慢性胰腺炎的个体化疼痛治疗 (INPAIN):一项国际性、多中心、研究者发起的前瞻性队列研究。

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Rasmus Hagn-Meincke,Ana Dugic,Ankit Agarwal,Anna Evans Phillips,Anna Waage,Dhiraj Yadav,Divya Pillai,Elaina Vivian,Enrique de-Madaria,Imran Khan Niazi,Jeffrey Easler,Jens Brøndum Frøkjær,Julia McNabb-Baltar,Louise Kuhlmann Asferg,Mahya Faghih,Maria Belen Garay Montiel,Mathias Cook,Misbah Unnisa,Paul Tarnasky,Peter Hegyi,Pramod Garg,Rasmus Bach Nedergaard,Robert Edwards,Rupjyoti Talukdar,Shagufta Farheen,Søren Schou Olesen,Soumya Jagannath,Suzette Schmidt,Vikesh Singh,Zoltán Hajnády,Asbjørn Mohr Drewes,
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引用次数: 0

摘要

引言 疼痛是慢性胰腺炎(CP)最主要的并发症,约 70% 的患者会出现疼痛。然而,对 CP 相关疼痛的病理生理学理解和管理却很复杂,这可能是因为患者有不同的 "疼痛表型",对治疗的反应也不尽相同。本研究旨在开发床旁测试面板,以识别不同的疼痛表型,研究其时间演变,并确定它们是否可用于预测治疗反应。 方法 INPAIN 研究是一项国际性、多中心、观察性、纵向队列研究,由 4 项子研究组成。这些研究将前瞻性地招募 400 名 CP 患者(50 名无痛患者和 350 名有痛患者)和 50 名对照组受试者,每半年进行一次观察,为期四年。测试面板由全面的主观和客观评估参数组成。各项子研究的统计分析策略各不相同。将利用各种机器学习技术(包括人工智能方法)开发一个预测疗效的模型,并进行内部交叉验证。疼痛参数的轨迹将通过图形分析和混合效应模型进行描述。该工具有望实现个性化治疗、改善临床实践、加强患者护理、提高生活质量并最大限度地减少治疗副作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Individualized Pain Treatment in Chronic Pancreatitis (INPAIN): An International, Multicenter, Investigator-initiated, Prospective, Cohort Study.
INTRODUCTION Pain is the foremost complication of chronic pancreatitis (CP), affecting about 70% of patients. However, the pathophysiological understanding and management of CP-related pain is complex, likely as patients have diverse "pain phenotypes" responding differently to treatment. This study aims to develop a bedside test panel to identify distinct pain phenotypes, investigate the temporal evolution, and determine whether they can be used to predict treatment response. METHOD The INPAIN study is an international, multi-center, observational, longitudinal cohort study comprised of 4 sub-studies. The studies will prospectively enroll 400 CP patients (50 without pain and 350 with pain) and 50 control subjects, conducting biannual observations for four years. The test panel is comprised of comprehensive subjective and objective assessment parameters. Statistical analysis strategies differ across the sub-studies. A model to predict treatment efficacy will be developed using various machine learning techniques, including an artificial intelligence approach, with internal cross-validation. Trajectories in pain parameters will be characterized by graphical analysis and mixed effect models. DISCUSSION The INPAIN study aims to comprehensively understand pain in CP through a test panel developed for routine clinical use. This tool has the potential to personalize treatments, improve clinical practice, enhance patient care, improve quality of life, and minimize treatment side effects.
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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