A comprehensive evaluation of risk factors for mortality, infection and colonization associated with CRGNB in adult solid organ transplant recipients: a systematic review and meta-analysis.

BACKGROUND: The burden of carbapenem-resistant gram-negative bacteria (CRGNB) among solid organ transplant (SOT) recipients has not been systematically explored. Here, we discern the risk factors associated with CRGNB infection and colonization in SOT recipients. METHODS: This study included observational studies conducted among CRGNB-infected SOT patients, which reported risk factors associated with mortality, infection or colonization. Relevant records will be searched in PubMed, Embase and Web of Science for the period from the time of database construction to 1 March 2023. RESULTS: A total of 23 studies with 13,511 participants were included, enabling the assessment of 27 potential risk factors. The pooled prevalence of 1-year mortality among SOT recipients with CRGNB was 44.5%. Prolonged mechanical ventilation, combined transplantation, reoperation and pre-transplantation CRGNB colonization are salient contributors to the occurrence of CRGNB infections in SOT recipients. Renal replacement therapy, post-LT CRGNB colonization, pre-LT liver disease and model for end-stage liver disease score increased the risk of infection. Re-transplantation, carbapenem use before transplantation and ureteral stent utilization increaesd risk of CRGNB colonization. CONCLUSION: Our study demonstrated that SOT recipients with CRGNB infections had a higher mortality risk. Invasive procedure may be the main factor contribute to CRGNB infection.

Artificial intelligence-based language learning: illuminating the impact on speaking skills and self-regulation in Chinese EFL context.

Introduction: This study investigated the effectiveness of artificial intelligence-based instruction in improving second language (L2) speaking skills and speaking self-regulation in a natural setting. The research was conducted with 93 Chinese English as a foreign language (EFL) students, randomly assigned to either an experimental group receiving AI-based instruction or a control group receiving traditional instruction. Methods: The AI-based instruction leveraged the Duolingo application, incorporating natural language processing technology, interactive exercises, personalized feedback, and speech recognition technology. Pre- and post-tests were conducted to assess L2 speaking skills and self-regulation abilities. Results: The results of the study demonstrated that the experimental group, which received AI-based instruction, exhibited significantly greater improvement in L2 speaking skills compared to the control group. Moreover, participants in the experimental group reported higher levels of self-regulation. Discussion: These findings suggest that AI-based instruction effectively enhances L2 speaking skills and fosters self-regulatory processes among language learners, highlighting the potential of AI technology to optimize language learning experiences and promote learners' autonomy and metacognitive strategies in the speaking domain. However, further research is needed to explore the long-term effects and specific mechanisms underlying these observed improvements.