Suppr超能文献

老年患者因背部疼痛寻求初级保健后无法康复的预测模型的外部验证和更新。

External validation and updating of prognostic prediction models for nonrecovery among older adults seeking primary care for back pain.

机构信息

Department of Rehabilitation Science and Health Technology, Faculty of Health Science, OsloMet-Oslo Metropolitan University, Oslo, Norway.

Research and Communication Unit for Musculoskeletal Health (FORMI), Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway.

出版信息

Pain. 2023 Dec 1;164(12):2759-2768. doi: 10.1097/j.pain.0000000000002974. Epub 2023 Jul 24.

Abstract

Prognostic prediction models for 3 different definitions of nonrecovery were developed in the Back Complaints in the Elders study in the Netherlands. The models' performance was good (optimism-adjusted area under receiver operating characteristics [AUC] curve ≥0.77, R2 ≥0.3). This study aimed to assess the external validity of the 3 prognostic prediction models in the Norwegian Back Complaints in the Elders study. We conducted a prospective cohort study, including 452 patients aged ≥55 years, seeking primary care for a new episode of back pain. Nonrecovery was defined for 2 outcomes, combining 6- and 12-month follow-up data: Persistent back pain (≥3/10 on numeric rating scale) and persistent disability (≥4/24 on Roland-Morris Disability Questionnaire). We could not assess the third model (self-reported nonrecovery) because of substantial missing data (>50%). The models consisted of biopsychosocial prognostic factors. First, we assessed Nagelkerke R2 , discrimination (AUC) and calibration (calibration-in-the-large [CITL], slope, and calibration plot). Step 2 was to recalibrate the models based on CITL and slope. Step 3 was to reestimate the model coefficients and assess if this improved performance. The back pain model demonstrated acceptable discrimination (AUC 0.74, 95% confidence interval: 0.69-0.79), and R2 was 0.23. The disability model demonstrated excellent discrimination (AUC 0.81, 95% confidence interval: 0.76-0.85), and R2 was 0.35. Both models had poor calibration (CITL <0, slope <1). Recalibration yielded acceptable calibration for both models, according to the calibration plots. Step 3 did not improve performance substantially. The recalibrated models may need further external validation, and the models' clinical impact should be assessed.

摘要

在荷兰的 Back Complaints in the Elders 研究中,针对 3 种不同的非恢复定义开发了预后预测模型。这些模型的性能较好(经乐观调整的接受者操作特征曲线下面积[AUC]曲线≥0.77,R2≥0.3)。本研究旨在评估 3 种预后预测模型在挪威 Back Complaints in the Elders 研究中的外部有效性。我们进行了一项前瞻性队列研究,纳入了 452 名年龄≥55 岁、因新发腰痛到初级保健就诊的患者。非恢复的定义是基于 6 个月和 12 个月随访数据的 2 个结局:持续性腰痛(数字评分量表≥3/10)和持续性残疾(Roland-Morris 残疾问卷≥4/24)。由于大量数据缺失(>50%),我们无法评估第三个模型(自我报告的非恢复)。这些模型包含生物心理社会预后因素。首先,我们评估了 Nagelkerke R2、区分度(AUC)和校准(大校准[CITL]、斜率和校准图)。第二步是根据 CITL 和斜率重新校准模型。第三步是重新估计模型系数,并评估这是否可以改善性能。腰痛模型的区分度可接受(AUC 0.74,95%置信区间:0.69-0.79),R2 为 0.23。残疾模型的区分度极好(AUC 0.81,95%置信区间:0.76-0.85),R2 为 0.35。两个模型的校准均较差(CITL<0,斜率<1)。根据校准图,重新校准后两个模型的校准均有所改善。第三步并没有显著提高性能。重新校准的模型可能需要进一步的外部验证,还应评估模型的临床影响。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验