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压力与疼痛。慢性背痛的预测性(神经)模式识别:一项纵向观察研究。

Stress and Pain. Predictive (Neuro)Pattern Identification for Chronic Back Pain: A Longitudinal Observational Study.

作者信息

Wippert Pia-Maria, Puerto Valencia Laura, Drießlein David

机构信息

Medical Sociology and Psychobiology, University of Potsdam, Potsdam, Germany.

Faculty of Health Sciences, Joint Faculty of the University of Potsdam, Brandenburg Medical School Theodor Fontane, and the Brandenburg University of Technology Cottbus-Senftenberg, Postdam, Germany.

出版信息

Front Med (Lausanne). 2022 May 10;9:828954. doi: 10.3389/fmed.2022.828954. eCollection 2022.

DOI:10.3389/fmed.2022.828954
PMID:35620722
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9129900/
Abstract

INTRODUCTION

Low back pain (LBP) leads to considerable impairment of quality of life worldwide and is often accompanied by psychosomatic symptoms.

OBJECTIVES

First, to assess the association between stress and chronic low back pain (CLBP) and its simultaneous appearance with fatigue and depression as a symptom triad. Second, to identify the most predictive stress-related pattern set for CLBP for a 1-year diagnosis.

METHODS

In a 1-year observational study with four measurement points, a total of 140 volunteers (aged 18-45 years with intermittent pain) were recruited. The primary outcomes were pain [characteristic pain intensity (CPI), subjective pain disability (DISS)], fatigue, and depressive mood. Stress was assessed as chronic stress, perceived stress, effort reward imbalance, life events, and physiological markers [allostatic load index (ALI), hair cortisol concentration (HCC)]. Multiple linear regression models and selection procedures for model shrinkage and variable selection (least absolute shrinkage and selection operator) were applied. Prediction accuracy was calculated by root mean squared error (RMSE) and receiver-operating characteristic curves.

RESULTS

There were 110 participants completed the baseline assessments (28.2 ± 7.5 years, 38.1% female), including HCC, and a further of 46 participants agreed to ALI laboratory measurements. Different stress types were associated with LBP, CLBP, fatigue, and depressive mood and its joint occurrence as a symptom triad at baseline; mainly social-related stress types were of relevance. Work-related stress, such as "excessive demands at work"[ = 0.51 (95%CI -0.23, 1.25), = 0.18] played a role for upcoming chronic pain disability. "Social overload" [ = 0.45 (95%CI -0.06, 0.96), = 0.080] and "over-commitment at work" [ = 0.28 (95%CI -0.39, 0.95), = 0.42] were associated with an upcoming depressive mood within 1-year. Finally, seven psychometric (CPI: RMSE = 12.63; DISS: RMSE = 9.81) and five biomarkers (CPI: RMSE = 12.21; DISS: RMSE = 8.94) could be derived as the most predictive pattern set for a 1-year prediction of CLBP. The biomarker set showed an apparent area under the curve of 0.88 for CPI and 0.99 for DISS.

CONCLUSION

Stress disrupts allostasis and favors the development of chronic pain, fatigue, and depression and the emergence of a "hypocortisolemic symptom triad," whereby the social-related stressors play a significant role. For translational medicine, a predictive pattern set could be derived which enables to diagnose the individuals at higher risk for the upcoming pain disorders and can be used in practice.

摘要

引言

腰痛(LBP)在全球范围内导致生活质量的显著下降,并且常常伴有身心症状。

目的

第一,评估压力与慢性腰痛(CLBP)之间的关联以及其与疲劳和抑郁作为一组症状同时出现的情况。第二,确定对于CLBP进行1年诊断的最具预测性的压力相关模式集。

方法

在一项为期1年、有四个测量点的观察性研究中,共招募了140名志愿者(年龄在18 - 45岁之间,有间歇性疼痛)。主要结局指标为疼痛[特征性疼痛强度(CPI)、主观疼痛残疾程度(DISS)]、疲劳和抑郁情绪。压力被评估为慢性压力、感知压力、工作投入与回报失衡、生活事件以及生理指标[应激负荷指数(ALI)、头发皮质醇浓度(HCC)]。应用了多元线性回归模型以及用于模型收缩和变量选择的程序(最小绝对收缩和选择算子)。通过均方根误差(RMSE)和受试者工作特征曲线计算预测准确性。

结果

110名参与者完成了包括HCC在内的基线评估(年龄28.2±7.5岁,女性占38.1%),另有46名参与者同意进行ALI实验室测量。不同类型的压力与LBP、CLBP、疲劳和抑郁情绪及其在基线时作为一组症状共同出现有关;主要是与社会相关的压力类型具有相关性。与工作相关的压力,如“工作要求过高”[β = 0.51(95%CI -0.23,1.25),P = 0.18]对即将出现的慢性疼痛残疾起作用。“社会负担过重”[β = 0.45(95%CI -0.06,0.96),P = 0.080]和“工作过度投入”[β = 0.28(95%CI -0.39,0.95),P = 0.42]与1年内即将出现的抑郁情绪相关。最后,七个心理测量指标(CPI:RMSE = 12.63;DISS:RMSE = 9.81)和五个生物标志物(CPI:RMSE = 12.21;DISS:RMSE = 8.94)可作为对CLBP进行1年预测的最具预测性的模式集推导得出。该生物标志物集对于CPI的曲线下面积为0.88,对于DISS为0.99。

结论

压力会破坏内稳态,促进慢性疼痛、疲劳和抑郁的发展以及“低皮质醇症状三联征”的出现,其中与社会相关的应激源起重要作用。对于转化医学而言,可以推导得出一个预测模式集,能够诊断出即将出现疼痛性疾病风险较高的个体,并可在实践中应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90fd/9129900/8f4688be72e6/fmed-09-828954-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90fd/9129900/f63cc0457318/fmed-09-828954-g001.jpg
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