RESUMEN
Background: Pemphigoid diseases constitute a group of autoimmune blistering disorders characterized by subepithelial blistering. The association between pemphigoid diseases and both end-stage kidney disease (ESKD) and its treatment is notable. However, there is limited evidence about the management of pemphigoid diseases in patients with ESKD. This systematic review compiled case reports and relevant studies, summarized the underlying mechanisms of pemphigoid diseases in patients with ESKD, and summarized the efficacy of various therapies. Methods: A systematic search of PubMed and Embase was performed for articles published between 1982 to June 2, 2024. Results: Fifty-three case reports and eight relevant studies were included. Triggers for pemphigoids in patients with ESKD included materials used to treat ESKD, immune dysregulation of patients with ESKD, and rejection of renal allograft. Treatment for these patients included removing triggers, as well as administering of corticosteroids, mycophenolate mofetil (MMF), tetracyclines, rituximab, methotrexate, dapsone, azathioprine, cyclosporine, intravenous immunoglobin (IVIG), plasmapheresis, and Janus kinase inhibitors. Conclusion: Removing triggers is the most effective strategy. Despite their suboptimal efficacy, corticosteroids remain the most commonly used agents in this patient population. MMF, tetracyclines, and rituximab are less used but with benefits. There are significant adverse effects associated with methotrexate treatment. Other treatment may also be beneficial and require further investigation. These findings may enable clinicians to optimize the therapeutic approach for these patients.
Asunto(s)
Fallo Renal Crónico , Penfigoide Ampolloso , Humanos , Penfigoide Ampolloso/terapia , Penfigoide Ampolloso/tratamiento farmacológico , Penfigoide Ampolloso/etiología , Penfigoide Ampolloso/inmunología , Fallo Renal Crónico/terapia , Fallo Renal Crónico/etiología , Fallo Renal Crónico/complicaciones , Inmunosupresores/uso terapéutico , Inmunosupresores/efectos adversos , Trasplante de Riñón/efectos adversosRESUMEN
Within the current process of large-scale dairy-cattle breeding, to address the problems of low recognition-accuracy and significant recognition-error associated with existing visual methods, we propose a method for recognizing the feeding behavior of dairy cows, one based on an improved RefineMask instance-segmentation model, and using high-quality detection and segmentation results to realize the recognition of the feeding behavior of dairy cows. Firstly, the input features are better extracted by incorporating the convolutional block attention module into the residual module of the feature extraction network. Secondly, an efficient channel attention module is incorporated into the neck design to achieve efficient integration of feature extraction while avoiding the surge of parameter volume computation. Subsequently, the GIoU loss function is used to increase the area of the prediction frame to optimize the convergence speed of the loss function, thus improving the regression accuracy. Finally, the logic of using mask information to recognize foraging behavior was designed, and the accurate recognition of foraging behavior was achieved according to the segmentation results of the model. We constructed, trained, and tested a cow dataset consisting of 1000 images from 50 different individual cows at peak feeding times. The method's effectiveness, robustness, and accuracy were verified by comparing it with example segmentation algorithms such as MSRCNN, Point_Rend, Cascade_Mask, and ConvNet_V2. The experimental results show that the accuracy of the improved RefineMask algorithm in recognizing the bounding box and accurately determining the segmentation mask is 98.3%, which is higher than that of the benchmark model by 0.7 percentage points; for this, the model parameter count size was 49.96 M, which meets the practical needs of local deployment. In addition, the technologies under study performed well in a variety of scenarios and adapted to various light environments; this research can provide technical support for the analysis of the relationship between cow feeding behavior and feed intake during peak feeding periods.