Transforming scholarly landscapes: The influence of large language models on academic fields beyond computer science

by Aniket Pramanick, Yufang Hou, Saif M. Mohammad, Iryna Gurevych

Large Language Models (LLMs) have ushered in a transformative era in Natural Language Processing (NLP), reshaping research and extending NLP’s influence to other fields of study. However, there is little to no work examining the degree to which LLMs influence other research fields. This work empirically and systematically examines the influence and use of LLMs in fields beyond NLP. We curate 106 LLMs and analyze ∼148k papers citing LLMs to quantify their influence and reveal trends in their usage patterns. Our analysis reveals not only the increasing prevalence of LLMs in non-CS fields but also the disparities in their usage, with some fields utilizing them more frequently than others since 2018, notably Linguistics and Engineering together accounting for ∼45% of LLM citations. Our findings further indicate that most of these fields predominantly employ task-agnostic LLMs, proficient in zero or few-shot learning without requiring further fine-tuning, to address their domain-specific problems. This study sheds light on the cross-disciplinary impact of NLP through LLMs, providing a better understanding of the opportunities and challenges.

Single catheter strategy for transradial angiography and primary percutaneous coronary intervention enhances procedural efficiency, microvascular outcomes, and cost-effectiveness: Implications for STEMI healthcare in resource-limited settings

by Mohajit Arneja, Swetharajan Gunasekar, Dharaneswari Hari Narayanan, Joshma Joseph, Harilalith Kovvuri, Sharath Shanmugam, Pavitraa Saravana Kumar, Asuwin Anandaram, Vinod Kumar Balakrishnan, Jayanty Venkata Balasubramaniyan, Sadhanandham Shanmugasundaram, Sankaran Ramesh, Nagendra Boopathy Senguttuvan

Background

Faster time to reperfusion can be achieved by minimizing various patient and system-level delays that contribute to total ischemic time. Procedural delays within the catheterization laboratory represent a non-negligible and modifiable component in the chain of reperfusion, but remain unquantified by conventional metrics such as door-to-ballon (D2B) time. Universal catheter approaches have rapidly gained traction as an alternative to the traditional two catheter approach for transradial coronary interventions. However, their utility for both diagnostic angiography and subsequent angioplasty is limited, and the impact of this strategy on reperfusion outcomes has remained unexplored. We utilized a procedural metric termed fluoroscopy-to-device (FluTD) time to quantify the efficiency of a single catheter strategy, and assessed its impact on epicardial and myocardial perfusion.

Methods and results

In this retrospective study, consecutive STEMI patients undergoing transradial primary PCI (pPCI) at a tertiary care center in India between May 2022 to October 2024 were analyzed. Patients were divided into two groups: 51 underwent PCI using a single universal guiding catheter (UGC), and 51 underwent the conventional two-catheter (CTC) approach. The primary outcome of the study was a comparison of the FluTD time between the two procedural strategies. Secondary outcomes included myocardial blush grade (MBG), Thrombolysis in Myocardial Infarction (TIMI) flow grade, total fluoroscopy time, radiation dose, device safety and efficacy, and procedural success.The median FluTD time was significantly shorter in the UGC compared to the CTC group (3 minutes [IQR 3–4] vs. 10 minutes [IQR 8–17], p  Conclusion

A single catheter strategy for both angiography and pPCI in STEMI patients was associated with a significant reduction in FluTD time and improved microvascular perfusion, without compromising device safety or efficacy. In low- and middle-income countries (LMICs), where intra- and extra-procedural delays are often more pronounced, inclusion of the single catheter strategy can optimize catheterization workflows and yield substantial cost-savings.