Clinical and Psychosocial Predictors of Urological Chronic Pelvic Pain Symptom Change in 1 Year: A Prospective Study from the MAPP Research Network

泌尿系统慢性盆腔疼痛症状一年内变化的临床和社会心理预测因素:来自MAPP研究网络的前瞻性研究

阅读:1

Abstract

PURPOSE: We examined baseline clinical and psychosocial characteristics that predict 12-month symptom change in men and women with urological chronic pelvic pain syndromes. MATERIALS AND METHODS: A total of 221 female and 176 male patients with urological chronic pelvic pain syndromes were recruited from 6 academic medical centers in the United States and evaluated at baseline with a comprehensive battery of symptom, psychosocial and illness-impact measures. Based on biweekly symptom reports, a functional clustering procedure classified participant outcome as worse, stable or improved on pain and urinary symptom severity. Cumulative logistic modeling was used to examine individual predictors associated with symptom change as well as multiple predictor combinations and interactions. RESULTS: About 60% of participants had stable symptoms with smaller numbers (13% to 22%) showing clear symptom worsening or improvement. For pain and urinary outcomes the extent of widespread pain, amount of nonurological symptoms and poorer overall health were predictive of worsening outcomes. Anxiety, depression and general mental health were not significant predictors of outcomes but pain catastrophizing and self-reported stress were associated with pain outcome. Prediction models did not differ between men and women and for the most part they were independent of symptom duration and age. CONCLUSIONS: These results demonstrate for the first time in a large multisite prospective study that presence of widespread pain, nonurological symptoms and poorer general health are risk factors for poorer pain and urinary outcomes in men and women. The results point to the importance of broad based assessment for urological chronic pelvic pain syndromes and future studies of the mechanisms that underlie these findings.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。