Cox proportional hazards models were used to explore the relationships between baseline UA, pre-to-post run-in reductions in UA and long-term cardiovascular outcomes. Results Mean baseline plasma UA was 0.33 mmol/L (SD 0.08). Baseline UA was a significant predictor of long-term cardiovascular events, with every 0.1 mmol/L higher UA conferring a 21% increase in event rate (HR 1.21, 95% CI 1.13-1.29, P <.001). This remained significant after adjustment for treatment allocation, cardiovascular risk factors and renal function. The extent of UA reduction during fenofibrate run-in was also a significant predictor of long-term cardiovascular events, with every 0.1 mmol/L greater reduction conferring a 14% lower long-term risk (HR 0.86, 95% CI 0.76-0.97, P = .015). This effect was not modified by treatment allocation (P-interaction = .77). Conclusions UA is a strong independent predictor of long-term cardiovascular risk in adults with T2D. Although greater reduction in UA on fenofibrate is predictive of lower cardiovascular risk, this does not appear to mediate the cardioprotective effects of fenofibrate.Peer reviewe

Development of multi-dimensional body image scale for malaysian female adolescents

The present study was conducted to develop a Multi-dimensional Body Image Scale for Malaysian female adolescents. Data were collected among 328 female adolescents from a secondary school in Kuantan district, state of Pahang, Malaysia by using a self-administered questionnaire and anthropometric measurements. The self-administered questionnaire comprised multiple measures of body image, Eating Attitude Test (EAT-26; Garner & Garfinkel, 1979) and Rosenberg Self-esteem Inventory (Rosenberg, 1965). The 152 items from selected multiple measures of body image were examined through factor analysis and for internal consistency. Correlations between Multi-dimensional Body Image Scale and body mass index (BMI), risk of eating disorders and self-esteem were assessed for construct validity. A seven factor model of a 62-item Multi-dimensional Body Image Scale for Malaysian female adolescents with construct validity and good internal consistency was developed. The scale encompasses 1) preoccupation with thinness and dieting behavior, 2) appearance and body satisfaction, 3) body importance, 4) muscle increasing behavior, 5) extreme dieting behavior, 6) appearance importance, and 7) perception of size and shape dimensions. Besides, a multidimensional body image composite score was proposed to screen negative body image risk in female adolescents. The result found body image was correlated with BMI, risk of eating disorders and self-esteem in female adolescents. In short, the present study supports a multi-dimensional concept for body image and provides a new insight into its multi-dimensionality in Malaysian female adolescents with preliminary validity and reliability of the scale. The Multi-dimensional Body Image Scale can be used to identify female adolescents who are potentially at risk of developing body image disturbance through future intervention programs

Association between SGLT2 inhibitor treatment and diabetic ketoacidosis and mortality in people with type 2 diabetes admitted to hospital with COVID-19

   Objective  To determine the association between prescription of SGLT2 inhibitors and diabetic ketoacidosis (DKA) incidence or mortality in people with type 2 diabetes hospitalized with COVID-19.  Research Design and Methods  This was a retrospective cohort study based on secondary analysis of data from a large nationwide audit from a network of 40 centres in United Kingdom with data collection up to December 2020 that was originally designed to describe risk factors associated with adverse outcomes among people with diabetes who were admitted to hospital with COVID-19.. The primary outcome for this analysis was DKA on or during hospital admission. The secondary outcome was mortality. Crude, age-sex adjusted and multivariable logistic regression models, were used to generate odds ratios and 95% confidence intervals for people prescribed SGLT2 inhibitor compared to those not prescribed SGLT2 inhibitor.   Results  The original national audit included 3067 people with type 2 diabetes who were admitted to hospital with COVID-19, of whom 230 (7.5%) were prescribed SGLT2 inhibitors prior to hospital admission. Mean (SD) age of the overall cohort was 72 years, 62.3% were men and 34.9% were prescribed insulin. Overall, 2.8% of the total population had DKA and 35.6% people died. The adjusted odds of DKA were not significantly different between those prescribed SGLT2 inhibitors and those not (OR 0.56, 0.16-1.97). The adjusted odds of mortality associated with SGLT2 inhibitors were similar in the total study population (OR 1.13, 0.78-1.63 ), in the sub-group prescribed insulin (OR 1.02, 0.59-1.77), and in the sub-group that developed DKA (OR 0.21, 0.01-8.76).  Conclusions We demonstrate a low risk of DKA and high mortality rate in people with type 2 diabetes admitted to hospital with COVID-19 and limited power but no evidence of increased risk of DKA or in-hospital mortality associated with prescription of SGLT2 inhibitors. </p

Estimating the effectiveness of routine asymptomatic PCR testing at different frequencies for the detection of SARS-CoV-2 infections

Background Routine asymptomatic testing using RT-PCR of people who interact with vulnerable populations, such as medical staff in hospitals or care workers in care homes, has been employed to help prevent outbreaks among vulnerable populations. Although the peak sensitivity of RT-PCR can be high, the probability of detecting an infection will vary throughout the course of an infection. The effectiveness of routine asymptomatic testing will therefore depend on testing frequency and how PCR detection varies over time. Methods We fitted a Bayesian statistical model to a dataset of twice weekly PCR tests of UK healthcare workers performed by self-administered nasopharyngeal swab, regardless of symptoms. We jointly estimated times of infection and the probability of a positive PCR test over time following infection; we then compared asymptomatic testing strategies by calculating the probability that a symptomatic infection is detected before symptom onset and the probability that an asymptomatic infection is detected within 7 days of infection. Results We estimated that the probability that the PCR test detected infection peaked at 77% (54–88%) 4 days after infection, decreasing to 50% (38–65%) by 10 days after infection. Our results suggest a substantially higher probability of detecting infections 1–3 days after infection than previously published estimates. We estimated that testing every other day would detect 57% (33–76%) of symptomatic cases prior to onset and 94% (75–99%) of asymptomatic cases within 7 days if test results were returned within a day. Conclusions Our results suggest that routine asymptomatic testing can enable detection of a high proportion of infected individuals early in their infection, provided that the testing is frequent and the time from testing to notification of results is sufficiently fast

Cesarean Section, Formula Feeding, and Infant Antibiotic Exposure: Separate and Combined Impacts on Gut Microbial Changes in Later Infancy

Established during infancy, our complex gut microbial community is shaped by medical interventions and societal preferences, such as cesarean section, formula feeding, and antibiotic use. We undertook this study to apply the significance analysis of microarrays (SAM) method to quantify changes in gut microbial composition during later infancy following the most common birth and postnatal exposures affecting infant gut microbial composition. Gut microbiota of 166 full-term infants in the Canadian Healthy Infant Longitudinal Development birth cohort were profiled using 16S high-throughput gene sequencing. Infants were placed into groups according to mutually exclusive combinations of birth mode (vaginal/cesarean birth), breastfeeding status (yes/no), and antibiotic use (yes/no) by 3 months of age. Based on repeated permutations of data and adjustment for the false discovery rate, the SAM statistic identified statistically significant changes in gut microbial abundance between 3 months and 1 year of age within each infant group. We observed well-known patterns of microbial phyla succession in later infancy (declining Proteobacteria; increasing Firmicutes and Bacteroidetes) following vaginal birth, breastfeeding, and no antibiotic exposure. Genus Lactobacillus, Roseburia, and Faecalibacterium species appeared in the top 10 increases to microbial abundance in these infants. Deviations from this pattern were evident among infants with other perinatal co-exposures; notably, the largest number of microbial species with unchanged abundance was seen in gut microbiota following early cessation of breastfeeding in infants. With and without antibiotic exposure, the absence of a breast milk diet by 3 months of age following vaginal birth yielded a higher proportion of unchanged abundance of Bacteroidaceae and Enterobacteriaceae in later infancy, and a higher ratio of unchanged Enterobacteriaceae to Alcaligenaceae microbiota. Gut microbiota of infants born vaginally and exclusively formula fed became less enriched with family Veillonellaceae and Clostridiaceae, showed unchanging levels of Ruminococcaceae, and exhibited a greater decline in the Rikenellaceae/Bacteroidaceae ratio compared to their breastfed, vaginally delivered counterparts. These changes were also evident in cesarean-delivered infants to a lesser extent. The clinical relevance of these trajectories of microbial change is that they culminate in taxon-specific abundances in the gut microbiota of later infancy, which we and others have observed to be associated with food sensitization

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs