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包含第二代数字健康系统的数字镇痛法:通过优化剂量和最小化副作用提高疗效

Digital Analgesic Comprising a Second-Generation Digital Health System: Increasing Effectiveness by Optimizing the Dosing and Minimizing Side Effects.

作者信息

Azmanov Henny, Bayatra Areej, Ilan Yaron

机构信息

Hebrew University, Faculty of Medicine, Hadassah Medical Center, Jerusalem, Israel.

出版信息

J Pain Res. 2022 Apr 13;15:1051-1060. doi: 10.2147/JPR.S356319. eCollection 2022.

Abstract

Opioids remain an essential part of the treatment of chronic pain. However, their use and increasing rates of misuse are associated with high morbidity and mortality. The development of tolerance to opioids and analgesics further complicates dosing and the need to reduce side effects. First-generation digital systems were developed to improve analgesics but are not always capable of making clinically relevant associations and do not necessarily lead to better clinical efficacy. A lack of improved clinical outcomes makes these systems less applicable for adoption by clinicians and patients. There is a need to enhance the therapeutic regimens of opioids. In the present paper, we present the use of a digital analgesic that consists of an analgesic administered under the control of a second-generation artificial intelligence system. Second-generation systems focus on improved patient outcomes measured based on clinical response and reduced side effects in a single subject. The algorithm regulates the administration of analgesics in a personalized manner. The digital analgesic provides advantages for both users and providers. The system enables dose optimization, improving effectiveness, and minimizing side effects while increasing adherence to beneficial therapeutic regimens. The algorithm improves the clinicians' experience and assists them in managing chronic pain. The system reduces the financial burden on healthcare providers by lowering opioid-related morbidity and provides a market disruptor for pharma companies.

摘要

阿片类药物仍然是慢性疼痛治疗的重要组成部分。然而,它们的使用以及滥用率的上升与高发病率和死亡率相关。对阿片类药物和镇痛药产生耐受性进一步使给药复杂化,并增加了减少副作用的需求。第一代数字系统旨在改善镇痛效果,但并不总是能够建立与临床相关的联系,也不一定能带来更好的临床疗效。缺乏改善的临床结果使得这些系统不太适用于临床医生和患者采用。有必要加强阿片类药物的治疗方案。在本文中,我们介绍了一种数字镇痛药的使用,它由在第二代人工智能系统控制下给药的镇痛药组成。第二代系统侧重于根据临床反应衡量的改善患者预后,并减少单个受试者的副作用。该算法以个性化方式调节镇痛药的给药。数字镇痛药为用户和提供者都带来了优势。该系统能够实现剂量优化,提高疗效,将副作用降至最低,同时提高对有益治疗方案的依从性。该算法改善了临床医生的体验,并协助他们管理慢性疼痛。该系统通过降低与阿片类药物相关的发病率减轻了医疗保健提供者的经济负担,并为制药公司提供了一个市场颠覆者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8262/9013915/aad01bafd5a6/JPR-15-1051-g0001.jpg

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