Association of socioeconomic status with inflammatory markers: a two cohort comparison.

OBJECTIVE: To assess the association between socioeconomic status (SES) and inflammatory markers using two different European population samples. METHODS: We used data from the CoLaus (N=6412, Lausanne, Switzerland) and EPIPorto (N=1205, Porto, Portugal) studies. Education and occupational position were used as indicators of socioeconomic status (SES). High-sensitivity C-reactive protein (hs-CRP) was available for both cohorts. Interleukin-6 (IL-6) and tumour necrosis factor-α (TNF-α) were available in CoLaus; leukocyte count and fibrinogen in EPIPorto. RESULTS: We showed that low SES was significantly associated with high inflammation in both studies. We also showed that behavioural factors contributed the most to SES differences in inflammation. In both studies the larger difference between the lowest and the highest SES was observed for hs-CRP. In the Swiss sample, a linear association between education and hs-CRP persisted after adjustment for all mediating factors and confounders considered (p for linear trend <0.001). CONCLUSION: Large social differences exist in inflammatory activity, in part independently from demographic and behavioural factors, chronic conditions and medication use. SES differences in inflammation are also similar in countries with different underlying socioeconomic conditions.

Prospective comparison of clinical prognostic scores in elderly patients with pulmonary embolism.

Background: The Geneva Prognostic Score (GPS), the Pulmonary Embolism Severity Index (PESI), and its simplified version (sPESI) are well known clinical prognostic scores for pulmonary embolism (PE).Objectives: To compare the prognostic performance of these scores in elderly patients with PE. Patients/Methods: In a multicenter Swiss cohort of elderly patients with venous thromboembolism, we prospectively studied 449 patients aged ≥65 years with symptomatic PE. The outcome was 30-day overall mortality. We dichotomized patients as low- vs. higher-risk in all three scores using the following thresholds: GPS scores ≤2 vs. >2, PESI risk classes I-II vs. III-V, and sPESI scores 0 vs. ≥1. We compared 30-day mortality in low- vs. higher-risk patients and the areas under the receiver operating characteristic curve (ROC). Results: Overall, 3.8% of patients (17/449) died within 30 days. The GPS classified a greater proportion of patients as low risk (92% [413/449]) than the PESI (36.3% [163/449]) and the sPESI (39.6% [178/449]) (P<0.001 for each comparison). Low-risk patients based on the sPESI had a mortality of 0% (95% confidence interval [CI] 0-2.1%) compared to 0.6% (95% CI 0-3.4%) for low-risk patients based on the PESI and 3.4% (95% CI 1.9-5.6%) for low-risk patients based on the GPS. The areas under the ROC curves were 0.77 (95%CI 0.72-0.81), 0.76 (95% CI 0.72-0.80), and 0.71 (95% CI 0.66-0.75), respectively (P=0.47). Conclusions: In this cohort of elderly patients with PE, the GPS identified a higher proportion of patients as low-risk but the PESI and sPESI were more accurate in predicting mortality.

Multicontrast connectometry: A new tool to assess cerebellum alterations in early relapsing-remitting multiple sclerosis.

BACKGROUND: Cerebellar pathology occurs in late multiple sclerosis (MS) but little is known about cerebellar changes during early disease stages. In this study, we propose a new multicontrast "connectometry" approach to assess the structural and functional integrity of cerebellar networks and connectivity in early MS. METHODS: We used diffusion spectrum and resting-state functional MRI (rs-fMRI) to establish the structural and functional cerebellar connectomes in 28 early relapsing-remitting MS patients and 16 healthy controls (HC). We performed multicontrast "connectometry" by quantifying multiple MRI parameters along the structural tracts (generalized fractional anisotropy-GFA, T1/T2 relaxation times and magnetization transfer ratio) and functional connectivity measures. Subsequently, we assessed multivariate differences in local connections and network properties between MS and HC subjects; finally, we correlated detected alterations with lesion load, disease duration, and clinical scores. RESULTS: In MS patients, a subset of structural connections showed quantitative MRI changes suggesting loss of axonal microstructure and integrity (increased T1 and decreased GFA, P < 0.05). These alterations highly correlated with motor, memory and attention in patients, but were independent of cerebellar lesion load and disease duration. Neither network organization nor rs-fMRI abnormalities were observed at this early stage. CONCLUSION: Multicontrast cerebellar connectometry revealed subtle cerebellar alterations in MS patients, which were independent of conventional disease markers and highly correlated with patient function. Future work should assess the prognostic value of the observed damage. Hum Brain Mapp 36:1609-1619, 2015. © 2014 Wiley Periodicals, Inc.

Soft tissue artifact distribution on lower limbs during treadmill gait: Influence of skin markers' location on cluster design.

Segment poses and joint kinematics estimated from skin markers are highly affected by soft tissue artifact (STA) and its rigid motion component (STARM). While four marker-clusters could decrease the STA non-rigid motion during gait activity, other data, such as marker location or STARM patterns, would be crucial to compensate for STA in clinical gait analysis. The present study proposed 1) to devise a comprehensive average map illustrating the spatial distribution of STA for the lower limb during treadmill gait and 2) to analyze STARM from four marker-clusters assigned to areas extracted from spatial distribution. All experiments were realized using a stereophotogrammetric system to track the skin markers and a bi-plane fluoroscopic system to track the knee prosthesis. Computation of the spatial distribution of STA was realized on 19 subjects using 80 markers apposed on the lower limb. Three different areas were extracted from the distribution map of the thigh. The marker displacement reached a maximum of 24.9mm and 15.3mm in the proximal areas of thigh and shank, respectively. STARM was larger on thigh than the shank with RMS error in cluster orientations between 1.2° and 8.1°. The translation RMS errors were also large (3.0mm to 16.2mm). No marker-cluster correctly compensated for STARM. However, the coefficient of multiple correlations exhibited excellent scores between skin and bone kinematics, as well as for STARM between subjects. These correlations highlight dependencies between STARM and the kinematic components. This study provides new insights for modeling STARM for gait activity.