ABSTRACT
One of the major causes of morbidity and mortality in tropical and subtropical regions is Dengue viral infection. This virus belongs to family flaviviridae comprising of four antigenically distinct serotypes DENV 1 - 4. A small number of studies conducted in North Eastern (NE) Region of India reported Dengue cases in Assam, Meghalaya, Nagaland, Manipur and Arunachal Pradesh. However, no studies have been conducted in the state of Tripura, with regard to pattern of Dengue viral infection and its circulating serotypes. Therefore, this study was undertaken to identify the serotypes circulating in Tripura. MethodsPatients with acute febrile illness were tested for detecting Dengue viral infection by MAC ELISA and / or NS1 detection test at Viral Research and Diagnostic Laboratory (VRDL), of a tertiary care centre in Tripura for a period of 3 years. All NS1 positive samples were further tested for presence of viral RNA by Reverse Transcriptase –PCR (RT - PCR) and serotyping was done using serotype specific primers. ResultsA total of 2515 acute febrile cases seen over a period of 3 years from 2014 to 2017 was tested for Dengue virus infection by serology. Out of 2515 of cases, 405 cases tested for NS1 antigen, where 10.61 % (43 / 405) was NS1 positive. The remaining 2110 cases were tested for IgM antibody MAC ELISA and 15.68 % (331 / 2110) was MAC ELISA positive. Out of all NS1 antigen positive cases 34.88 % of PCR positive and serotype characterisation showed DENV - 1 was predominant serotype followed by DENV - 2 and DENV - 4 respectively. ConclusionsThere is a rising trend of Dengue virus infection in Tripura with circulation of multiple serotypes. Moreover, cocirculation of multiple serotypes is a risk to the emergence of recombinant strains and also heterotypic infection in the near future might lead to development of DHF and DSS. Hence, molecular characterization of circulating serotypes may be helpful in addressing the probabilities of Dengue outbreak and possibilities of complications.
ABSTRACT
Background:Lower Respiratory Tract Infection(LRTI) is one of the commonest health problem which is not a single disease but a group of specific infections with varying etiology and symptomatology. This study was undertaken to determine bacterial etiology of LRTI and associated risk factors 250 samples from patients with suspected LRTI were collected Methodology:and processed by standard microbiological procedure. Risk factors relating to LRTI were also further evaluated from clinical history of the patient. Total 100 isolates were recovered where Klebsiella pneumoniae(57%) was predominant followed by Pseudomonas Results:aeruginosa(19%), Acinetobacter spp.,(9%), Citrobacter freundii(7%), Staphylococcus aureus(3%), and Streptococcus pneumoniae(2%). Multiple co-morbidities are more associated with LRTI than single risk factor like Diabetes mellitus, Smoking, Alcohol, Hypertension and COPD. Knowledge of bacterial agents causing LRTI and prevalent risk factors in our geographical area is to be required for better Conclusion:treatment and prevention of the disease
ABSTRACT
Introduction: Resistance to antibiotics is an extremely common phenomenon in bacteria isolated from clinical material. However there is scarcity of data on antibiotic resistance from North Eastern part of India. In this Study, we aimed to generate data to find out the trend of Antibiotic resistance among the clinical isolates. Methods: Involving both indoor and outdoor patients attending this hospital are included in this study. Culture & Microbial sensitivity were performed by ‘Kirby Bauer‘ method and an according to current CLSI guidelines. Drug resistance pattern were analyzed among the Common clinical isolates. Results: Majority of isolated organisms were klebsiella sp and Staphylococcus sp . Cephalosporins resistance (99%) was more in Gram negative bacilli as compare to Fluroquinolones among Gram positive cocci (85%). Conclusion: This pilot study from a Medical College of North East has demonstrated very high levels of resistance to commonly used antibiotics and generated data can be used to formulate antibiotic use protocols in the state.