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A prospective, longitudinal study to evaluate the clinical utility of a predictive algorithm that detects risk of opioid use disorder

机译:一项前瞻性纵向研究,用于评估检测阿片类药物使用障碍风险的预测算法的临床效用

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Purpose: The purpose of this study was to determine the clinical utility of an algorithm-based decision tool designed to assess risk associated with opioid use. Specifically, we sought to assess how physicians were using the profile in patient care and how its use affected patient outcomes. Patients and methods: A prospective, longitudinal study was conducted to assess the utility of precision medicine testing in 5,397 patients across 100 clinics in the USA. Using a patent-protected, validated algorithm combining specific genetic risk factors with phenotypic traits, patients were categorized into low-, moderate-, and high-risk patients for opioid abuse. Physicians who ordered precision medicine testing were asked to complete patient evaluations and document their actions, decisions, and perceptions regarding the utility of the precision medicine tests. The patient outcomes associated with each treatment action were carefully documented. Results: Physicians used the profile to guide treatment decisions for over half of the patients. Of those, guided treatment decisions for 24.5% of the patients were opioid related, including changing the opioid prescribed, starting an opioid, or titrating a patient off the opioid. Treatment guidance was strongly influenced by profile-predicted opioid use disorder (OUD) risk. Most importantly, patients whose physicians used the profile to guide opioid-related treatment decisions had improved clinical outcomes, including better pain management by medication adjustments, with an average pain decrease of 3.4 points on a scale of 1–10. Conclusion: Patients whose physicians used the profile to guide opioid-related treatment decisions had improved clinical outcomes, as measured by decreased pain levels resulting from better pain management with prescribed medications. The clinical utility of the profile is twofold. It provides clinically actionable recommendations that can be used to 1) prevent OUD through limiting initial opioid prescriptions and 2) reduce pain in patients at low risk of developing OUD.
机译:目的:本研究的目的是确定旨在评估与阿片类药物使用相关的风险的基于算法的决策工具的临床效用。具体来说,我们试图评估医生如何在患者护理中使用此配置文件以及其使用如何影响患者的预后。患者和方法:进行了一项前瞻性纵向研究,以评估美国100所诊所中的5397例患者进行精确医学测试的效用。使用结合了特定遗传风险因素和表型特征的专利保护的经过验证的算法,将患者分为阿片类药物滥用的低,中和高风险患者。要求订购精确医学测试的医师完成对患者的评估,并记录他们对精确医学测试的效用的行动,决策和看法。仔细记录了与每种治疗措施相关的患者预后。结果:医师使用该配置文件来指导一半以上患者的治疗决策。其中,针对24.5%的患者的指导治疗决策与阿片类药物有关,包括更改处方的阿片类药物,开始使用阿片类药物或从阿片类药物中滴定患者。轮廓预测的阿片类药物使用障碍(OUD)风险极大地影响了治疗指导。最重要的是,其医师使用此配置文件来指导与阿片类药物相关的治疗决定的患者改善了临床结局,包括通过药物调整更好地控制了疼痛,平均疼痛减轻了3.4点(1-10分)。结论:医生通过使用该配置文件指导与阿片类药物相关的治疗决定的患者的临床结局得到改善,这可以通过使用处方药更好地控制疼痛来减轻疼痛程度来衡量。该配置文件的临床用途是双重的。它提供了可用于临床的建议,可用于1)通过限制初始阿片类药物处方预防OUD,以及2)降低发生OUD风险较低的患者的疼痛。

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