Browsing by Author "Subhajit Das"

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Floatation of decalcified bone marrow core biopsy - A clue to marrow hypocellularity
(Journal of Clinical and Diagnostic Research, 2014) Vijai Tilak; Subhajit Das; Gyan Prakash Singh
Background: Examination of bone marrow plays a pivotal role in the practice of haematology. It can be evaluated by three ways - bone marrow aspiration smears (BMA), bone marrow touch imprints (BMI) and bone marrow biopsy (BMB). BMB sections are considered to be the gold standard for assessing overall marrow cellularity.; Aim and objective: To evaluate the correlation, if any, between bone marrow cellularity and floatation pattern of the core biopsy specimen, after proper decalcification.; Setting and design: This study was carried out in the Department of Pathology, Institute of Medical Sciences, Varanasi over a period of 26 months.; Materials and methods: Specimens of BMA, BMI and BMB were collected from 182 cases. The core biopsy specimens were fixed in 10% buffered formalin for 24 hours, and were decalcified in 5% formic acid for 12 hours. The properly decalcified core biopsy samples were then put into adequate-sized container filled with 10% buffered formalin, and floatation pattern was documented.; Statistical analysis: All the observations were evaluated using simple and basic statistical tools, i.e. sensitivity, specificity, positive predictive value. Chi square test was applied for obtaining statistical correlation i.e. P-value.; Results: Out of 182 core biopsy specimens, 32.4% (n=59) floated, while rests sank. Out of the 59 floating core biopsies, 57 were hypocellular. 7 core biopsies, among 123 specimens that sank, were hypocellular. The sensitivity and specificity of floatation pattern for hypocellular marrow were 89.2% and 99.1%, respectively. A strong correlation (p-value <0.001) between the floatation pattern and bone marrow cellularity was obtained.; Conclusion: Assessment of floatation pattern of properly decalcified marrow core specimen is reliable for assessing marrow hypocellularity. © 2014, Journal of Clinical and Diagnostic Research. All right reserved.
Prediction of hepatitis-C virus using statistical learning models
(BioMed Central Ltd, 2025) Shalini Kumari; Subhajit Das; Prashant Kumar Sonker; Agni Saroj; Mukesh Sunil Kumar
The hepatitis-c virus (HCV) is a viral infection that targets the liver and has emerged as a significant global health concern. This study investigates the classification of HCV patients by identifying the potential factors crucial for the progression and early detection of HCV. The study includes dataset of 615 HCV patients from the UCI Machine Learning Repository for illustrative purposes and analyzed it through machine learning models such as naive Bayes (NB), random forest (RF), support vector machine (SVM), logistic regression (LR), decision trees (DT), and artificial neural network (ANN). The models were evaluated using various performance metrics, and a comparative analysis using non-parametric tests was conducted to evaluate the statistical significance of the model. The empirical findings show that the RF model achieved the highest performance, with an accuracy of 96.71% with Brier score (BS) of 0.035 and Matthews correlation coefficient (MCC) of 0.849, an accuracy of 96.45% with BS of 0.031 and MCC of 0.837 and an accuracy 97.41% with BS of 0.026 and MCC of 0.947 when evaluated using all features, using selected features, and selected features with the application of the synthetic minority oversampling technique (SMOTE). The analytical methods have improved the overall predictive accuracy for HCV infection and will aid in the early identification of the disease. As a result, patients can be treated at the earliest possible stage, thereby increasing the number of lives saved. © The Author(s) 2025.
Psoriasis and metabolic syndrome: Co-incidence or correlation
(Wolters Kluwer Medknow Publications, 2016) Subhajit Das; Anupam Manna; Nehal Ahmad; Debjit Banerjee; Soumit Mondal; Pankaj Tayal
Background: Psoriasis is an immune-mediated chronic skin disease having effects on other organs. It has been linked to diabetes mellitus, hypertension, obesity, and dyslipidemia. All of these components ultimately increase the risk of metabolic syndrome and cardiovascular morbidities. Several studies have been done in the western world to identify the presence of metabolic syndrome (or its components) in psoriatic patients. Aims and Objectives: Our study had been done with the objective of identifying the prevalence of metabolic syndrome in psoriatics in comparison to normal population. Materials and Methods: The study was an institution-based case-control study. Subjects were recruited after obtaining informed consent. Cases of psoriasis were diagnosed clinically, and unrelated healthy volunteers served as controls. Inclusion criteria for cases were patients of clinically diagnosed psoriasis without any coexistent immune-suppressed conditions such as HIV, malignancy, or any other physiological conditions such as pregnancy or lactation that might influence metabolic syndrome. Smokers and alcoholics were also excluded from the study. Metabolic syndrome was defined by Adult treatment panel III criteria. Statistical Analysis: Descriptive statistics were expressed as range, mean ± standard deviation, frequencies (number of cases), and whichever was appropriate. For analytical statistics, numerical data were analyzed using t-test or ANOVA test, and for categorical data, Chi-square and Fischer's exact test were used. P ≤ 0.05 was considered as statistically significant. Results: Abdominal obesity (odds ratio [OR] = 2.6), hypertension (OR = 2.2), hyperglycemia (OR = 2.8), dyslipidemia (OR = 2.9), and metabolic syndrome (OR = 2.6) are associated with psoriasis. Conclusion: Psoriatic patients have an increased risk of developing abdominal obesity, hypertension, hyperglycemia, and dyslipidemia in comparison to general population. All these contribute to higher preponderance to metabolic syndrome. © 2016 Medical Journal of Dr. D.Y. Patil University
Value of bone marrow imprint smears in early diagnosis of bone marrow pathologies
(Journal of Clinical and Diagnostic Research, 2014) Vijai Tilak; Subhajit Das; Soobashchan Bundhun
Background: Examination of bone marrow plays a pivotal role in the practice of haematology. It can be evaluated by three ways–bone marrow aspiration (BMA), bone marrow touch imprints (BMI) and bone marrow biopsy (BMBx).; Aim and Objective: To study the efficacy and reliability of BMI smears in comparison to BMA smears, in making a diagnosis of diseases involving bone marrow.; Setting and Designs: This study was carried out in the Department of Pathology, Institute of Medical Sciences, Varanasi over a period of 26 months.; Materials and Methods: A total number of 182 cases, with their BMA, BMI and BMBx samples (from each and every case), were evaluated and their findings even compared.; Statistical Analysis: All the observations were evaluated using simple and basic statistical tool, i.e. percentage.; Results: The cellularity or cell density on BMI correlated with the cellularity of BMBx in 78.6% cases, which was higher than the value observed with BMA smears (71.4%). The spreading quality was better and cytological details were better appreciated in BMI as compared to BMA. Also, the presence of lymphoglandular bodies and particles on BMI were additive diagnostic clues. All of those findings were reflected in the higher diagnostic accuracy of BMI than BMA.; Conclusion: BMI should be a standard practice and be considered as an early and reliable diagnostic tool for evaluating bone marrow pathologies. © 2014, Journal of Clinical and Diagnostic Research. All right reserved.