SOMT University of Physiotherapy, Amersfoort, The Netherlands; Department of General Practice, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.
Department of General Practice, Erasmus MC, University Medical Center, Rotterdam, The Netherlands; Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, The Netherlands.
Physiotherapy. 2021 Dec;113:61-72. doi: 10.1016/j.physio.2021.05.011. Epub 2021 Jun 12.
Development and internal validation of prognostic models for post-treatment and 1-year recovery in patients with neck pain in primary care.
Prospective cohort study.
Primary care manual therapy practices.
Patients with non-specific neck pain of any duration (n=1193).
Usual care manual therapy.
Recovery defined in terms of pain intensity, disability, and global perceived improvement directly post-treatment and at 1-year follow-up.
All post-treatment models exhibited acceptable discriminative performance after derivation (AUC≥0.7). The developed post-treatment disability model exhibited the best overall performance (R=0.24; IQR, 0.22-0.26), discrimination (AUC=0.75; 95% CI, 0.63-0.84), and calibration (slope 0.92; IQR, 0.91-0.93). After internal validation and penalization, this model retained acceptable discriminative performance (AUC=0.74). The five other models, including those predicting 1-year recovery, did not reach acceptable discriminative performance after internal validation. Baseline pain duration, disability, and pain intensity were consistent predictors across models.
A post-treatment prognostic model for disability was successfully developed and internally validated. This model has potential to inform primary care clinicians about a patient's individual prognosis after treatment, but external validation is required before clinical use can be recommended.
为初级保健中颈部疼痛患者的治疗后和 1 年恢复建立预测模型并进行内部验证。
前瞻性队列研究。
初级保健手法治疗诊所。
持续时间不限的非特异性颈部疼痛患者(n=1193)。
常规手法治疗。
直接治疗后和 1 年随访时,以疼痛强度、残疾和整体感知改善来定义恢复。
所有治疗后模型在推导后均显示出可接受的区分性能(AUC≥0.7)。所开发的治疗后残疾模型表现出最佳的整体性能(R=0.24;IQR,0.22-0.26)、区分能力(AUC=0.75;95%CI,0.63-0.84)和校准(斜率 0.92;IQR,0.91-0.93)。经过内部验证和惩罚后,该模型仍保持可接受的区分性能(AUC=0.74)。其他五个模型,包括预测 1 年恢复的模型,在内部验证后均未达到可接受的区分性能。基线疼痛持续时间、残疾和疼痛强度是各模型中的一致预测因素。
成功开发并内部验证了一种治疗后残疾预测模型。该模型有可能为初级保健临床医生提供有关患者治疗后个体预后的信息,但在推荐临床使用之前需要进行外部验证。