Artificial Intelligence is no more the talk of the fiction read in novels or seen in movies. It has been making inroads slowly and gradually in medical education and clinical management of patients apart from all other walks of life. Recently, chatbots particularly ChatGPT, were developed and trained, using a huge amount of textual data from the internet. This has made a significant impact on our approach in medical science. Though there are benefits of this new technology, a lot of caution is required for its use. doi: https://doi.org/10.12669/pjms.39.2.7653 How to cite this: Khan RA, Jawaid M, Khan AR, Sajjad M. ChatGPT - Reshaping medical education and clinical management. Pak J Med Sci. 2023;39(2):---------. doi: https://doi.org/10.12669/pjms.39.2.7653 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BackgroundSouth-Asia is known as a hub for multidrug-resistant (MDR) bacteria. Unfortunately, proper surveillance and documentation of MDR pathogens is lacking in Pakistan. The alarming increase in the prevalence of extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae is a serious problem. From this perspective, we analysed published data regarding ESBL-producing Enterobacteriaceae in different regions of Pakistan.MethodsA meta-analysis was performed to determine the prevalence of ESBL-producing Enterobacteriaceae in Pakistan. A Web-based search was conducted in electronic databases, including PubMed, Scopus and PakMedi Net (for non-indexed Pakistani journals). Articles published (in either indexed or non-indexed journals) between January 2002 and July 2016 were included in the study. Relevant data were extracted, and statistical analysis was performed using the Metaprop command of STATA version 14.1.ResultsA total of 68 studies were identified from the electronic data base search, and 55 of these studies met our inclusion criteria. Pakistan’s overall pooled proportion of ESBL-producers was 0.40 (95% CI: 0.34–0.47). The overall heterogeneity was significant (I2 = 99.75%, p < 0.001), and significant ES = 0 (Z = 18.41, p < 0.001) was found. OXA, SHV, TEM and CTX-M were the most commonly found gene variants for ESBLs in these studies.ConclusionThe prevalence of ESBL-producing Enterobacteriaceae is high in Pakistan. Little is known about the annual frequency of ESBLs and their prevalence in different provinces of Pakistan. No data are available regarding ESBL frequency in Baluchistan. This underscores an urgent demand for regular surveillance to address this antimicrobial resistance problem. Surveillance to better understand the annual ESBL burden is crucial to improve national and regional guidelines.

The concept of drone usage for commercial purposes by retailers worldwide is still in its early stages, and unheard of in Pakistan. Moreover, research on consumer perceptions regarding commercial drones in Pakistan and around the world is very sparse. The purpose of this paper is to gauge the level of acceptability and concerns Pakistani consumers may have in accepting the drone delivery technology. This study offers new insights that retailers and delivery companies can use to penetrate target markets in early stages. The authors have executed a quantitative analysis through the means of a survey. A sample of middle‐ and upper class residents of two cities in Pakistan was selected on which purposive sampling technique was applied. A total of 307 responses were collected and these responses were analysed in SPSS. Various analysis techniques were applied including Cronbach’s alpha, the Pearson correlation analysis, regression analysis and cluster analysis. The results show that consumers in Pakistan perceive privacy issues as a primary concern in relation to drone delivery. The results also throw light on the profile of consumer segments that can be targeted by retailers who may desire to use the drone delivery technology in the near future. Using these findings, retailers using the drone delivery mechanism can address consumer’s fears and ambiguities. Retailers can resolve consumer concerns by designing pro‐privacy parameters in the initial service design stage and the infrastructure deployment of drones.

Objective:To determine the factors contributing to lack of interest in research activities among postgraduate residents in pediatric medicine.Methods:This cross-sectional survey was conducted at The Children’s Hospital Lahore, Pakistan in August 2017. The questionnaire was distributed to 105 postgraduate residents working in pediatric medicine department and 90 of them returned the completed proforma (response rate; 86%). Data was analyzed by SPSS version 22.Results:Out of 90 residents’ females were predominant (n=58/90; 64.4%). Mean age of the participants was 28.22 ± 2.092 years. Majority were unmarried (n=57; 63.3%). The highest mean score (2.31±0.697) was regarding “Lack of proper training for research”, followed by “lack of previous exposure” (2.26±0.728) and “over loaded curriculum” (2.13±0.753). “Uncooperative faculty” and “funding issues” as a barrier towards research (p=0.016 and 0.014 respectively) was mentioned by males more than females. “Social and family commitment” was a significant perceived barrier in married residents as compared to unmarried residents (p=0.001). The residents in the younger age group were more reluctant to do research due to “over loaded curriculum” (p=0.038).Conclusion:Lack of proper training of research, lack of previous exposure and time management are the major factors affecting resident’s research work, whereas married residents face more social/family constraints as compare to unmarried residents.

Standard statistical procedures often require data to be normally distributed and the results of these methods will be inappropriate when the assumption of normality is not satisfied. Therefore, the postulation of normality is strictly required before proceeding statistical analysis. Although a number of criteria's have been available to assess the assumption of normality, but these tests do not have the same nature and power to diagnose the departures of a data set from normality, thus the choice of appropriate test always remains a