Browsing by Author "Sudeep Kumar"

Now showing 1 - 6 of 6

A study of clinical presentation and delays in management of acute myocardial infarction in community
(Elsevier B.V., 2012) Pravin K. Goel; Saurabh Kumar Srivastava; Fauzia Ashfaq; P.R. Gupta; P.C. Saxena; Rajeev Agarwal; Sudeep Kumar; Naveen Garg; Satyendra Tewari; Aditya Kapoor
To assess the medico social demographics of acute myocardial infarction (AMI) in our community we studied 609 patients presenting between January 2008 to December 2008 with a detailed questionnaire in four centres of UP. Medical attention was sought late (> 6 hours) in 316 (51. 6%), thrombolysis was obtained in 45. 2% (275) and presentation was atypical in 16. 3% (99). 36. 2% (221) had pre-monitory symptoms of which 68% (150) ignored the same while of 32% (71) who did seek medical attention 47. 9% (37) were brushed away as non-cardiac in origin. 20. 3% (46/226) of hy- pertension, 23. 2% (43/185) of diabetes and 83. 4% (91/109) of hyperlipidaemia was diagnosed post event. We conclude that at least half of patients with AMI do not get definitive therapy, at least one in 10 patients do not have the classical symptoms, reasonable proportion are unaware of their risk factors, and a good majority have pre-monitory symptoms which get overlooked. © 2012, Cardiological Society of India. All rights reserved.
Fully Automated Agatston Score Calculation From Electrocardiography-Gated Cardiac Computed Tomography Using Deep Learning and Multi-Organ Segmentation: A Validation Study
(SAGE Publications Inc., 2024) Ashish Gautam; Prashant Raghav; Vijay Subramaniam; Sunil Kumar; Sudeep Kumar; Dharmendra Jain; Ashish Verma; Parminder Singh; Manphoul Singhal; Vikash Gupta; Samir Rathore; Srikanth Iyengar; Sudhir Rathore
To evaluate deep learning-based calcium segmentation and quantification on ECG-gated cardiac CT scans compared with manual evaluation. Automated calcium quantification was performed using a neural network based on mask regions with convolutional neural networks (R-CNNs) for multi-organ segmentation. Manual evaluation of calcium was carried out using proprietary software. This is a retrospective study of archived data. This study used 40 patients to train the segmentation model and 110 patients were used for the validation of the algorithm. The Pearson correlation coefficient between the reference actual and the computed predictive scores shows high level of correlation (0.84; P <.001) and high limits of agreement (±1.96 SD; −2000, 2000) in Bland–Altman plot analysis. The proposed method correctly classifies the risk group in 75.2% and classifies the subjects in the same group. In total, 81% of the predictive scores lie in the same categories and only seven patients out of 110 were more than one category off. For the presence/absence of coronary artery calcifications, the deep learning model achieved a sensitivity of 90% and a specificity of 94%. Fully automated model shows good correlation compared with reference standards. Automating process reduces evaluation time and optimizes clinical calcium scoring without additional resources. © The Author(s) 2024.
Fully Automated Agatston Score Calculation From Electrocardiography-Gated Cardiac Computed Tomography Using Deep Learning and Multi-Organ Segmentation: A Validation Study
(SAGE Publications Inc., 2025) Ashish Gautam; Prashant Raghav; Vijay Subramaniam; Sunil Kumar; Sudeep Kumar; Dharmendra Jain; Ashish Verma; Parminder D. Singh; Manphool Singhal; Vikash Gupta; Samir Rathore; Srikanth R.S. Iyengar; Sudhir Rathore
To evaluate deep learning-based calcium segmentation and quantification on ECG-gated cardiac CT scans compared with manual evaluation. Automated calcium quantification was performed using a neural network based on mask regions with convolutional neural networks (R-CNNs) for multi-organ segmentation. Manual evaluation of calcium was carried out using proprietary software. This is a retrospective study of archived data. This study used 40 patients to train the segmentation model and 110 patients were used for the validation of the algorithm. The Pearson correlation coefficient between the reference actual and the computed predictive scores shows high level of correlation (0.84; P <.001) and high limits of agreement (±1.96 SD; −2000, 2000) in Bland–Altman plot analysis. The proposed method correctly classifies the risk group in 75.2% and classifies the subjects in the same group. In total, 81% of the predictive scores lie in the same categories and only seven patients out of 110 were more than one category off. For the presence/absence of coronary artery calcifications, the deep learning model achieved a sensitivity of 90% and a specificity of 94%. Fully automated model shows good correlation compared with reference standards. Automating process reduces evaluation time and optimizes clinical calcium scoring without additional resources. © The Author(s) 2024.
Novel Tripartite Classification for Fractures of Coronoid Process of Mandible: A Retrospective Tertiary Center Study
(Springer, 2024) Arjun Mahajan; Akhilesh Kumar Singh; Naresh Kumar Sharma; Vyomika Bansal; Sudeep Kumar; Sharanya Mani; Zainab Akram
Introduction: Coronoid process of mandible is seldom fractured during maxillofacial trauma. Majority of the cases of coronoid fracture are treated conservatively, but some lead to complications which are often overlooked. At present, the literature on coronoid fractures is inadequate for meta-analysis. Also, there exists no standardized classification in the literature. Hence, the purpose of this study was to analyze the incidence and establish a novel ‘tripartite’ classification. Material and Methods: In this study carried out at level 1 trauma center, all patients with coronoid fracture with or without associated maxillofacial fractures were included. Relevant data were noted from Hospital records and CT scans (computer tomographic scans). These cases were classified according to ‘tripartite’ classification and treated. Data feed was given to IBM® SPSS® statistics (version 21) for analysis. Results: Among 33 coronoid fracture patients, majority (57.57% cases) were from age group of 21–40 years with 82.85% cases attributed to road traffic accidents. 11.43% cases were bilateral, and the rest unilateral cases revealed right-side predilection. Conclusion: Novel tripartite classification allows us to easily categorize and visualize the coronoid fractures. Horizontal types 1 to 3 and vertical types 4 to 6 are in increasing order of incidence, which makes it easy for communication, treatment approach and record maintenance. © The Association of Oral and Maxillofacial Surgeons of India 2024.
Patterns and determinants of dyslipidaemia in 'Young' versus 'Not so Young' patients of coronary artery disease: A multicentric, randomised observational study in northern India
(Elsevier B.V., 2012) Nakul Sinha; Sudeep Kumar; Himanshu Rai; Neha Singh; Aditya Kapoor; Satyendra Tewari; R.K. Saran; V.S. Narain; R.P.S. Bharadwaj; R.K. Bansal; P.C. Saxena; P.R. Sinha; P.R. Gupta; Mukul Mishra; Praveen Jain; C.M. Pandey; Uttam Singh; S.S. Agarwal
Aims: The aims of the study were to ascertain difference in lipid levels of 'Young' onset of coronary artery disease (CAD) (≤ 45 years) vs. 'Not so Young' onset of CAD (≥ 55 years) among north Indians and also to investigate determinants of 'dyslipidaemia' in CAD patients. Methods: This was a prospective, multicentric, randomised, observational study carried in eight cen- tres of UP, India. All blood investigations were performed employing a central laboratory. Results: Out of a total 435 patients studied, 218 were in the 'young group' (YG) and 235 were in the 'Not so Young Group' (NSYG). Dyslipidaemia was more common in YG as evident by significantly higher levels of total cholesterol, triglycerides, low- and very low-density lipoprotein cholesterol as compared to NSYG. Diabetes, hypertension, urban lifestyle, and family history of CAD were found to be important determinants of dyslipidaemia in YG. Conclusion: We conclude that lipid levels among north Indians are significantly higher in younger patients with CAD when compared with elderly. © 2012, Cardiological Society of India. All rights reserved.
Silent intruders: Hematolymphoid neoplasms revealed in the jaws: a series of three cases
(Wolters Kluwer Medknow Publications, 2025) Trupti Jain; Sudeep Kumar; Shivangni Rajoria; R. Keerthika; Akhilesh Chandra; Rahul Agrawal
The head and neck regions, rich in lymph nodes, are common initial sites for nodal and extranodal hematolymphoid neoplasms, particularly B-cell neoplasms. Lymphomas, including Hodgkin’s and non-Hodgkin’s types, range from indolent to aggressive and often affect the oral and maxillofacial areas. Plasma cell neoplasms, such as solitary bone plasmacytoma (SBP) and solitary extramedullary plasmacytoma (SEP), must be distinguished from multiple myeloma (MM) due to varied treatment modalities. Diagnosing these neoplasms is challenging, requiring thorough examination. Timely recognition and management of plasma cell tumors in the head and neck, especially SBP, are essential to prevent disease progression. These tumors can mimic other malignancies and indicate early MM, necessitating detailed evaluation. Healthcare providers should be aware of the higher risk of oral NHL in HIV-positive patients and consider NHL in the differential diagnosis of intraoral lesions to improve outcomes. Herein, we present three cases with usual presentations in the oral cavity that resulted in unusual diagnoses. © 2025 Indian Journal of Pathology and Microbiology.