Humans ; Diagnosis, Differential ; Constriction, Pathologic/diagnosis* ; Bile Duct Neoplasms/diagnosis* ; Endoscopy, Digestive System

Humans ; Fabry Disease/therapy* ; Hypertrophy, Left Ventricular/diagnosis* ; Diagnosis, Differential

Humans ; Fabry Disease/therapy* ; Hypertrophy, Left Ventricular/diagnosis* ; Diagnosis, Differential

Herpes zoster is a clinical syndrome associated with reactivation of varicella zoster virus (VZV), often occurring years after VZV infection, and characterized typically by painful grouped vesicles in a dermatomal distribution. Bullous herpes zoster, an atypical presentation of herpes zoster, is a relatively rare phenomenon; to the authors’ knowledge, there have only been eight reports in worldwide literature. We present a case of a 59-year-old female with lupus nephritis who presented with multiple grouped vesicles evolving into large tender bullae filled with serosanguinous fluid on the lateral aspect of the right leg, and dorsal and medial aspects of the right foot, four days after the first dose of 1g of rituximab therapy. The diagnosis of bullous herpes zoster along L4-L5 dermatomes was made based on the clinical presentation and the presence of multinucleated giant cells on Tzanck smear. The giant bullae were drained and dressed, and the patient was treated with valacyclovir at the renally adjusted dose of 1g once a day for seven days and pregabalin 150 mg once daily. After seven days of antiviral treatment, there were no new bullae or vesicles, and the pain improved. Recognizing this atypical presentation of a common disease, especially in patients with an immunocompromised state, highlights the importance of prompt recognition and treatment.
Human ; herpes zoster ; lupus nephritis ; rituximab ; diagnosis, differential

Objective To evaluate the accuracy of different convolutional neural networks (CNN),representative deep learning models,in the differential diagnosis of ameloblastoma and odontogenic keratocyst,and subsequently compare the diagnosis results between models and oral radiologists. Methods A total of 1000 digital panoramic radiographs were retrospectively collected from the patients with ameloblastoma (500 radiographs) or odontogenic keratocyst (500 radiographs) in the Department of Oral and Maxillofacial Radiology,Peking University School of Stomatology.Eight CNN including ResNet (18,50,101),VGG (16,19),and EfficientNet (b1,b3,b5) were selected to distinguish ameloblastoma from odontogenic keratocyst.Transfer learning was employed to train 800 panoramic radiographs in the training set through 5-fold cross validation,and 200 panoramic radiographs in the test set were used for differential diagnosis.Chi square test was performed for comparing the performance among different CNN.Furthermore,7 oral radiologists (including 2 seniors and 5 juniors) made a diagnosis on the 200 panoramic radiographs in the test set,and the diagnosis results were compared between CNN and oral radiologists. Results The eight neural network models showed the diagnostic accuracy ranging from 82.50% to 87.50%,of which EfficientNet b1 had the highest accuracy of 87.50%.There was no significant difference in the diagnostic accuracy among the CNN models (P=0.998,P=0.905).The average diagnostic accuracy of oral radiologists was (70.30±5.48)%,and there was no statistical difference in the accuracy between senior and junior oral radiologists (P=0.883).The diagnostic accuracy of CNN models was higher than that of oral radiologists (P<0.001). Conclusion Deep learning CNN can realize accurate differential diagnosis between ameloblastoma and odontogenic keratocyst with panoramic radiographs,with higher diagnostic accuracy than oral radiologists.
Humans ; Ameloblastoma/diagnostic imaging* ; Deep Learning ; Diagnosis, Differential ; Radiography, Panoramic ; Retrospective Studies ; Odontogenic Cysts/diagnostic imaging* ; Odontogenic Tumors

Genetic testing has the power to identify individuals with increased predisposition to disease, allowing individuals the opportunity to make informed management, treatment and reproductive decisions. As genomic medicine continues to be integrated into aspects of everyday patient care and the indications for genetic testing continue to expand, genetic services are increasingly being offered by non-genetic clinicians. The current complexities of genetic testing highlight the need to support and ensure non-genetic professionals are adequately equipped with the knowledge and skills to provide services. We describe a series of misdiagnosed/mismanaged cases, highlighting the common pitfalls in genetic testing to identify the knowledge gaps and where education and support is needed. We highlight that education focusing on differential diagnoses, test selection and result interpretation is needed. Collaboration and communication between genetic and non-genetic clinicians and integration of genetic counsellors into different medical settings are important. This will minimise the risks and maximise the benefits of genetic testing, ensuring adverse outcomes are mitigated.
Humans ; Missed Diagnosis ; Genetic Testing ; Educational Status ; Diagnosis, Differential ; Genotype

After the first outbreak of corona virus disease 2019 (COVID-19) at the end of 2019, it has caused multiple rounds of transmission in many countries around the world. Cancer patients are mainly elderly people, and the immunosuppression state caused by the tumor itself and anti-tumor treatment, more accompanying underlying diseases, and more hospital environmental exposure leading to a higher incidence of COVID-19 infection. The proportion of severe cases after infection is high, and the mortality is high. Therefore, based on the domestic and foreign research and clinical practice, the Expert Committee of Geriatric Cancer Prevention and Treatment of Chinese Society of Clinical Oncology launched a discussion based on the characteristics of cancer patients, including the epidemiology, clinical manifestations, differential diagnosis, definition and risk factors of severe cases, diagnosis and treatment recommendations, recovery of anti-tumor treatment and vaccination recommendations. To provide the corresponding suggestions for the clinical diagnosis and treatment of such patients.
Humans ; Adult ; Aged ; COVID-19/diagnosis* ; Neoplasms/epidemiology* ; Incidence ; Disease Outbreaks ; Diagnosis, Differential ; COVID-19 Testing

Bradyarrhythmias are commonly encountered in clinical practice. While there are several electrocardiographic criteria and algorithms for tachyarrhythmias, there is no algorithm for bradyarrhythmias to the best of our knowledge. In this article, we propose a diagnostic algorithm that uses simple concepts: (1) the presence or absence of P waves, (2) the relationship between the number of P waves and QRS complexes, and (3) the regularity of time intervals (PP, PR and RR intervals). We believe this straightforward, stepwise method provides a structured and thorough approach to the wide differential diagnosis of bradyarrhythmias, and in doing so, reduces misdiagnosis and mismanagement.
Humans ; Bradycardia/therapy* ; Algorithms ; Diagnosis, Differential ; Electrocardiography

Humans ; Infant ; Biliary Atresia/diagnosis* ; Choledochal Cyst/diagnosis* ; RNA, Circular ; Diagnosis, Differential

Humans ; Histiocytosis, Sinus/diagnosis* ; Diagnosis, Differential ; Lung