Heymans Martijn W, Anema Johannes R, van Buuren Stef, Knol Dirk L, van Mechelen Willem, de Vet Henrica C W
Body@Work, Work and Health, Research Center Physical Activity, TNO-VUmc, Amsterdam, The Netherlands.
J Occup Rehabil. 2009 Jun;19(2):155-65. doi: 10.1007/s10926-009-9166-3. Epub 2009 Feb 18.
From the viewpoint of cost prevention, it is necessary to identify patients that are of high risk for long-term work disability, production loss and sick-leave.
Secondary data analysis in a cohort of 628 workers on sick-leave between 3 and 6 weeks due to low back pain (LBP). The association of a broad set of demographic, work, LBP and psychosocial related factors on lasting return to work was studied using Cox regression analysis with backward selection. The most relevant factors were used to derive a clinical prediction rule to determine the risk of sick-leave of more than 6 months. Variable and model selection and clinical model performance were performed with bootstrapping techniques. Also the test characteristics of the clinical model were considered.
Longer work absence is related to "moderate" to "poor" job satisfaction, a higher score of fear avoidance beliefs, higher pain intensity at baseline, a longer duration of complaints and being of female gender. Calibration and discrimination of the clinical prediction rule were 0.90 (slope) and 0.63 (c-index), respectively. The explained variance of 6% of the prediction rule was low and the clinical performance in terms of sensitivity, specificity, positive and negative predictive values at specific cut-off points was moderate.
Our study confirmed the importance of demographic, work, LBP and psychosocial related factors on the prediction of long-term sick-leave. When these factors were used to derive a clinical prediction rule the performance was moderate. As a consequence, prudence has to be taken when using the prediction rule in practice.
从成本预防的角度来看，有必要识别出那些长期工作残疾、生产损失和病假风险较高的患者。
对628名因腰痛（LBP）而休病假3至6周的工人队列进行二次数据分析。使用带有向后选择的Cox回归分析研究了一系列广泛的人口统计学、工作、腰痛和社会心理相关因素与持续重返工作之间的关联。使用最相关的因素得出临床预测规则，以确定病假超过6个月的风险。采用自抽样技术进行变量和模型选择以及临床模型性能评估。同时考虑了临床模型的检验特征。
较长时间的缺勤与“中等”至“较差”的工作满意度、较高的恐惧回避信念得分、基线时较高的疼痛强度、较长的投诉持续时间以及女性性别有关。临床预测规则的校准度和辨别力分别为0.90（斜率）和0.63（c指数）。预测规则6%的解释方差较低，在特定临界点的敏感性、特异性、阳性和阴性预测值方面的临床性能中等。
我们的研究证实了人口统计学、工作、腰痛和社会心理相关因素在预测长期病假方面的重要性。当使用这些因素得出临床预测规则时，性能中等。因此，在实践中使用该预测规则时必须谨慎。
