Mangumritchie7461

Given that subjective variables might reduce remission by composite DAS (CDAS), the main objectives were to explore whether RA patients with mainly tender

mainly swollen joints had differences in patient-reported outcome measures (PROMs), clinical or US assessments or in achieving remission defined by CDAS or US.

In a Nordic multicentre study, RA patients initiating tocilizumab were assessed by PROMs, clinical, laboratory and US assessments (36 joints and 4 tendons) at baseline, 4, 12 and 24 weeks. Remission was defined according to clinical disease activity index (CDAI)/Boolean or no Doppler activity present. Tender-swollen joint differences (TSJDs) were calculated. Statistics exploring changes over time/differences between groups included Wilcoxon, Mann-Whitney, Kruskal-Wallis and Spearman tests.

One hundred and ten patients were included [mean (s.d.) age 55.6 (12.1) years, RA duration 8.7 (9.5) years]. All PROMs, clinical, laboratory and US scores decreased during follow-up (

 < 0.001). During follow-up, tender joint counts were correlated primarily with PROMs [

 = 0.24-0.56 (

 < 0.05-0.001)] and swollen joint counts with US synovitis scores [

 = 0.33-0.72 (

 < 0.05-0.001)]. At 24 weeks, patients with TSJD > 0 had higher PROMs and CDAI (

 < 0.05-0.001) but lower US synovitis scores (

 < 0.05). Remission by CDAI/Boolean was seen in 26-34% and by Doppler 53%, but only 2-3% of patients with TSJD > 0 achieved CDAI/Boolean remission.

Patients with more tender than swollen joints scored higher on subjective assessments but had less US synovitis. They seldom achieved CDAS remission despite many being in Doppler remission. If patients with predominantly tender joints do not reach CDAS remission, objective assessments of inflammation should be performed.

ClinicalTrials.gov, https//clinicaltrials.gov/, NCT02046616.

ClinicalTrials.gov, https//clinicaltrials.gov/, NCT02046616.

The aim was to examine the prevalence of urate-lowering treatment (ULT) in community-dwelling adults with gout and the reasons for drug discontinuation.

Adults with gout living in the East Midlands, UK, were mailed a postal questionnaire by their general practice surgery. It enquired about demographic details, co-morbidities, number of gout flares in the previous 12 months, current ULT and the reasons for discontinuing ULT if applicable. The number (percentage), median [interquartile range (IQR)] and mean (s.d.) were used for descriptive purposes. The Mann-Whitney

test and χ

test were used for univariate analyses. STATA v.16 was used for data analysis. Statistical significance was set at

 < 0.05.

Data for 634 gout patients [89.3% men, mean (s.d.) age 64.77 (12.74) years)] were included. Of the respondents, 59.8% self-reported taking ULT currently, with the vast majority (95.6%) taking allopurinol. this website Participants self-reporting current ULT experienced fewer gout flares in the previous 12 months than those who did not self-report current ULT [median (IQR) 0 (0-2) and 1 (0-3), respectively,

 < 0.05]. One hundred and seven participants (16.9%) self-reported ULT discontinuation previously. The most commonly cited reasons for this were side-effects (29.7%), being fed up with taking tablets (19.8%) and lack of benefit from treatment or ULT-induced gout flares (19.8%). Treatment being stopped by the general practitioner without a clear reason known to the participant (15.8%) was another common report.

This study identified patient-, physician- and treatment-related barriers to long-term ULT. These should be addressed when initiating ULT and during regular review. Further research is required to confirm these findings in other populations.

This study identified patient-, physician- and treatment-related barriers to long-term ULT. These should be addressed when initiating ULT and during regular review. Further research is required to confirm these findings in other populations.[This corrects the article DOI 10.1093/cdn/nzaa087.].Studying the effects of gestational exposures to chemical mixtures on infant birth weight is inconclusive due to several challenges. One of the challenges is which statistical methods to rely on. Bayesian factor analysis (BFA), which has not been utilized for chemical mixtures, has advantages in variance reduction and model interpretation.

We analyzed data from a cohort of 384 pregnant women and their newborns using urinary biomarkers of phthalates, phenols, and organophosphate pesticides (OPs) and serum biomarkers of polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), perfluoroalkyl substances (PFAS), and organochlorine pesticides (OCPs). We examined the association between exposure to chemical mixtures and birth weight using BFA and compared with multiple linear regression (MLR) and Bayesian kernel regression models (BKMR).

For BFA, a 10-fold increase in the concentrations of PCB and PFAS mixtures was associated with an 81 g (95% confidence intervals [CI] = -132 to -31 g) and 57 g (95% CI = -105 to -10 g) reduction in birth weight, respectively. BKMR results confirmed the direction of effect. However, the 95% credible intervals all contained the null. For single-pollutant MLR, a 10-fold increases in the concentrations of multiple chemicals were associated with reduced birth weight, yet the 95% CI all contained the null. Variance inflation from MLR was apparent for models that adjusted for copollutants, resulting in less precise confidence intervals.

We demonstrated the merits of BFA on mixture analysis in terms of precision and interpretation compared with MLR and BKMR. We also identified the association between exposure to PCBs and PFAS and lower birth weight.

We demonstrated the merits of BFA on mixture analysis in terms of precision and interpretation compared with MLR and BKMR. We also identified the association between exposure to PCBs and PFAS and lower birth weight.Long-term air pollution exposure, notably fine particulate matter, is a global contributor to morbidity and mortality and a known risk factor for coronary artery disease (CAD) and myocardial infarctions (MI). Knowledge of impacts related to source-apportioned PM2.5 is limited. New modeling methods allow researchers to estimate source-specific long-term impacts on the prevalence of CAD and MI. The Catheterization Genetics (CATHGEN) cohort consists of patients who underwent a cardiac catheterization at Duke University Medical Center between 2002 and 2010. Severity of coronary blockage was determined by coronary angiography and converted into a binary indicator of clinical CAD. History of MI was extracted from medical records. Annual averages of source specific PM2.5 were estimated using an improved gas-constrained source apportionment model for North Carolina from 2002 to 2010. We tested six sources of PM2.5 mass for associations with CAD and MI using mixed effects multivariable logistic regression with a random intercept for county and multiple adjustments.