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In this article, we introduce a new Stata command to estimate the net survival function and the net cumulative hazard. The command includes graphic facilities. It was designed to have a similar syntax to sts, the Stata command dedicated to estimate survival and related functions. We present two examples to illustrate the use of this new command.

Two-dimensional (2D) planning on standard radiographs for total hip arthroplasty may not be sufficiently accurate to predict implant sizing or restore leg length and femoral offset, whereas 3D planning avoids magnification and projection errors. Furthermore, weightbearing measures are not available with computed tomography (CT) and leg length and offset are rarely checked postoperatively using any imaging modality. Navigation can usually achieve a surgical plan precisely, but the choice of that plan remains key, which is best guided by preoperative planning. The study objectives were therefore to (1) evaluate the accuracy of stem/cup size prediction using dedicated 3D planning software based on biplanar radiographic imaging under weightbearing and (2) compare the preplanned leg length and femoral offset with the postoperative result. This single-centre, single-surgeon prospective study consisted of a cohort of 33 patients operated on over 24 months. The routine clinical workflow consisted of preoperative biplanar weightbearing imaging, 3D surgical planning, navigated surgery to execute the plan, and postoperative biplanar imaging to verify the radiological outcomes in 3D weightbearing. 3D planning was performed with the dedicated hipEOS® planning software to determine stem and cup size and position, plus 3D anatomical and functional parameters, in particular variations in leg length and femoral offset. Component size planning accuracy was 94% (31/33) within one size for the femoral stem and 100% (33/33) within one size for the acetabular cup. There were no significant differences between planned versus implanted femoral stem size or planned versus measured changes in leg length or offset. Cup size did differ significantly, tending towards implanting one size larger when there was a difference. Biplanar radiographs plus hipEOS planning software showed good reliability for predicting implant size, leg length, and femoral offset and postoperatively provided a check on the navigated surgery. Compared to previous studies, the predictive results were better than 2D planning on conventional radiography and equal to 3D planning on CT images, with lower radiation dose, and in the weightbearing position.

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(1) Background: The progression of periodontitis, induced by polymicrobial dysbiosis, can be modified by systemic or environmental factors such as stress or anxiety affecting host response. The purpose of this study is to evaluate the potential associations between psychosocial factors scores or salivary cortisol levels with clinical periodontal parameters and bacterial environment in patients with periodontitis; (2) Methods: Subgingival microbiota was collected in two pathological and one healthy sites from thirty diseased patients (before/after scaling and root planing (SRP)) and from one healthy site from thirty control patients. Usual clinical periodontal parameters were recorded, and a saliva sample was harvested. Patients completed stress and anxiety self-assessment questionnaires. Cortisol concentrations were determined by ELISA and bacteria were identified by PCR; (3) Results: No correlation between salivary cortisol and the stress-anxiety self-declared was found (p > 0.05), but high concentrations of this molecule were associated positively and linearly with periodontal pocket depth (p = 0.04). It appeared that certain psychosocial stressors are associated with a modulation of the bacterial colonization of pockets of diseased group (before/after SRP), notably concerning Tannerella forsythia (p = 0.02), Porphyromonas gingivalis (p = 0.03), Fusobacterium nucleatum (p = 0.049) and Campylobacter rectus (p = 0.01). (4) Conclusion: This study reveals associations between bacteria colonization and psychosocial parameters in periodontitis that needs to be further investigated.

Objective This study aimed to use cluster analysis (CA) to identify different clinical phenotypes among antiphospholipid antibodies (aPL)-positive patients. Methods The Alliance for Clinical Trials and International Networking (APS ACTION) Registry includes persistently positive aPL of any isotype based on the Sydney antiphospholipid syndrome (APS) classification criteria. We performed CA on the baseline characteristics collected retrospectively at the time of the registry entry of the first 500 patients included in the registry. A total of 30 clinical data points were included in the primary CA to cover the broad spectrum of aPL-positive patients. Results A total of 497 patients from international centres were analysed, resulting in three main exclusive clusters: (a) female patients with no other autoimmune diseases but with venous thromboembolism (VTE) and triple-aPL positivity; (b) female patients with systemic lupus erythematosus, VTE, aPL nephropathy, thrombocytopaenia, haemolytic anaemia and a positive lupus anticoagulant test; and (c) older men with arterial thrombosis, heart valve disease, livedo, skin ulcers, neurological manifestations and cardiovascular disease (CVD) risk factors. Conclusions Based on our hierarchical cluster analysis, we identified different clinical phenotypes of aPL-positive patients discriminated by aPL profile, lupus or CVD risk factors. Our results, while supporting the heterogeneity of aPL-positive patients, also provide a foundation to understand disease mechanisms, create new approaches for APS classification and ultimately develop new management approaches.