Suppr超能文献

预测持续性躯体症状的病程:对症状严重程度和功能状态进行 2 年随访的预测模型的开发和内部验证。

Predicting the course of persistent physical symptoms: Development and internal validation of prediction models for symptom severity and functional status during 2 years of follow-up.

机构信息

Department of General Practice and Elderly Care Medicine, VU University Medical Center Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.

Department of General Practice and Elderly Care Medicine, VU University Medical Center Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.

出版信息

J Psychosom Res. 2018 May;108:1-13. doi: 10.1016/j.jpsychores.2018.02.009. Epub 2018 Feb 21.

Abstract

OBJECTIVE

Increased knowledge about predictors of the course of persistent physical symptoms (PPS) is needed to identify patients at risk for long-term PPS in clinical settings. Therefore, we developed prediction models for the course of PPS in terms of symptom-severity and related functional status during a 2-year follow-up period.

METHODS

We used data of the PROSPECTS cohort study, consisting of 325 PPS patients from several health care settings. Symptom severity (PHQ-15), physical functioning (RAND 36 PCS) and mental functioning (RAND 36 MCS) were assessed at baseline and 6, 12 and 24 months afterwards. We applied mixed model analyses to develop prediction models for all outcomes, using all follow-up measurements. Potential predictors were based on empirical and theoretical literature and measured at baseline.

RESULTS

For symptom severity, physical functioning and mental functioning we identified predictors for the adverse course of PPS included physical comorbidity, higher severity and longer duration of PPS at baseline, anxiety, catastrophizing cognitions, embarrassment and fear avoidance cognitions, avoidance or resting behaviour and neuroticism. Predictors of a favourable course included limited alcohol use, higher education, higher levels of physical and mental functioning at baseline, symptom focusing, damage cognitions and extraversion. Explained interpersonal variance for all three models varied between 70.5 and 76.0%. Performance of the models was comparable in primary and secondary/tertiary care.

CONCLUSION

The presented prediction models identified several relevant demographic, medical, psychological and behavioural predictors for adverse and favourable courses of PPS. External validation of the presented models is needed prior to clinical implementation.

摘要

目的

需要更多关于持续性身体症状(PPS)病程预测因素的知识,以便在临床环境中识别出长期 PPS 风险患者。因此,我们针对 2 年随访期间的症状严重程度和相关功能状态,开发了 PPS 病程预测模型。

方法

我们使用了 PROSPECTS 队列研究的数据,该研究包含了来自多个医疗保健机构的 325 名 PPS 患者。在基线和 6、12 和 24 个月后,评估了症状严重程度(PHQ-15)、身体功能(RAND 36 PCS)和心理功能(RAND 36 MCS)。我们应用混合模型分析,使用所有随访测量数据,为所有结局开发预测模型。潜在预测因素基于经验和理论文献,并在基线时进行测量。

结果

对于症状严重程度、身体功能和心理功能,我们确定了 PPS 不良病程的预测因素,包括身体合并症、基线时 PPS 的严重程度和持续时间更高、焦虑、灾难化认知、尴尬和恐惧回避认知、回避或休息行为以及神经质。有利病程的预测因素包括有限的饮酒、较高的教育程度、基线时较高的身体和心理功能水平、症状聚焦、损害认知和外向性。所有三个模型的人际方差解释率在 70.5%至 76.0%之间。初级和二级/三级保健中的模型性能相当。

结论

所提出的预测模型确定了几个与不良和有利 PPS 病程相关的人口统计学、医学、心理和行为预测因素。在临床实施之前,需要对所提出的模型进行外部验证。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验