Levels of sCD163 in women rheumatoid arthritis: Relationship with cardiovascular risk markers.

AIM: The soluble scavenger receptor differentiation antigen 163 (sCD163), a monocyte/macrophage activation marker, is related to cardiovascular mortality in the general population. This study aimed to evaluate their relationship between serum levels of sCD163 with cardiovascular risk indicators in rheumatoid arthritis (RA). METHODS: A cross-sectional study was performed on 80 women diagnosed with RA. The cardiovascular risks were determined using the lipid profile, metabolic syndrome, and QRISK3 calculator. For the assessment of RA activity, we evaluated the DAS28 with erythrocyte sedimentation rate (DAS28-ESR). The serum levels of sCD163 were determined by the ELISA method. Logistic regression models and receiver operating characteristics (ROC) curve were used to assess the association and predictive value of sCD163 with cardiovascular risk in RA patients. RESULTS: Levels of sCD163 were significantly higher in RA patients with high sensitivity protein C-reactive to HDL-c ratio (CHR)≥0.121 (p=0.003), total cholesterol/HDL-c ratio>7% (p=0.004), LDL-c/HDL-c ratio>3% (p=0.035), atherogenic index of plasma>0.21 (p=0.004), cardiometabolic index (CMI)≥1.70 (p=0.005), and high DAS28-ESR (p=0.004). In multivariate analysis, levels of sCD163≥1107.3ng/mL were associated with CHR≥0.121 (OR=3.43, p=0.020), CMI≥1.70 (OR=4.25, p=0.005), total cholesterol/HDL-c ratio>7% (OR=6.63, p=0.044), as well as with DAS28-ESR>3.2 (OR=8.10, p=0.008). Moreover, levels of sCD163 predicted CHR≥0.121 (AUC=0.701), cholesterol total/HDL ratio>7% (AUC=0.764), and DAS28-ESR>3.2 (AUC=0.720). CONCLUSION: Serum levels of sCD163 could be considered a surrogate of cardiovascular risk and clinical activity in RA.

Objective classification of psychomotor laparoscopic skills of surgeons based on three different approaches.

BACKGROUND: The determination of surgeons' psychomotor skills in minimally invasive surgery techniques is one of the major concerns of the programs of surgical training in several hospitals. Therefore, it is important to assess and classify objectively the level of experience of surgeons and residents during their training process. The aim of this study was to investigate three classification methods for establishing automatically the level of surgical competence of the surgeons based on their psychomotor laparoscopic skills. METHODS: A total of 43 participants, divided into an experienced surgeons group with ten experts (> 100 laparoscopic procedures performed) and non-experienced surgeons group with 24 residents and nine medical students (< 10 laparoscopic procedures performed), performed three tasks in the EndoViS training system. Motion data of the instruments were captured with a video-tracking system built into the EndoViS simulator and analyzed using 13 motion analysis parameters (MAPs). Radial basis function networks (RBFNets), K-star (K*), and random forest (RF) were used for classifying surgeons based on the MAPs' scores of all participants. The performance of the three classifiers was examined using hold-out and leave-one-out validation techniques. RESULTS: For all three tasks, the K-star method was superior in terms of accuracy and AUC in both validation techniques. The mean accuracy of the classifiers was 93.33% for K-star, 87.58% for RBFNets, and 84.85% for RF in hold-out validation, and 91.47% for K-star, 89.92% for RBFNets, and 83.72% for RF in leave-one-out cross-validation. CONCLUSIONS: The three proposed methods demonstrated high performance in the classification of laparoscopic surgeons, according to their level of psychomotor skills. Together with motion analysis and three laparoscopic tasks of the Fundamental Laparoscopic Surgery Program, these classifiers provide a means for objectively classifying surgical competence of the surgeons for existing laparoscopic box trainers.