Analysis of spectrum of ovarian tumours: a study of 55 cases

Background: Malignant epithelial tumours are the most common ovarian cancers and also the most lethal gynaecological malignancies. This study was undertaken to analyse histomorphological spectrum and clinicopathological correlation of ovarian tumours.Methods: This retrospective study was done for the period of one year at Department of Pathology, New Civil Hospital, Surat, which is a tertiary health care center. Here we studied 55 cases of ovarian mass received in formalin, which were subjected to histopathological examination and immunohistochemistry as and when required.Results: In total, 55 ovarian tumour specimens were examined. Out of which 28 cases (51%) were benign, 3 cases (5%) were borderline and 24 cases (44%) were malignant. Most common histological type was surface epithelial tumours (60%) followed by germ cell tumours (13%). The commonest benign tumour was mucinous cystadenoma and commonest malignant tumour was serous adenocarcinoma. Malignancy was quite common in ovarian masses in our institute.Conclusions: Ovarian tumours are quite common in our set up and epithelial tumours are the commonest variety of ovarian tumours. The histological type of ovarian tumour correlates with the prognosis of the tumour.

A rare case of retroperitoneal leiomyosarcoma

Leiomyosarcoma, a rare malignancy of smooth muscle may arise from the retroperitoneum. They often reach a large size before diagnosis is made. Patient presents with vague symptoms, as such retroperitoneal malignancies are related to displacement of organs and obstructive phenomenon. The present paper is one of the very few case reports of retroperitoneal leiomyosarcoma which illustrates the presenting symptoms, gross and microscopic findings, treatment modalities and prognostic indicators of a 70 years old male seen at Government medical college, New Civil Hospital, Surat

Characteristic and trends of malaria in Surat district of Gujarat: a hospital based study

Background: Malaria is a major health problem and infects many individuals despite of various efforts to control it. The present study was aimed to observe characteristics of malaria, seasonal variation and prevalence of malaria in our region.Methods: This retrospective study was conducted in our institute from period of January 2012 to December 2012.  All the fever cases undergone investigations for malarial parasites were included in present study for defined time period.  All the laboratory data of the patients having fever were retrieved from the Pathology Laboratory of our institute.Results: out of total 32674 reports studied 4907(15.01%) were positive for malaria with overall Slide positivity rate and slide falciparum rate were 15.01% and 38.29% respectively. Incidence of malaria occurs throughout year with increased incidence of P. falciparum in monsoon.Conclusion: In the present study incidence of malaria was higher in monsoon in comparison to other seasons. But throughout the year no declining trends in incidence of malaria was observed. P. vivax malaria was more commonly observed in our study but incidence of P. falciparum increased in monsoon

A retrospective study of the pattern of sexually transmitted diseases in teenagers attending sexually transmitted disease clinic during a 7-year period at a tertiary care centre

Background: Adolescent period corresponds to the age group of 10-15 years. While teenage period, which corresponds to 13-19 year of age group, is the stage of psychosocial development. More and more young people are becoming sexually active in their mid-teens making them vulnerable to contracting the STDs. Adolescents especially in urban areas have favorable attitudes toward premarital and extramarital sex. Material and Methods: This is a retrospective study conducted at tertiary care center. Data regarding STD in teenagers (13-19 year) and their sexual behavior from January 2009 to December 2015 was collected from STI clinic. Result: Total number of adolescent attended STI clinic was 381,out of which 200 were male and 181 were female. Most common STD in female was VVC and in male was nodular scabies. out of 381 patients 155 male and 93 female had confessed about indulging in sexual activity.10 patients were tested positive for HIV and 11 patients were tested positive for syphilis. Conclusion: There is increasing incidence & prevalence of STDs in adolescents due to risky sexual behavior. It is essential to include sex education in teaching methods

ISSN 2347-954X (Print) Adverse Cutaneous Drug Reactions: Clinical Patterns & Its Impact on the Quality of Life. A Two Year Survey at Dermatology out Patient Clinic of Tertiary Care Hospital

Abstract: Adverse cutaneous drug reactions (ACDR) are an important clinical entity seen in dermatology outdoor patient practice and it form a major cause of patient's morbidity & mortality. Our objective was to evaluate the different clinical spectrum of ACDR in dermatology outdoor department patients & to establish the impact of ACDR on the quality of life of patients. All 110 patients, more than 16 years of age, attended the dermatology outdoor department were enrolled

Stacked Model-Based Classification of Parkinson’s Disease Patients Using Imaging Biomarker Data

Parkinson’s disease (PSD) is a neurological disorder of the brain where nigrostriatal integrity functions lead to motor and non-motor-based symptoms. Doctors can assess the patient based on the patient’s history and symptoms; however, the symptoms are similar in various neurodegenerative diseases, such as progressive supranuclear palsy (PSP), multiple system atrophy—parkinsonian type (MSA), essential tremor, and Parkinson’s tremor. Thus, sometimes it is difficult to identify a patient’s disease based on his or her symptoms. To address the issue, we have used neuroimaging biomarkers to analyze dopamine deficiency in the brains of subjects. We generated the different patterns of dopamine levels inside the brain, which identified the severity of the disease and helped us to measure the disease progression of the patients. For the classification of the subjects, we used machine learning (ML) algorithms for a multivariate classification of the subjects using neuroimaging biomarkers data. In this paper, we propose a stacked machine learning (ML)-based classification model to identify the HC and PSD subjects. In this stacked model, meta learners can learn and combine the predictions from various ML algorithms, such as K-nearest neighbor (KNN), random forest algorithm (RFA), and Gaussian naive Bayes (GANB) to achieve a high performance model. The proposed model showed 92.5% accuracy, outperforming traditional schemes