Artificial Intelligence Revolutionizing the Field of Medical Education.

Medical education has ventured into a new arena of computer-assisted teaching powered by artificial intelligence (AI). In medical institutions, AI can serve as an intelligent tool facilitating the decision-making process effectively. AI can enhance teaching by assisting in developing new strategies for educators. Similarly, students also benefit from intelligent systems playing the role of competent teachers. Thus, AI-integrated medical education paves new opportunities for advanced teaching and learning experiences and improved outcomes. On the other hand, optical mark recognition and automated scoring are ways AI can also transform into a real-time assessor and evaluator in medical education. This review summarizes the AI tools and their application in medical teaching or learning, assessment, and administrative support. This article can aid medical institutes in planning and implementing AI according to the needs of the educators.

Presence of Resistant DEC Strains in a Tertiary Healthcare Center in North East India in Children under 18 Years.

Introduction Diarrheal illness such as diarrheagenic Escherichia coli (DEC), apart from rotavirus, is a common etiological agent known to cause moderate-to-severe diarrhea in low-income countries where unregulated use of antibiotics is rampant, giving rise to multidrug resistant (MDR) strains. This study is an earnest effort in reflecting the resistance pattern in such isolates. Materials and Methods It is a hospital-based cross-sectional study conducted over a period of 1 year (January to December, 2015). Children aged less than 18 years presenting with ( n = 170) and without ( n = 47) diarrhea were included as cases and controls, respectively. Fresh stool sample from eligible participants was collected and inoculated on MacConkey agar. Based on the colony morphology and biochemical identification followed by polymerase chain reaction (PCR), different pathotypes of DEC were identified. All such isolates were subjected to antimicrobial susceptibility testing employing VITEK 2 identification system. The result of the tested antibiotics was evaluated as per Clinical and Laboratory Standards Institute 2015 guidelines. Results DEC with specific virulence genes were detected by multiplex real-time PCR in 39 and 3 children with or without diarrhea, respectively. Most common DEC pathotypes found were enteroaggregative E. coli (38%) followed by enteropathogenic E. coli (28.5%). MDR isolates comprised 35 of 42 DEC pathotypes (83.3%). Resistance among DEC pathotypes to ampicillin, amoxicillin-clavulanate, ciprofloxacin, cephalosporin, nalidixic acid, imipenem, and cotrimoxazole was found to be statistically significant in comparison to non-DEC isolates. Conclusion This study has highlighted the increased prevalence of MDR strains among DEC pathotypes. Looking for these isolates will help detect dreadful DEC pathotypes like enterohemorrhagic E. coli where early administration of a sensitive antibiotic will go a long way in preventing complication like hemorrhagic colitis and hemolytic uremic syndrome.

Ecology of Bloodstream Infections and Temporal Trends of Their Antibiograms with Respect to Source and Duration of Incubation: A 5-Year Retrospective Observational Analysis.

Purpose Blood is one of the most important connective tissues of human body. Bloodstream infection can range from inapparent bacteremia till fulminant septic shock with high mortality. Presence of microbes in blood whether continuously, intermittently, or transiently is a grave risk to every organ of body. Culture of blood is a vital tool to diagnose such infections. Drug susceptibility patterns help in rationalizing therapy. Objective The aim of the study is to perform bacteriological analysis and assess drug sensitivity patterns of blood culture isolates and compare in light of other associated variables. Design Retrospective observational study was conducted from January 2009 to December 2013 at a tertiary care hospital at Shillong, India. Blood samples were collected with aseptic guidelines and cultured for 7 days. Growths were identified by standard biochemical tests and subjected to sensitivity testing according to Modified Kirby Bauer disk diffusion method. Data for source of blood collection and duration of incubation were noted and compared. Results A total of 658 (11.2%) pathogens were isolated from 5,867 bacteremia-suspected patient blood specimens. Contamination was observed at the rate of 1.21%. Gram-negative organisms were the predominant pathogens recovered, Klebsiella pneumoniae being the most common. No significant difference was observed between the number of organisms isolated within or beyond 48 hours. Acinetobacter baumannii and K. pneumoniae have significantly higher chances ( p < 0.05) of isolation from central line catheters compared with peripheral venipuncture. Conclusion Successful treatment of sepsis depends on early diagnosis and proper antimicrobial therapy. Local knowledge of bacteriological profile and antimicrobial sensitivity patterns helps rationalize empiric treatment strategies.

Clinico-aetiologic profile of Onychomycoses in a tertiary care centre in northeast India.

Onychomycosis refers to fungal nail infection. Despite a clearly diseased appearance, it is often deemed a merely cosmetic problem of relatively minor importance. However, it may result in much psychological or occupational turmoil, diminished self-esteem and resulting reluctance for public interaction. A wide number of factors determine the treatment outcome and its prevalence varies greatly. Our study was conducted between January 2011 and December 2014 in northeast India. Of 243 patients presenting with nail abnormalities, 158 (65%) were positively diagnosed by either direct microscopy or culture or both. A distal lateral subungual infection was the most predominant clinical pattern observed, and the most frequent aetiological agents were dermatophytes, of which Trichophyton rubrum was predominant.

Real-time multiplex polymerase chain reaction with high-resolution melting-curve analysis for the diagnosis of enteric infections associated with diarrheagenic Escherichia coli.

INTRODUCTION: Although diarrheagenic Escherichia coli (DEC) strains are important bacterial causative agents of diarrhoea, they are not routinely sought as stool pathogens in clinical laboratories as conventional microbiological testing are unable to distinguish between normal flora and pathogenic strains of E. coli. This study was undertaken to determine the prevalence of DEC pathotypes amongst children with and without diarrhoea and to detect specific virulent genes present in different DEC pathotypes, using real-time multiplex polymerase chain reaction (PCR) with high-resolution melting (HRM) technology. MATERIALS AND METHODS: Stool samples were obtained from cases and controls. Using a set of conventional biochemical tests, E. coli strains were identified. Further, these isolates were subjected to multiplex PCR system for the detection of virulence genes of different pathotypes of DEC. Real-time multiplex PCR was performed for the detection of specific virulent genes of DEC pathotypes, using Rotor-Gene Q instrument (Qiagen) having High-resolution Melt analyser using Type-it HRM PCR kit (Qiagen) containing EvaGreen fluorescent intercalating dye. RESULTS: In this study, we had successfully standardised two multiplex PCR assays which were found to be effective for direct detection of enteropathogenic E. coli (EPEC), enteroaggregative E. coli (EAEC), enterotoxigenic E. coli (ETEC) and enteroinvasive E. coli (EIEC). A total of 42 DEC strains were detected at an overall rate of 19.3% (n = 42), from the total 217 E. coli isolates recovered from the cases (n = 39, 17.9%) and control (n = 3, 3.8%) groups. Amongst the 42 DEC pathotypes (39 from cases and 3 from controls), EPEC (10%), EAEC (8.82%), ETEC (2.94%) and EIEC (1.18%) were found in children with diarrhoea (cases) and in children without diarrhoea (control) only EAEC (2.13%) and EPEC (4.26%) were detected. Age distribution, gender variation, seasonal variation and clinical features were also analysed. CONCLUSION: This study helped evaluate the prevalence of DEC amongst children (<18 years of age) with and without diarrhoea using multiplex real-time PCR with HRM analysis.