Online ISSN: 2515-8260

Keywords : CAD


Tirumalasetty.Sriharsha, A.Arun Kumar, Deepthi.V, Raghav Raj.J, Vikrannth.V, Kannan.R

European Journal of Molecular & Clinical Medicine, 2023, Volume 10, Issue 1, Pages 876-880

 Introduction: Auto immune haemolytic anemias are caused by antibody production by the body against its own RBCs. They are characterised by a positive direct anti globulin test and divided into warm and cold types. Vitamin B12 deficiency associated with Auto immune hemolytic anemia  leads to  severe complications such as severe anemia, pancytopenia, and rarely hemolysis.  
Case presentation:A  37 year old male presented with c/o breathlessness, yellowish discolouration of eyes, oral ulcers, generalised fatigue, decreased appetite for 3 weeks. Clinical examination was unremarkable except for pallor, icterus and oral ulcers. Lab reports revealed severe anemia with peripheral smear  Peripheral smear showed macrocytic normochromic anemia, hypersegmented neutrophils, cabot rings with hemolysis features. S.Folate and B12 levels were Low.Direct Coomb’s test was positive. LFT revealed Indirect Hyper Bilirubinemia, Increased LDH. Patient treated with PRBC transfusion and Inj.Vitamin B12 intra venously .On follow up patient symptoms got improved .
Conclusion:  Macrocytic anemia presented with Hemolysis is rare in occurence.The fact that patients anemia resolved after vitamin B12 treatment indicates a possibility of vitamin B12 Deficiency causing AIHA


Dr. Devpriya Shukla, Dr. Pushpendra Singh Sengar, Dr. Anju Jha, Dr. Maneesh Jain

European Journal of Molecular & Clinical Medicine, 2022, Volume 9, Issue 7, Pages 463-470

INTRODUCTION: -Heart failure is among key reasons of hospitalizations throughout the world. Prevalence is 1% among the ages of 50 and 59 years, gradually growing to >10% over age of 80 years. In patients with heart failure, concomitant and notable renal impairment is prevalent. Heart failure is increasingly being classified as a type of cardiorenal failure, in which there are contemporaneous cardiac and renal dysfunctions, each of which         accelerates the progress of the other.
AIMS AND OBJECTIVES:-To study the etiology, risk factors and clinical outcomes of heart failure and cardiorenal syndrome.
MATERIALS AND METHODS: - The present study is an observational study conducted at Sri Aurobindo medical college and Post Graduate Institute, Hospital ,Indore on 75 patients admitted in Medicine ward, Medicine emergency and Medicine ICU.
RESULTS:-The major risk factor which associated with mortality was coronary artery disease  73.5%.Type 2 diabetes mellitus was present in 62.5% patients while hypertension in 42.7%. Smoking was the risk factor in 46.2% and alcohol in 41.7% patients, COPD was present in 8.2% cases. NYHA grade 4 was more common and was seen in 79.2% while NYHA grade 3 in 22.8% cases.
CONCLUSION: Cardiorenal syndrome is very common in people who have heart failure. Patients with heart failure who have had two or more previous hospitalizations, sepsis, history of CAD and hypothyroidism are more likely to develop cardiorenal syndrome. The development of cardiorenal syndrome is an independent predictor of frequent readmissions, In addition to longer hospitalization and slower recovery, under treatment of the cardiorenal syndrome has the potential to be fatal on an individual level and have massive public health repercussions.

Micro and Macro vascular complications in type 2 diabetic patients with non-alcoholic fatty liver disease

Dr.Anil Kumar, Dr.J Nagajyothi, Dr.Raghu Nandan

European Journal of Molecular & Clinical Medicine, 2022, Volume 9, Issue 1, Pages 447-453

NAFLD is a spectrum of liver lesions ranging from simple hepatic steatosis to NASH with progressive fibrosis leading to cirrhosis and liver failure in some patients and eventually hepatocellular carcinoma. The different parts of this spectrum are probably best regarded as parts of a histological continuum. All patients underwent ultrasound (USG) of the abdomen to detect fatty changes in the liver, performed by aexperienced radiologist, using a high-resolution B-mode ultrasonography system, having an electric linear transducer mid frequency of 3-5 MHz.The scanning was done for an average of 20 minutes.
In our study out of 50 patients,22(44%) patients were having diabetic neuropathy on the basis of clinical examination,out of them 10 (45.45%) patients were males & 12 (54.54%) patients were females. There was higher prevalence of diabetic neuropathy in female patients. 28 (56%) patients were negative for neuropathy. Out of total 50 diabetic patients with NAFLD, 31 (62%) patients were having evidence of CAD, out of 31 patients, 17 (54.8%) were male & 14 (45.2%) were female. 19 (38%) patients having no evidence of CAD.

A Computer Aided Diagnosis of Lung Disease using Machine Learning Approach

Subapriya V; Jaichandran R; Shunmuganathan K.L; Abhiram Rajan; Akshay T; Shibil Rahman

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 2662-2667

Cancer is a disease that is unregulated by cells in the body. Lung nodule is called lung cancer because the disease starts in the lungs. Cancer of the pulmonary system begins in the lungs and may travel to lymph nodes or other body species such as the brain. The lungs can also be impacted by cancer from other bodies. The metastases are named as cancer cells migrate from organ to organ. Lung cancers are normally grouped into two major cell and non-small cell types. In this study we predict a Computer Aided Diagnosis (CAD) for lung cancer prediction using Convolutional Neural Network (CNN) and ML approach

Deep Learning in Tuberculosis Diagnosis: A Survey

B. Sandhiya; Dr.R. Punniyamoorthy; Saravanan. B; Vijay Prabhu. R; Subhash. V

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 2736-2740

Tuberculosis is a contagious syndrome that leads to death Worldwide. In majority of the developing countries, the access to the diagnostic tool and the test usage is relatively poor. Now the recent advancement in the field of Artificial Intelligence may help them to fill this technology gap. Computer Aided Detection and Diagnosis helps in diagnosing the diseases through some clinical symptoms as well as X-ray images of the patients. Nowadays many strategies are formulated to increase the classification accuracy of tuberculosis diagnosis using AI and Deep Learning approaches. Our survey paper, focus to describe the wide AI and deep learning approaches employed in the diagnosis of tuberculosis.