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Diabetic foot ulcer is a devastating complication of diabetes mellitus and significant cause of mortality and morbidity all over the world and can be complex and costly. The development of foot ulcer in a diabetic patient has been estimated to be 19%-34% through their lifetime. The pathophysiology of diabetic foot ulcer consist of neuropathy, trauma and, in many patients, additional peripheral arterial disease. In particular, diabetic neuropathy leads to foot deformity, callus formation, and insensitivity to trauma or pressure. The standard algorithms in diabetic foot ulcer management include assessing the ulcer grade classification, surgical debridement, dressing to facilitate wound healing, off-loading, vascular assessment (status and presence of a chance for interventional vascular correction), and infection and glycemic control. Although especially surgical procedures are sometimes inevitable, they are poor predictive factors for the prognosis of diabetic foot ulcer. Different novel treatment modalities such as nonsurgical debridement agents, oxygen therapies, and negative pressure wound therapy, topical drugs, cellular bioproducts, human growth factors, energy-based therapies, and systematic therapies have been available for patients with diabetic foot ulcer. However, it is uncertain whether they are effective in terms of promoting wound healing related with a limited number of randomized controlled trials. This review aims at evaluating diabetic foot ulcer with regard to all aspects. We will also focus on conventional and novel adjunctive therapy in diabetic foot management.  相似文献   
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目的对某大型综合医疗救援船急救流程进行仿真优化救治的研究。方法根据该大型医疗救援船现有甲板舱室情况,将该船的三、四层甲板各舱室按照所配备的救治功能进行分区,并在对海上可能出现的伤情进行轻、中、重分类的同时将三种伤情的急救流程根据舱室功能优化处理。结果通过仿真手段模拟三类伤病员在治疗区域内的可视化救治流程。结论实现了救治流程的优化,为该船海上急救工作的开展提供重要的技术依据。  相似文献   
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复发性子宫内膜癌的诊断、评估、多学科联合诊疗(MDT)对选择治疗方案具有重要意义,初始治疗情况和复发情况是主要评估内容。局部复发可以行放疗或手术切除,广泛复发以化疗为主。化疗、放疗、手术是常规方式,而基于分子分型的内分泌治疗、免疫检查点抑制剂治疗及靶向治疗也有重要意义。  相似文献   
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《Diagnostic Histopathology》2022,28(11):493-500
After decades of relative stagnation lung cancer is emerging as a disease type where rapid progress is being made in diagnosis and therapy, as well as in our understanding of disease biology. Much of this progress is of immediate impact to diagnosticians, and more is likely to affect diagnostic practice in the near future. In this review we seek to briefly summarize several key areas of active research of immediate or probable imminent value to trainee and consultant pulmonary pathologists alike. We cover some major changes in tumour classification, grading, and patient stratification, as well as considering the state of the art in machine-assisted interpretation of lung cancer histology, and the use of genetically modified lung cancer models.  相似文献   
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《Saudi Dental Journal》2021,33(7):656-660
PurposeKnowledge about the most prevalent types of Kennedy classifications is of great value and will enlighten dental students, dental technicians, and practitioners regarding the treatment needs of their patients, ultimately leading to better treatment outcomes. The aim was to determine the prevalence of various Kennedy classifications among patients attending clinics at the College of Dentistry at King Saud bin Abdulaziz University for Health Sciences and King Abdulaziz Dental Center, National Guard Health Affairs, who were seeking treatment for partial edentulism.MethodsAn observational cross-sectional study was conducted by visualizing cast models for partially edentulous patients. Kennedy classification, age, gender, and treatment design were recorded from the lab request sheets that were attached to the casts in the labs at both the College of Dentistry at King Saud bin Abdulaziz University for Health Sciences and King Abdulaziz Dental Center, National Guard Health Affairs. The statistical analyses were performed with SPSS version 20.0 utilizing frequency and Pearson’s and Spearman’s correlation tests.ResultsKennedy Class I (45.0%) was the most prevalent pattern in both dental arches, followed by Class III (26.2%). Next was Class II (23.3%), while Class IV was the least prevalent (5.4%).ConclusionKennedy Class I was the most noted classification in our patient population. As age increases, there is an increased tendency toward Class I and II.  相似文献   
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In 1952, renal cell carcinomas had been divided into 2 categories—clear cell or granular cell—depending upon their cytoplasmic staining characteristics. In the following years, the inventory of renal epithelial tumors has expanded by the addition of tumors named by their architectural pattern (i.e., papillary RCC, tubulocystic RCC), anatomic location (i.e., collecting duct carcinoma, renal medullary carcinoma), associated diseases (i.e., acquired cystic disease-associated RCCs). With the extensive application of molecular diagnostic techniques, it becomes possible to detect genetic distinctions between various types of renal neoplasm and discover new entities, otherwise misdiagnosed or diagnosed as unclassified RCC. Some tumors such as ALK rearrangement-associated RCC, MiT family translocation renal carcinomas, SDH-deficient renal cancer or FH-deficient RCC, are defined by their molecular characteristics. The most recent World Health Organization (WHO) classification of renal neoplasms account for more than 50 entities and provisional entities. New entities might be included in the upcoming WHO classification. The aim of this review is to summarise and discuss the newly acquired data and evidence on the clinical, pathological, molecular features and on the prognosis of new RCC entities, which will hopefully increase the awareness and the acceptance of these entities among clinicians and improve prognostication for individual patients.  相似文献   
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AimSkin tears are traumatic wounds characterised by separation of the skin layers. Severity evaluation is important in the management of skin tears. To support the assessment and management of skin tears, this study aimed to develop an algorithm to estimate a category of the Skin Tear Audit Research classification system (STAR classification) using digital images via machine learning. This was achieved by introducing shape features representing complicated shape of the skin tears.MethodsA skin tear image was separated into small segments, and features of each segment were estimated. The segments were then classified into different classes by machine learning algorithms, namely support vector machine and random forest. Their performance in classifying wound segments and STAR categories was evaluated with 31 images using the leave-one-out cross validation.ResultsSupport vector machine showed an accuracy of 74% and 69% in classifying wound segments and STAR categories, respectively. The corresponding accuracy using random forest were 71% and 63%.ConclusionMachine learning algorithms revealed capable of classifying categories of skin tears. This could offer the potential to aid nurses in their management of skin tears, even if they are not specialised in wound care.  相似文献   
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BACKGROUND: The dynamic monitoring of immune status is crucial to the precise and individualized treatment of sepsis. In this study, we aim to introduce a model to describe and monitor the immune status of sepsis and to explore its prognostic value.  相似文献   
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