{"title":"Development of Prediction Model for the Prognosis of Sick Leave Due to Low Back Pain.","authors":"Lisa C. Bosman, J. Twisk, A. Geraedts, M. Heymans","doi":"10.1097/JOM.0000000000001749","DOIUrl":null,"url":null,"abstract":"OBJECTIVE\nThe aim of this study was to develop a prediction model for the prognosis of sick leave due to low back pain (LBP).\n\n\nMETHODS\nThis is a cohort study with 103 employees sick-listed due to non-specific LBP and spinal disc herniation. A prediction model was developed based on questionnaire data and registered sick leave data with follow up of 180 days.\n\n\nRESULTS\nAt follow up 31 (30.1%) employees were still sick-listed due to LBP. Forward selection procedure resulted in a model with: catastrophizing, musculoskeletal work load, and disability. The explained variance was 27.3%, calibration was adequate and discrimination was fair with AUC = 0.761 [IQR: 0.755-0.770].\n\n\nCONCLUSION\nThe prediction model of this study can adequately predict LBP sick leave after 180 days and could be used for employees sick listed due LBP.","PeriodicalId":46545,"journal":{"name":"International Journal of Occupational and Environmental Medicine","volume":"11 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Occupational and Environmental Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/JOM.0000000000001749","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 7
Abstract
OBJECTIVE
The aim of this study was to develop a prediction model for the prognosis of sick leave due to low back pain (LBP).
METHODS
This is a cohort study with 103 employees sick-listed due to non-specific LBP and spinal disc herniation. A prediction model was developed based on questionnaire data and registered sick leave data with follow up of 180 days.
RESULTS
At follow up 31 (30.1%) employees were still sick-listed due to LBP. Forward selection procedure resulted in a model with: catastrophizing, musculoskeletal work load, and disability. The explained variance was 27.3%, calibration was adequate and discrimination was fair with AUC = 0.761 [IQR: 0.755-0.770].
CONCLUSION
The prediction model of this study can adequately predict LBP sick leave after 180 days and could be used for employees sick listed due LBP.
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