We conducted a case-control study to examine the merit of silver-coated tumour prostheses. We reviewed 85 patients with Agluna-treated (silver-coated) tumour implants treated between 2006 and 2011 and matched them with 85 control patients treated between 2001 and 2011 with identical, but uncoated, tumour prostheses. In all, 106 men and 64 women with a mean age of 42.2 years (18.4 to 90.4) were included in the study. There were 50 primary reconstructions (29.4%); 79 one-stage revisions (46.5%) and 41 two-stage revisions for infection (24.1%). The overall post-operative infection rate of the silver-coated group was 11.8% compared with 22.4% for the control group (p = 0.033, chi-square test). A total of seven of the ten infected prostheses in the silver-coated group were treated successfully with debridement, antibiotics, and implant retention compared with only six of the 19 patients (31.6%) in the control group (p = 0.048, chi-square test). Three patients in the silver-coated group (3.5%) and 13 controls (15.3%) had chronic periprosthetic infection (p = 0.009, chi-square test). The overall success rates in controlling infection by two-stage revision in the silver-coated group was 85% (17/20) compared with 57.1% (12/21) in the control group (p = 0.05, chi-square test). The Agluna-treated endoprostheses were associated with a lower rate of early periprosthetic infection. These silver-treated implants were particularly useful in two-stage revisions for infection and in those patients with incidental positive cultures at the time of implantation of the prosthesis. Debridement with antibiotic treatment and retention of the implant appeared to be more successful with silver-coated implants.

Pachydermoperiostosis, also known as Touraine-Solente-Golé syndrome/Rosenfeld-Kloepfer syndrome/primary or idiopathic Hypertrophic osteoarthropathy, is an autosomal-dominant/autosomal recessive inherited disorder with variable expression. In its complete form, it is characterized by pachyderma (thickening of the facial skin), skeletal changes (periostosis), excessive sweating (hyperhydrosis), and acropachia (digital clubbing). We report a patient with skeletal symptoms, associated with pachyderma and clubbing of fingers. Radiographs of patient showed periosteosis of distal end of long bones. We review the characteristic features of this syndrome. The patient required a close follow-up because of complications that might develop on the long-term.

Background: The solitary node in thyroid is a palpably discrete swelling within an apparently normal thyroid gland. It is usually a benign lesion but from clinical standpoint the possibility of neoplastic disease is of major concern for surgeon and patient. AS there is variability in the conclusion of various authors and there is no work about clinicopathology of solitary nodules of thyroid in our region. Present study has been designed to evaluate the epidemiology, fine needle aspiration cytology and incidence of malignancy in solitary nodule.Methods: As per exclusion and inclusion criteria 80 patients with solitary nodule of thyroid were included in this study. Various data like age, sex, family history, duration of nodule, site and size of nodule were recorded. Thyroid function test, fine needle aspiration cytology and ultrasonographic finding were recorded from case record.Results: Out of all histopathological finding of nodules follicular adenoma was most common followed by multinodular goitre (25%) and Adenomatous goitre (7.5%). Carcinoma was present in (17.5 %) and thyroiditis is 7.5% patients.Conclusions: Most of the patients were Euthyroid and benign condition was more common than malignancy. Follicular adenoma was most common among benign lesion and papillary carcinoma was more common neoplasm. Most of the patients required hemithyroidectomy.

Background: Study of factors/predictors leading to the disease severity is important. They help us for the early identification of the patients who are susceptible to develop severe form of disease. Cases with a set of unfavorable factors can be given priority attention for the management thereby it may be possible to reduce the mortality rates. Objective: The objective of this study was to study the patient-related risk factors for predicting severity of coronavirus disease 2019 (COVID-19) infection admitted to a tertiary care hospital. Methods: A hospital-based retrospective study was carried out among 305 cases of COVID-19. Hospital records of these cases were studied. Sociodemographic variables and presence of comorbidities were noted. Disease severity was classified as per the standard guidelines. It was classified as mild, moderate, and severe. Univariate and multivariate analysis was carried out. Results: Majority, i.e., 42.3% had severe disease. On univariate analysis, advanced age, coming from rural area, preexisting hypertension, being obese were significant risk factors for severe disease (P < 0.05). Those with severe disease had total risk factors score of 3.36 ± 1.68 compared to 2.48 ± 1.67 for mild or moderate disease, and this difference was statistically significant (P < 0.05). In the final model, coming from rural area and advanced age were the significant predictors of severe disease in the present study (P < 0.05). Conclusion: Advanced age and being from rural area were the significant predictors of severe disease in the present study.

Visual sentiment analysis, which studies the emotional response of humans on visual stimuli such as images and videos, has been an interesting and challenging problem. It tries to understand the high-level content of visual data. The success of current models can be attributed to the development of robust algorithms from computer vision. Most of the existing models try to solve the problem by proposing either robust features or more complex models. In particular, visual features from the whole image or video are the main proposed inputs. Little attention has been paid to local areas, which we believe is pretty relevant to human’s emotional response to the whole image. Application of image recognition to find people in images and analyze their sentiments or emotions. This project uses the CNN algorithm to perform that task. Given an image, it would search for faces, identify them, put a rectangle in their positions and describe the emotion found and emoji is displayed.