宣布 John J. Sciarra 2024 年度 IJGO 论文奖得主

IF 2.6 3区医学 Q2 OBSTETRICS & GYNECOLOGY

International Journal of Gynecology & Obstetrics Pub Date : 2025-03-06 DOI:10.1002/ijgo.70061

Michael Geary

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引用次数: 0

摘要

《国际妇科杂志》编辑；产科（IJGO）很高兴地宣布，2024年在IJGO发表的来自低收入或中等收入国家的最佳临床研究论文奖的获奖者。获奖论文是：Soares FM， da Rocha Carvalho Rosa LO， Cecatti JG等。设计，建设和验证产科风险分类系统，以预测重症监护病房入院。中华妇产科杂志；2024；167: 1243 - 1254。https://doi.org/10.1002/ijgo.15782。这篇文章发表在2024年12月的《IJGO》上。该奖项将提供800英镑的津贴，一份认可证书，并从奖项颁发之日起一年内免费进入IJGO。低收入和中等收入国家在2024年向IJGO提交的所有临床研究论文都被考虑为该奖项的候选人。这篇论文是从181篇符合条件的文章中选出的。编辑们进行了选择和审查，IJGO编辑委员会批准了这一决定。获奖论文由Soares等人撰写。该研究调查了基于机器学习的风险分类系统的开发和验证，以预测高危孕妇的重症监护病房（ICU）入院情况。利用9550例严重孕产妇发病率的数据，对机器学习模型的准确性、敏感性和特异性进行了测试。表现最好的模型XGBoost估计ICU入院率为11.6%，低于实际的21.5%，表明可能存在ICU资源过度使用的情况。这项研究的结果强调了人工智能驱动的工具在优化ICU分配和改善孕产妇护理方面的潜力。其他值得特别表彰的论文将被授予荣誉奖。虽然荣誉奖不包括经济奖励，但每位作者都会收到IJGO编辑的认可证书和推荐信。以下11篇论文获得荣誉奖：

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Announcing the winner of the John J. Sciarra IJGO prize paper award for 2024

The editors of the International Journal of Gynecology & Obstetrics (IJGO) are pleased to announce the winner of the prize paper award for the best clinical research paper from a low- or middle-income country published in IJGO during 2024. The winning paper is: Soares FM, da Rocha Carvalho Rosa LO, Cecatti JG, et al. Design, construction, and validation of obstetric risk classification systems to predict intensive care unit admission. Int J Gynecol Obstet. 2024; 167: 1243–1254. https://doi.org/10.1002/ijgo.15782. It was published in the December 2024 issue of IJGO.

This award brings with it a stipend of £800, a certificate of recognition, and complimentary access to IJGO for a period of 1 year from the date the prize is awarded.

All clinical research articles submitted to the IJGO from low- and middle-income countries that were published in 2024 were considered for this prize. The paper was chosen from 181 qualifying articles. Selection and review were undertaken by the editors, and the Editorial Board of IJGO endorsed the decision.

The winning paper is by Soares et al. The study investigates the development and validation of a machine-learning-based risk classification system to predict intensive care unit (ICU) admission for high-risk pregnant women. Using data from 9550 cases of severe maternal morbidity, machine-learning models were tested on accuracy, sensitivity and specificity. The highest-performing model, XGBoost, estimated ICU admission at 11.6%, lower than the actual 21.5%, suggesting the potential overuse of ICU resources. The findings of this study highlight the potential for AI-driven tools to optimize ICU allocation and improve maternal care.

Additional papers that are worthy of special recognition are awarded an honorable mention. While the honorable mention recognition does not include a financial award, each author receives a certificate of recognition and a letter of commendation from the editors of IJGO.

The following 11 papers receive an honorable mention:

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来源期刊

International Journal of Gynecology & Obstetrics 医学-妇产科学

CiteScore

5.80

自引率

2.60%

发文量

493

审稿时长

3-6 weeks

期刊介绍： The International Journal of Gynecology & Obstetrics publishes articles on all aspects of basic and clinical research in the fields of obstetrics and gynecology and related subjects, with emphasis on matters of worldwide interest.