Machine Learning on 50,000 Manuscripts Shows Increased Clinical Research by Academic Cardiac Surgeons

IF 1.8 3区 医学 Q2 SURGERY
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引用次数: 0

Abstract

Introduction

Academic cardiac surgeons are productive researchers and innovators. We sought to perform a comprehensive machine learning (ML)-based characterization of cardiac surgery research over the past 40 y to identify trends in research pursuits.

Methods

US-based academic websites were queried for surgeon profiles. Publications since 1980 were obtained from Web of Science, and publication classifications (e.g., “human”, “animal”) were collected through the National Institutes of Health iCite tool. Publications were deemed “basic or translational” if >50% of their classification was under “animal” or “molecular or cell”, and “clinical” if otherwise. ML-based clustering was performed on publication titles and Medical Subject Heading terms to identify research topics.

Results

A total of 944 cardiac surgeons accounted for 48,031 unique publications. Average citations per year have decreased since 1980 (P < 0.001). The percentage of basic or translational publications by cardiac surgeons has decreased over time (P < 0.001), comprising of only 8% of publications in 2022. Adult cardiac surgeons, those who received an F32, K08, or R01, and those with a PhD were more likely to publish basic or translational research. Top areas of basic or translational research were myocardial reperfusion, aortic aneurysms or remodeling, and transplant immunology. Major areas of clinical research included aortic disease, aortic valve disease, and mechanical circulatory support. Collaboration analysis revealed that 55% of publications were single-center, and the yearly percentage of these publications has decreased over time (P < 0.001).

Conclusions

Cardiac surgeons are performing less basic or translational research relative to clinical research than ever before. The majority of publications over the past 40 y did not involve cross-center collaboration. Continued support for clinical research is needed, while also encouraging collaborative basic or translational science to foster innovation in patient care.

对 50,000 篇手稿的机器学习显示学术界心脏外科医生的临床研究有所增加
导言:学术界的心脏外科医生是卓有成效的研究者和创新者。我们试图对过去 40 年的心脏外科研究进行基于机器学习 (ML) 的全面描述,以确定研究趋势。1980年以来的出版物来自Web of Science,出版物分类(如 "人类"、"动物")通过美国国立卫生研究院iCite工具收集。如果>50%的分类属于 "动物 "或 "分子或细胞",则将其视为 "基础或转化 "论文,反之则视为 "临床 "论文。对出版物标题和医学主题词进行了基于 ML 的聚类,以确定研究主题。结果共有 944 名心脏外科医生发表了 48,031 篇独特的出版物。自 1980 年以来,每年的平均引用次数有所下降(P < 0.001)。随着时间的推移,心脏外科医生发表的基础或转化性论文的比例也在下降(P <0.001),2022 年仅占论文总数的 8%。成年心脏外科医生、获得 F32、K08 或 R01 的医生以及拥有博士学位的医生更有可能发表基础或转化研究论文。基础或转化研究的首要领域是心肌再灌注、主动脉瘤或重塑以及移植免疫学。临床研究的主要领域包括主动脉疾病、主动脉瓣疾病和机械循环支持。合作分析表明,55% 的论文是单中心发表的,随着时间的推移,这些论文的年度比例有所下降(P < 0.001)。过去 40 年中发表的大多数论文都不涉及跨中心合作。需要继续支持临床研究,同时鼓励合作开展基础或转化科学研究,以促进患者护理的创新。
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来源期刊
CiteScore
3.90
自引率
4.50%
发文量
627
审稿时长
138 days
期刊介绍: The Journal of Surgical Research: Clinical and Laboratory Investigation publishes original articles concerned with clinical and laboratory investigations relevant to surgical practice and teaching. The journal emphasizes reports of clinical investigations or fundamental research bearing directly on surgical management that will be of general interest to a broad range of surgeons and surgical researchers. The articles presented need not have been the products of surgeons or of surgical laboratories. The Journal of Surgical Research also features review articles and special articles relating to educational, research, or social issues of interest to the academic surgical community.
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