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使用在线便利样本中的影响分层评分对非特异性慢性下腰痛患者进行分类。

Classifying patients with non-specific chronic low back pain using the impact stratification score in an online convenience sample.

机构信息

RAND Corporation, Behavioral and Policy Sciences, 20 Park Plaza #920, Boston, MA, 02116, USA.

RAND Corporation, Behavioral and Policy Sciences, 1776 Main Street, Santa Monica, CA, USA.

出版信息

BMC Musculoskelet Disord. 2023 Sep 9;24(1):719. doi: 10.1186/s12891-023-06848-2.

Abstract

BACKGROUND

In 2014, the National Institute of Health Pain Consortium's research task force (RTF) on research standards for chronic low back pain (CLBP) proposed the Impact Stratification Score (ISS) as a patient-reported outcome measure that could stratify patients by the impact CLBP has on their lives. This work compares three newly developed ISS-based classifications to the RTF's original to provide an optimal recommendation.

METHODS

The online sample included 1226 individuals from Amazon's Mechanical Turk who indicated having non-specific CLBP, average age of 40, 49% female, and 67% White. Participants completed the PROMIS-29 v2.1 profile survey that contains the 9 ISS items as well the Roland-Morris Disability Questionnaire (RMDQ) and Graded Chronic Pain Scale (GCPS). Other items included high-impact chronic pain; not working due to health problems; overall health; and number of healthcare visits for back pain in the past 6 months. Three new classifications were created using quartiles (Classification 2), latent profile analysis (Classification 3), and one modeled after the GCPS (Classification 4). Classifications were subsequently compared to the RTF-proposed classification (Classification 1) on several concurrent and prognostic criteria.

RESULTS

Classification 1 had three CLBP severity groups, four in Classification 2, three in Classification 3, and four in Classification 4. All novel classifications improved upon the original. Classification 2 performed best at minimizing the classification of those with negative outcomes into the lowest severity groups at baseline (e.g., 11% with RMDQ ≥ 7) and 6 months (e.g., 8.2% had fair/poor health). Classification 4 performed best at maximizing classification of those with negative outcomes into the most severe group concurrently (e.g., 100% had GCPS grade ≥ 2) and at 6 months (e.g., 100% with RMDQ ≥ 7).

CONCLUSIONS

We developed three ISS-based classification schemes and tested them against several outcomes. All three improved upon the original scheme. While appearing more optimal than other classifications in the lowest severity groups, Classification 2 presents some considerations and limitations. Given that Classification 4 was an improvement at the lowest end of severity and was the best at the highest end, it is our tentative recommendation that this approach be adopted to classify individuals with non-specific CLBP.

摘要

背景

2014 年,美国国立卫生研究院疼痛联合会的慢性下背痛(CLBP)研究标准研究工作组(RTF)提出了影响分层评分(ISS),作为一种可以根据 CLBP 对患者生活的影响对患者进行分层的患者报告结局测量。这项工作比较了三种新开发的基于 ISS 的分类方法与 RTF 的原始分类方法,以提供最佳建议。

方法

在线样本包括来自亚马逊 Mechanical Turk 的 1226 名个体,他们表示患有非特异性 CLBP,平均年龄 40 岁,女性占 49%,白人占 67%。参与者完成了 PROMIS-29 v2.1 概况调查,该调查包含 9 个 ISS 项目以及 Roland-Morris 残疾问卷(RMDQ)和分级慢性疼痛量表(GCPS)。其他项目包括高影响慢性疼痛;因健康问题而无法工作;总体健康状况;以及过去 6 个月内因背痛就诊的次数。使用四分位数(分类 2)、潜在剖面分析(分类 3)和模拟 GCPS 的方法(分类 4)创建了三种新的分类方法。随后,根据几种同时存在的和预后的标准,将分类方法与 RTF 提出的分类(分类 1)进行比较。

结果

分类 1 有三个 CLBP 严重程度组,分类 2 有四个,分类 3 有三个,分类 4 有四个。所有新的分类方法都优于原始分类方法。在基线时(例如,RMDQ≥7 的有 11%)和 6 个月时(例如,健康状况良好/差的有 8.2%),将具有负面结果的患者分类到最低严重程度组的人数最少,分类 2 的效果最佳。在同时将具有负面结果的患者分类到最严重组的人数最多(例如,GCPS 等级≥2 的有 100%),以及在 6 个月时(例如,RMDQ≥7 的有 100%),分类 4 的效果最佳。

结论

我们开发了三种基于 ISS 的分类方案,并对它们进行了多种结果的测试。所有三种分类方法都优于原始方案。虽然分类 2 在最低严重程度组中看起来比其他分类方法更优,但它存在一些考虑因素和局限性。由于分类 4 在严重程度的最低端有所改进,在最高端表现最佳,因此我们暂定建议采用这种方法来对非特异性 CLBP 患者进行分类。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64dc/10492344/a4394ca32922/12891_2023_6848_Fig1_HTML.jpg

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